This Deep Learning Technology Is Redefining Ad Integrity

By Russ Banham

Perspectives

In the pre-social media era, marketers had a good idea about how many times consumers saw their corporate logo and other brand images. Then, around 2010, after social media sites took off, millions of people could see a company’s logo, unbeknownst to the organization. That was both good and bad news.

While exposing people to a company’s logo could, in theory, make them more familiar with the brand, products, and services, there was also the possibility the image could be put into a negative context and go viral. Until recently, marketers had no way to monitor the use of their advertising images by third parties.

Today, deep learning makes this possible. Computer vision, a subset of deep learning technology, gives marketers insights into how many people have viewed a logo or other brand images, in addition to their context.

“The use of computer vision for marketing purposes is becoming an increasingly common application of deep learning technology,” said Clement Chung, director of machine learning at Wave Financial, a provider of integrated software and tools for small businesses. “Companies can see just how they are being represented in online images, both positively and negatively.”

Ad Impact, Across Mediums

Deep learning is a subset of machine learning, itself a subset of artificial intelligence, in which computers are instructed to learn by example. For instance, in self-driving cars, the car’s computer is instructed to stop at a red light. Once the car is programmed to do so, the machine will know to stop at all red lights.

Computer vision technology, then, uses object recognition software to tabulate how many times an ad or logo has been viewed in social or traditional media, and the context in which the image appeared.

“The technique involves two parts—the development of an algorithm to train the computer to find the image, and then the use of object recognition to determine the context of the image,” said Chung.

This has to two positive effects for marketers. To begin, it helps them identify how many times an ad was viewed outside of its original distribution campaign. If we were to consider a Dodgers Stadium beer ad, for example, computer vision technology could provide a way to calculate how many times the billboard at the game was seen both on social media and traditional media. If the game is televised, chances are local and even national news stations may also carry images of the event in which the billboard ad is visible.

Detecting viewership can help marketing teams decide where to put ad dollars. “What if the ratings on the televised event have dropped significantly, meaning fewer people are seeing it at home?” Brian Kim, senior vice president of product at GumGum, a leading computer vision company,said. “This might convince the marketer to put its spend elsewhere.”

Using computer vision, companies can calculate if more people saw the image on social media or other media than the TV ratings indicate. “That’s a far better determinant of the advertisement’s value,” Kim noted.

Chung agreed, stating that a marketer may also discover things like a billboard placed behind the catcher was seen by more people than one situated in left field. “The goal in all cases is to get a bigger bang for your advertising dollar,” he said.

An Opportunity Algorithm

The technology also identifies missed opportunities and flags necessary damage control. If the context is positive, the company has the opportunity to push the advertised image toward becoming viral.

However, there is also the risk that an image of the brand or its logo could become a “meme of the worst kind, used for satirical purposes,” said Chung. “In such cases, the product’s brand value can quickly erode, especially if the marketer is unaware of the negative associations and is too late to do anything about it.”

Computer vision offers a way to be notified in real time about insulting brand imagery. “An algorithm can be created to spot the use of certain offensive words that accompany the image on social media,” Chung pointed out. One obvious example, he noted: “This product sucks!”

With the emerging technology, marketers have the ability to counter the offense. “There have been memes created by overworked millennials and teenagers fed up with too much homework where they’ve snapped a picture of themselves ‘drinking’ a household cleaning product—the ‘my fake suicide’ kind of thing,” said Kim. “With computer vision tools, brand managers have instant access to what is now a negative trend to quickly adjust the conversation in a more positive direction.”

Of course, computer vision can also help spot and seize marketing opportunities. For instance, GumGum has created a way for marketers to run an advertisement at opportune—often fleeting—moments in social media.

“We’ve developed a contextual relevance algorithm using object recognition software that can pinpoint, for example, when happy images involving humans and cats appear on social media,” said Kim. “Say this image appeared on CNN. We now have the opportunity to stick a banner ad for a national pet store chain into the image in real time. We would receive income from the pet store chain to display the advertisement and arrange for CNN to be paid a portion of the earnings.”

The technology is also able to train the algorithm to find a context in which a brand should appear in certain images, but doesn’t. With the beer company example, this might include adding logos to images of people photographed at parties, restaurants, or taverns where they know the beer is served.

“Computer vision can find images that fit the marketer’s desired demographic, and if the brand is not evident in these images, the information is nonetheless insightful for marketing purposes,” Chung said. “The company now has better intelligence on where to put its marketing spend.”

Russ Banham is a Pulitzer-nominated journalist and author who writes frequently about marketing technologies.

Meet Rose, the One-of-a-Kind Chatbot of the Future

By Russ Banham

Perspectives magazine

Her name is Rose, and she is exactly the kind of person one would expect to handle customer queries at The Cosmopolitan of Las Vegas, a hotel known for its decadent tag line, “Just the right amount of wrong.” Listening to Rose speak, she conjures images that seem to align with The Cosmopolitan’s, well, suggestive ads.

But Rose is not a person—she’s a chatbot that made her debut last year as the hotel’s virtual concierge. And today, her persona matches the attitude of many looking to escape for a weekend in Vegas.

“If you called to ask Rose something and she couldn’t answer, she will say, `Sorry, I just spilled wine on my top and need to change into something more comfortable. Let me get you to a live agent,’” said Clara de Soto, cofounder of Reply.ai, the company that created Rose’s conversational strategy in partnership with The Cosmopolitan’s digital marketing agency R/GA.

Rose is new in the world of AI chatbots, yet she’s not only a smart algorithm. She’s also a personality. As more companies create voice-enabled bots to handle customer queries, they’re realizing the value in having virtual points of contact serve as a marketing extension of their brand.

“The reality is that you’re not just building a bot,” de Soto said, “you’re building a relationship.”

Rapport Is Money

For the Cosmopolitan, this relationship also has bottom-line benefits. Guests who engage with Rose spend 30 percent more at the hotel than those who don’t. And when these guests leave, they’re 33 percent happier, too, according to the hotel’s surveys.

Of course, it isn’t always easy to capture the right personality in a chatbot. “We equate it more to a long-distance run than a sprint,” said de Soto. “The reality is it takes time to do this right. In Rose’s case, the conversational strategy planning took us a solid two years.”

Most voice-enabled chatbots continue to be menu-based, whereby a caller asks a question and is provided with three or four possible answers to pick from. More sophisticated bots like Rose leverage machine learning and, in this case, natural language processing (NLP) to understand and interpret a question before providing an answer.

Certain questions, like booking a reservation at a restaurant or buying tickets for a game or a show, are easier than others. At present, Rose has been able to successfully answer a question 80 percent of the time without turning the person over to a live human being, de Soto said.

When compared to Facebook’s Messenger chatbot that reportedly fulfilled just 30 percent of user requests in 2017, that feels like pretty high functionality. Yet, de Soto continues her work to continually increase Rose’s batting percentage. “There are so many ways of asking a question and Rose is learning all the time,” she added.

Even questions that are salacious in nature, Rose can answer. “We made sure her response was not inappropriate, yet still reflected the brand,” de Soto said.

No Two Bots Should Be Alike

According to Juniper Research, an AI-focused research firm, by replacing human beings with pre-programmed bots, companies in the retail, banking, and healthcare sectors can trim 2.5 billion hours off of the time needed for humans to respond to customer inquiries in the next five years. What’s more, the firm estimates these companies will save an estimated $11 billion in the same timeframe.

Such a dramatic savings in time and overhead is reason enough for companies across industries to invest in chatbots. Another seems to be their reliability. Unlike people, they’re never sick, tired, angry, or rude—and, they don’t make the same mistake twice, thanks to machine learning.

“Machines do things the same way all the time until they learn something new,” said Kevin Kelly, founder and co-president of New York-based digital advertising agency Bigbuzz Marketing Group.

Potential downsides, of course, include difficulties in answering tough questions, causing customer frustration, and a lack of human connection. According to a 2018 survey by consultancy PwC, 64 percent of U.S. consumers felt that brands have lost the human touch in their automated customer experiences.

However, the same study indicates that more human-like interactions could tip the scale. “Automated solutions should learn from human interactions so those experiences can improve,” the study reported.

That’s exactly the kind of work that Reply.ai is doing. “No two bots should be alike,” said de Soto. “Each must be unique because each company is unique.”

While Rose serves as an extension of the Cosmopolitan’s brand strategy, she’s not alone. De Soto aids in the development of other chatbots who do the same (albeit without the sass), working for several insurers, for instance, that need bots who show empathy. For example, upon filing a collision claim, the chatbot will state, “Oh, I’m so sorry to hear that,” before moving on to asking the next question.

Liberal Arts Majors Rejoice

One problem with previous generations of chatbots was that the IT engineers who built the underlying technology also crafted the bot’s responses. De Soto, who has a theater background as a performer, instead enlists a combination of playwrights, copy editors, sociologists, and user experience (UX) designers to humanize the dialogue elements.

In writing the scripts, these creatives collaborate with other creative people at marketing firms to ensure message and tone consistency. “There’s a new title running around called a `conversation designer,’” said Kelly. “Their job is to design chatbot responses to customer queries that sound like real people—assuming people were always smart, helpful, interesting, and fun.”

Bigbuzz is currently working with Reply.ai to develop a full-service chatbot for a large provider of smart home devices. “[De Soto’s] team is presently working on the bot’s tone of voice to give it the right personality,” he said.

And personality may be just what is needed to keep callers on the line. Kelly predicted that in five years, chatbots will become so savvy and ubiquitous, human beings will rarely provide customer service.

“A subset of AI is machine learning, which will continuously guide chatbots to learn from each customer interaction, training them to solve problems in more accurate, faster, and useful ways,” he said. “In ten years, people will be telling their children about the old days when real, live people used to answer their silly questions on their mobile phones.”

Russ Banham is a Los Angeles-based technology writer.

Critical audit matters coming into focus

By Russ Banham

Journal of Accountancy

As auditors prepare for a new auditing standard requiring the disclosure of critical audit matters (CAMs) in their reports, they are traveling in uncharted territory and contemplating new information that they will be providing to investors.

The new auditing standard AS 3101, The Auditor’s Report on an Audit of Financial Statements When the Auditor Expresses an Unqualified Opinion, adopted by the PCAOB in 2017, is predicated on enhancing the relevance and usefulness of the auditor’s report. The first phase of implementation affects PCAOB audits of companies with fiscal years ending on or after Dec. 15, 2017, and includes disclosing auditor tenure and other changes to the form and content of the auditor’s report.

The second phase of implementation requires CAMs to be disclosed in the auditor’s report beginning with fiscal years ending on or after June 30, 2019, for audits of large accelerated filers, and for all other applicable companies for fiscal years ending on or after Dec. 15, 2020. The phased implementation date gives audit firms time to develop processes around determining which items they will disclose as CAMs, which are matters that:

  • Have been communicated to the audit committee;
  • Are related to accounts or disclosures that are material to the financial statements; and
  • Involved especially challenging, subjective, or complex auditor judgment.

At present, audit firms are developing processes to ensure all their engagement partners have a consistent method to identify CAMs.

“As with all changes in our audit methodology, we will distribute implementation guidance and tools for engagement teams to implement the new standard,” said Dave Sullivan, CPA, national managing partner for quality and professional practice at Deloitte & Touche LLP. “We also plan to design and implement controls to monitor the adoption of the CAM disclosures and assure that engagement teams have considered all the requirements of the new standard while applying it to their unique client situation.”

OPPORTUNITIES AND CHALLENGES

The standard is intended to provide investors with more comprehensive information for investment decisions and is an opportunity for auditors to provide more information of value during the audit. AS 3101 requires auditors to identify a CAM, describe the principal considerations that led to its selection as such, describe how the CAM was addressed in the audit, and refer to the relevant financial statement accounts or disclosures in making these determinations. While CAMs may be matters that were traditionally discussed with audit committees, they were not discussed in an auditor’s report.

Sullivan provided an example of a CAM that might not have been disclosed in past auditor reports. “Let’s say a company with a lot of goodwill on its books is struggling,” he said. “It’s going through the process of predicting future earnings to determine whether or not the goodwill will be impaired. The projections may involve revenue and expense calculations 10 years into the future. This would fit the definition of a critical audit matter, as it is material to the financial statement and could be subjective, complex, and involve auditor judgment.”

The new standard creates several challenges for auditors, audit committees, and preparers of financial statements. First, the PCAOB did not provide an all-inclusive list of what might constitute a CAM. Rather, it is the auditor’s responsibility to make this determination.

“The new framework is broad enough that on one level you might think that ‘goodwill impairment’ is a difficult judgment that would always be a CAM, yet this is not the case,” Sullivan said. “A company could be so profitable that this is not a difficult, complex, or subjective judgment. But if the company the next year has a truly bad year, then goodwill impairment could be a CAM.”

Other possible CAMs include a company’s valuations of hard-to-value securities and investments in nonliquid assets, assuming in both cases that they are material to the balance sheet, Sullivan said. “While the firm anticipates some effort in reporting the CAMs the first year of compliance, we’re very supportive of the new audit model and the goal of giving investors additional information to assist their valuations,” he added. “By separating out such issues for specific attention by investors, they’re better aware that this was a significant estimate by management and one of the most challenging areas in the audit for the auditor.”

A second challenge is how many CAMs an auditor must detail in the report. “Auditors will first look to the definition of a CAM in the auditing standard,” said Cindy Fornelli, executive director of the Center for Audit Quality (CAQ), which is affiliated with the AICPA. “A CAM is any matter arising from the audit of the financial statements that is communicated or required to be communicated to the audit committee, that relates to accounts or disclosures material to the financial statements, and that involved especially challenging, subjective, or complex auditor judgment. There is no set number for CAMs for the auditor to communicate.”

Boilerplate language is another area that will represent a challenge for auditors related to this standard. SEC Chairman Jay Clayton issued a warning of sorts when the new standard was issued. He said he would be disappointed if CAMs result in boilerplate communications that snuff out the potential for the new standard to deliver meaningful information toinvestors.

Fornelli shared that auditors may identify the same CAM from one year to the next. “Investors are looking for comparability. So as long as a CAM provides meaningful and accurate information about the audit, it may be OK to use similar language year after year,” she said.

Fornelli also said that investors must appreciate that the new PCAOB standard does not provide the same heightened degree of transparency called for in the United Kingdom’s auditor reporting standard issued in 2013 by the Financial Reporting Council (FRC). The FRC standard requires auditors to describe the most significant risks of material misstatement, disclose the levels of overall and performance materiality, and explain the scope of the audit.

“They’re different standards with different levels of transparency,” Fornelli said. “The other caveat I have for investors is that they should not expect the CAMs to be a proxy for the conversations they must still have with management, the audit committee, and the auditors. This is not the purpose of the standard. Nevertheless, investors will get insights into what the auditor has found to be challenging or complex, which is a big step forward.”

GETTING READY

Given these various challenges, the good news is that the phased effective dates give auditors, audit committees, and preparers time to get ready. While other mandatory features of the new auditing standard, such as disclosure of an auditor’s tenure, were phased in on Dec. 15, 2017, the communication of critical audit matters for large accelerated filers is not required until audits of fiscal years ending on or after June 30, 2019, and for all other companies for audits of fiscal years ending on or after Dec. 15, 2020. “That’s a pretty good lead time,” Sullivan said.

In the meantime, Sullivan said engagement teams are endeavoring to consider all the matters that may be CAMs, to determine which ones will be disclosed as such in the auditor’s report. The firm’s internal implementation guidance and model workpapers are guiding engagement teams through the process of considering relevant items and documenting their conclusions as to whether or not each matter is, in fact, a CAM. “We’ll monitor the application of this guidance and tools as we prepare to implement this portion of the new standard,” he added.

The firm also expects to engage in frequent dialogues with the audit committee about what might constitute a CAM disclosure. “We will then take a dry run, going through the process of identifying the matters that could be CAMs and how they might look in a report,” Sullivan said. “Once that is done, we would bring everyone together to look at the draft and react to the disclosures.”

Sullivan recommended launching this audit planning process early in the fiscal year to discern the challenging, complex, and subjective areas of the audit and discuss them with the relevant parties. “As the year progresses, if circumstances change or something big happens like an acquisition, certain CAMs may drop off the list, but others will remain so there are no surprises two days before the filing,” he said.

Lastly, Sullivan advised that auditors exercise restraint in not trying to do too much, too soon. “You need to present important information, not duplicative information,” he said. “If there is a very good description of the [entity’s] critical estimates in the footnotes, in which the matter’s complexities and subjective judgment is detailed, I don’t think auditors need to repeat the same words [that are] in the body of the 10-K. They’re already voluminous and can be repetitive.”


About the author

Russ Banham is a Pulitzer-nominated business journalist and author who writes frequently about finance and accounting issues.

Prejudice and Pride on the Road to the C-Suite: The Story of XL Catlin’s CDO

By Russ Banham

Carrier Management

Math has been the one constant in Henna Karna’s life.

The chief data officer of XL Catlin today heads up the data and digital transformation team at the global property/casualty insurer and reinsurer. She is widely considered to be one of the foremost data scientists in the insurance industry, beginning her career initially as an actuary and then becoming a predictive modeler and cryptographer for several government agencies.

Karna subsequently worked in both the business and technology sides of high technology and financial services companies, and spent a brief period in academia. She returned to the public sector to lead disruptive digital innovations at Verisk Analytics and AIG, serving the latter as global head of data and technology for the actuarial organization. She’s taking her work to the next level at XL Catlin, which has embarked on a robust initiative to make data a competitive differentiator and the nucleus of all business decisions.

“Our vision is to create an embedded digital ecosystem that intelligently converts data into business insights on a platform that can be used democratically by the company, our customers and our partners,” said Karna, who has a master’s in business administration from MIT and both a master’s and a Ph.D. in applied mathematics from the University of Massachusetts. “In this journey, I am fortunate to have such a great team and the buy-in from across the technology and business sides of the organization. It is not our vision, our approach or our technology that will make this successful but rather our teamwork and partnership.”

The sheer volume of data today in digital format is a goldmine for all industries, assuming there are ways to rapidly unearth this intelligence. “The challenge is the time and effort required to access and analyze data,” said Karna. “Finding what you need at a point in time is elusive. Our mission is to transform the company to create this value in real time.”

Micro-Databases

XL Catlin is well on its way toward achieving this vision. (Disclaimer: The reporter for this article has also written content for XL Catlin.)

Different datasets now reside in an array of searchable micro-databases with transparent indicators, effectively transforming data into “reusable assets,” said Karna. “We are becoming hyper-flexible in how we leverage data, convert it into information, and then transform it into insights and intelligence.”

In these regards, XL Catlin is at the vanguard of the P/C insurance industry, which some see as being in the midst of an existential crisis. Under attack by InsurTech startups predicated on more efficient ways to underwrite, process and distribute insurance, carriers can no longer abide legacy operations and technology. It’s either transform or die; otherwise, customers will turn to competitors that sell innovative insurance coverages tailored specifically to their needs at lower premiums.

Karna is well positioned to lead such a transformative event. “Henna stretches the thinking of every team she is in,” said her former boss at AIG, William Kolbert, the insurer’s chief information officer/global consumer. “She knows what it takes to go from good to great.”

Prejudice and Pride

Karna is no stranger to difficult challenges. She came to the United States as a child from Purnia, India, the fifth largest of 38 cities within Bihar state, a rural area in the country’s eastern region. Purnia’s small farms produce multiple crops like rice, potatoes and wheat. It is one of India’s least literate cities, yet Karna’s father, Arun, persevered to become the first in his family to graduate college. He later received a master’s in mechanical engineering.

“My dad is the oldest of seven siblings from a village that struggled with water and electricity,” said Karna. “Everything he earned went to our village—the classic ‘oldest son’ responsibility.”

Her mother, Pushpa, a homeopathic doctor, came from a family that had been part of Ghandi’s movement in the second Indian Revolution. Post-independence, the family achieved a more comfortable existence. Pushpa’s father received his master’s in mechanical engineering from Oxford University in England and a Ph.D. in India. Arun sought to do the same and moved the family to Narragansett, R.I., to attend the University of Rhode Island.

Karna was five years old, the second oldest of four siblings. Her life was turned upside-down. “Money was very tight,” she recalled. “My father was given a very nominal stipend from the university to support the six of us. Kitchari rice and lentils became our most consistent meal at home. My mother walked four miles to buy groceries and back. She sewed all our clothes from scratch fabrics. My siblings and I had to walk or bike several miles each day to and from school, where we relied on meal tickets for lunch. It took several decades before my family could afford to buy a home.”

Tough as these conditions were, they were nothing compared to the virulent racism her family experienced. Narragansett then and today is almost completely white, with the most recent U.S. Census tallying a 95.8 percent population of Caucasians.

“We were the only Indian family anywhere,” said Karna. “I was the subject of intense bullying at school. Girls used to lock me in closets and purposefully trip me in the cafeteria carrying the tiny bit of food I had. One time, some kids stole my gym clothes and burned them in the trash while I was showering. Name-calling and emotional abuse were part of every day. I remember teachers telling the class generalized statements of how people were so poor and illiterate in India that they lived in trees and ate snakes, which is a complete fabrication. The ignorance was profound.”

Life was even worse at home. Karna’s family was involved in a near-fatal car accident. Her parents were hospitalized, and her brother, who suffered a skull fracture, was in and out of the hospital for months. “We went pretty quickly from barely surviving to an even more devastating situation,” she confided. “Survival became the only goal.”

There were some rare instances of goodness. Neighbors and other people pitched in to help until Arun was back at work. “My favorite memory is of the woman in school who served us lunch,” Karna said. “She spoke no English but could tell from my face that life was not easy. Because we did not eat beef, she purposefully saved sauce for me before adding the meat. It was a small gesture but meant so much to me at the time. I still remember her face.”

Saving Graces

Through their ordeals, the family found refuge in academics. Today, Karna’s sister is a physician and her two brothers work at Goldman Sachs and as a serial entrepreneur, respectively.

“I was slightly different than my siblings—more on the creative side,” she said. “I liked the arts, which is why I liked mathematics. Most people don’t see math as creative, but I do. I found writing mathematical proofs and arguing hypotheses to be a form of creativity. In a real world that had become insensible, math became my sanctuary.”

In middle school, Karna read epic fantasy books involving different worlds than the one in which she lived (David Eddings was her favorite author). She started reading Marvel comic books and was particularly attracted to The X-Men, relating to their singularities—the mutations that had made them superheroes. She nurtured her first real friendships with a girl named Maya and a boy named Benjamin, whose families were of European descent and welcoming.

“I think I would have quit school and forgotten how to appreciate people had Maya and Benjamin not been there,” she said, laughing. “Maya and I were both nonconformists. And Benjamin was the class valedictorian, a jock, and yet didn’t wear it with arrogance. Till this day, we stay in touch.”

Karna also found inspiration in the lives led by two historical figures—Abraham Lincoln and Rani Lakshmibai, a young woman who led the first revolt against British rule in India in 1857. Lakshmibai was 29 years old and queen of the princely state of Jhansiin in Northern India, having married the local Maharaja.

“The British compared her to Joan of Arc,” Karna noted. “She refused to accept the constraints put upon her and other women at the time. She was fearless in wanting to stop the practice of slavery and the ingrained racism against certain groups of Indian people that the British had encouraged. She inspired me to find the good in all things and to never accept the status quo, always looking at everything with a fresh perspective—something I try to bring to work every day.”

Karna was similarly impressed by Lincoln’s courage in speaking up for what he knew in his heart was right for America, despite the political consequences. “As a victim of racism, it was an awakening to realize that there were people who had the strength to stand up for what they knew was right,” she said. “Every era needs such people.”

Stepping Out

Karna gradually came out of her shell in high school. She became more vocal in class and no longer tried to conform to others’ expectation of what it meant to be American. As she developed confidence in her abilities, she discovered a newfound love for being Indian.

“We were advised to blend in to not get harassed,” she recalled. “The reality was that was going to happen anyway, so I decided to embrace my difference, braiding my hair and wearing Indian clothes to school. But I was still a classic teenage girl. I wore my salwar (a pair of light, loose, pleated trousers tapering to a tight fit around the ankles) with sneakers, which was pretty cool, I thought. Not that anyone else agreed!”

Mathematics remained her passion. Unlike English literature or history classes that focused on the western world, math was not subjective. “Because I didn’t really understand ‘American culture’ or get the jokes, my grades outside of math were not the best,” she acknowledged. “With math, there was always a right answer and I could find my way to it.”

She excelled in the subject. While in high school, she also indulged her creative interests, applying them to woodworking. She eventually got an after-school job carving walking canes. “I worked for this woman who gave me $30 for every cane I carved and then sold them for $450 each,” she said, laughing at the sheer capitalism.

The elaborate canes included a handle with a rope-like design with knots that Karna carved. She was interested in knot theory—the mathematical study of closed curves in three dimensions and their possible deformations without one part cutting through another. “I’d carve each rope handle based on a mathematical proof,” she said, referring to an argument for a mathematical theorem drawn from previously established theorems. “Then, I put together this little booklet that explained the theorem in terms of nature. Ultimately, I carved 30 different cane handles.”

Taking Charge

Karna brings the same diligence and precision to her role leading XL Catlin’s data and digital transformation. The company’s CEO Mike McGavick said the strategic imperative is crucial to the insurer’s differentiation in the evolving insurance industry. “Everything we do is focused on the customer—providing better insurance solutions and giving them even greater peace of mind—and to do that we need to be more efficient in how we underwrite, distribute our products and innovate. Data transformation is the gateway.”

Karna, who is tasked with building this gateway, explained its value: “By being able to access intelligent data instantly across the enterprise, our people, customers and partners like brokers will have the information they need to improve every link in the insurance value chain,” she said.

She provided an apt analogy of why this transformation is needed in the insurance sector. “Back when people took photographs and sent out the roll of film to be printed, they received back a dozen images,” she said. “It wasn’t difficult to find that photo of grandpa doing something silly. Today, you laboriously scroll through hundreds and hundreds of digital images to find the picture you’re looking for. It takes so long you get frustrated and move onto something else. Well, looking for data is like looking for that one photo.”

XL Catlin is making the hunt vastly simpler and easier. “We started by analyzing our ‘current state’ business capabilities—underwriting, actuarial work, how we go to market, product distribution, claims and so on—measuring dozens of metrics like the length of time it took in each case to extract information,” said Karna.

Her team then brainstormed how to speed up these processes while increasing the rigor and quality of data at the same time. Recently, the architecture needed to move different datasets in real time to the containerized micro-databases that have been built. Insurance processes like underwriting and claims can now draw from the containers.

Asked for an example, she pointed to the data amassed in a micro-database on different policy endorsements. Previously, there was no way to analyze each endorsement type, as there was no central repository. Karna calls this a “classic data problem.”

“It used to be that if someone wanted to understand the trends around a particular policy endorsement to measure them against other endorsements, they would have to manually ferret out the answers in a ‘business as usual’ way,” she explained. “Now, the insights are there for the taking. Time instead is directed toward information analysis that shapes an insightful story.”

Is it hard work?

“It’s an effort,” Karna conceded. “But we see it more as a mission with a journey, one that we’ve been on for the past year-and-one-half. We’ve taken the time to do this right—up-skilling colleagues’ capabilities, changing the entire technical stack [the software that provides the infrastructure for a computer] and modifying our KPIs [key performance indicators]. I can say that we have officially created assets out of our data. We now have measurable value across four pillars: operational, foundational, strategic and disruptive.”

Finding Her Way

As the transformation initiative moves forward, Karna’s embrace of mathematics as a form of creativity differentiates XL Catlin’s approach. The company’s digital innovation is one of the key factors in the decision by French insurer AXA to acquire the company. “My career has been varied, broad and fairly nonlinear, but the reality is that math has always been my forte,” she said. “Mathematics is analytical, and the heart of analytics is data. Most companies now realize that data is how they must drive their businesses forward in future.”

Karna has her hands on the wheel at XL Catlin. “Henna is superbly positioned from her career experiences and interests to lead our company forward in becoming the industry’s premier data-driven commercial insurer,” said CEO McGavick. “She brings a business lens to solving problems yet also has tremendous analytical experience.”

McGavick shared something he had written to Karna following her interview for the chief data officer position in 2016. “Happily, in most cases, I meet some really impressive people in senior interviews…Even against such high expectations, I did not expect to be as impressed as I was by our session and your clear passion for your work and the people you seek to lead.”

XL Catlin’s Chief Information Officer/Reinsurance Dave Walker is confident that the company’s data and digital transformation initiative is on the right track. “This is the first time in decades that I really see a very high possibility of us succeeding in a data strategy,” said Walker. “We’ve made attempts before and thought we were on the right path, but it didn’t have this level of thoroughness in the vision and didn’t create this level of energy in the company. With Henna at the helm, I’m confident we’re going to get there.”

Karna is a happy person today, a wife and mother balancing work-life demands like other women with demanding but meaningful jobs. She no longer feels the need to wear a salwar to boldly state her uniqueness. In today’s multicultural workforce, she blends easily into the quilt, just one “American” among many with a unique background story. “On occasion, I’ll wear a nose ring or a saree to remind me of my cultural heritage,” she confessed. “But the truth is, I just really like the style.”

Russ Banham is a Pulitzer-nominated financial journalist and author.

Technologies for Aging Baby Boomers

By Russ Banham

Despite the popular misconception that everyone ends up in a nursing home, more than half of 95 year-olds still live at home. Among them is my 93 year-old dad.

Jack served in World War II and the Korean War and came home with a Bronze Star and a Purple Heart. When you experience combat as a teenager and survive, it makes the rest of life’s challenges a bump in the road. He’s battled colon cancer and melanoma and won, and came out of a quadruple bypass smiling. A former marathoner who ran the NYC Marathon in four hours at 60, he goes for a two-mile walk each day, jogging in the last couple blocks. He fills his morning making art collages and then cuts vegetables to get dinner ready for my working sister and her husband, whose home he shares. He fully expects to become a centenarian.

There are likely to be more Jacks as my generation of Baby Boomers enter our golden years. With longevity rates pointing upwards—more than one in three women and one in five men who are 65 will reach age 90, according to the Brooking Institution—the volume of older Boomers likely to be taking care of themselves at home is substantial. This social phenomenon, called “aging in place,” will likely lead the Baby Boomer generation to depend on technologies that ease the daily challenges of living long and well in their own homes.

Virtual Caregivers

One can thank modern healthcare advancements for our longer expected lifespans. “We are all benefiting from new medicines, bio-technology, gene therapies, and 3D bio-printing of body parts,” said Nancy Shenker, who writes the popular Bots & Bodies column in Inc. magazine and is the founder and publisher of Embrace The Machine, an AI marketing agency. “There’s a lot of work being done to keep us Boomers alive and thriving longer than previous generations.”

Yet despite scientific advancements, no one is predicting peak health and fitness for those in their last decades. Even the fittest Boomers today are likely to experience fading hearing, eyesight, and mobility—which is where technology comes into play.

A variety of solutions using sensors, smartphone apps, GPS systems, and voice activation have been developed to help older people age in place—enjoying independent lives in their homes. Lively, for instance, is a smartwatch that can remind older people when it is time to take a particular medication. ElliQ is a social robot that uses AI technology to encourage a more active and engaged lifestyle; marketed by Intuition Robots, the robot may suggest that the user go for a walk, knowing that the weather outside is perfect that very minute for a promenade.

Voice technologies allow people to communicate with their smart speakers, like Amazon Echo, and connect to smart devices to help perform household tasks.

“There is great value for someone whose motor skills are compromised to say `open the trashcan’ when they need to dump a large bag of refuse into it,” said Shenker. “They can ask the smart coffee machine to make coffee or the smart refrigerator which foods are in short supply, and then request that those items be ordered over the internet for delivery.”

Saving Lives, Maintaining Dignity

Technology can be a literal lifesaver, yet even with new innovations come complications. While personal emergency response systems—worn on the wrist or around the neck—allow seniors to press a button in the event of an emergency, only 14 percent of older people continuously wear the devices continuously. What’s more, approximately 83 percent of seniors fail to activate the alert button after being on the floor for more than five minutes.

Newer technologies are setting out to address these shortcomings. TruSense, for example, is a smart health monitoring and tracking device that combines GPS with a range of monitoring sensors in the home. The technology detects periods of human inactivity that may indicate a possible health crisis.

“If someone gets up at a certain time of the day and then moves through a series of rooms over a period of time—and does not do this one morning— a designated family member is contacted immediately,” said Rob Deubell, senior vice president of TruSense.

The internet-enabled sensors measure motion, temperature, water leaks, the presence of visitors, and voice sounds. This data flows to a computer that uses algorithms to discern when normal human behaviors, habits, and patterns are out of alignment.

The algorithm is developed to trigger an alarm when two or more events occur simultaneously, limiting the possibility of false alerts. If Grandma, for example, is sleeping at her grandchild’s place, there will be no movement. But if there is no movement and some other anomaly is detected, such as a much higher or lower room temperature, then this may be clearer evidence of a potential fall or other life threatening issue.

The tool also provides a way for a Boomer-designated family member to receive information about their loved one without monitoring behavior 24/7. “We’ve integrated the solution with digital assistants like Alexa on the Echo smart speaker,” said Deubell. “You can ask, `How is Mom doing today?’ and get an updated response drawn from our app.”

While surveillance cameras can achieve similar aims, Deubell said that nobody likes the Big Brother-ish feeling they’re being watched in their own home. “We wanted a solution that was non-invasive to maintain the dignity of seniors,” he explained.

Fully In Charge

With new technologies on the rise, aging in place might just relieve some of the financial and emotional constraints placed on families, society, and healthcare institutions to care for aging Boomers.

It might also improve the lives of those that make their way to triple digits. “I fully plan to live past 100,” said Shenker, who is today a spry 60. “And I also plan to be fully in charge of how I live my life.”

Russ Banham is a Pulitzer-nominated financial journalist and author.

How a melanoma scare – and a great dermatologist – made me more serious about skincare

By Russ Banham

At my annual checkup, the doctor noticed an oddly shaped mole of a worrisome size on my back. “Have your wife take a peek at it now and then to make sure it doesn’t change,” he instructed me. He was pretty certain that it was just, well, a mole.

By “change,” he meant grow in size or height, develop asymmetrical borders, alter color, or otherwise evolve into something that it currently was not. I’d have monitored it myself were it not smack dab in the middle of my back. My life was in my wife’s hands, or so I told her. Was I worried? A little. My father and aunt had skin cancer.

I also hail from the Baby Boom generation of kids whose moms implored us to “Go outside and get some color on your face.” Being too pale was considered the sign of a recluse, someone with poor athletic skills who read Archie comics indoors all the time. As teenagers growing up in Queens, New York, summers with my pals were enjoyed at Jones Beach, ogling the waves (yeah, right) for hours at a time. In the dog days of August, my attire was a pair of cutoff jeans and sunglasses, no shirt or shoes. The sun had most of my body to burn to a crisp. I was a sitting duck for solar radiation, tallying up more sunburns than I can count.

After one month of watching the peculiar mole, my wife gave up. “I can’t tell if it’s changing,” Jenny sighed. “This is too much to ask.”

Who could blame her? She wasn’t a doctor. So I contacted the real thing, a dermatologist a friend recommended.

Will Kirby, DO, is a local celebrity in Los Angeles, where I live. Will won the Big Brother competition in 2001, taking home enough money to finish his medical training. In his younger years, he had a basal cell carcinoma (a type of skin cancer) removed from his leg, which set his life’s course. Will took one look at the mole on my back and said “Not good.” He snipped it off and had a biopsy performed of the tissue. The diagnosis: A dysplastic nevus, a precursor to melanoma, a skin cancer. A nevus is a mole; dysplastic is atypical.

Within days I was on my stomach as Dr. Kirby removed more tissue from the site of the mole, then sutured a two-inch long line. Three months later, he took a peek and liked what he saw. “Not to worry,” he said.

Since then, Dr. Kirby and I have become friends. This is often the case with a skin cancer patient and his dermatologist. Every three months for the next two years, I was in his office. Dr. Kirby surveyed the landscape of my body, circling suspicious moles with a pen. In the eight years of my visits to date, I’ve had three more dysplastic nevi (plural of nevus) removed and multiple other moles snipped away before they could get worse. “That’s what we do here — snip, snip, snip away cancer,” Dr. Kirby said when I called for an interview. “The key is to be vigilant. The sooner we snip, the better the outcome.”

So far, so good: None of the three types of skin cancer I’ve attracted have entered the thornier territory of Stage 2. I even had a topical procedure done on my face, the site of several snips to reduce the risk of future cancers. The medication contained a substance called ingenol that kills abnormal cells that lead to skin cancer. My face looked like a deflated football for a week, until the dead skin sloughed off. I’m promised at least five years of a cancer-free face, at which point I will undergo the same procedure.

This is now my future. Certainly, I’m to blame for the sun exposure of my youth. While I apply sunscreen with SPF 50 every morning, and wear a hat on hikes and the rare weekend at a Malibu beach, the blistering sunburns of my youth will forever take their toll. I will always develop odd-looking moles. Dr. Kirby will give them the once-over and snip when he must. He’s my younger big brother now, looking out for me for life.

When found and treated early, the estimated 5-year survival rate for melanoma is 99%. But new therapies offer hope for even advanced cases. In 2015, former President Jimmy Carter, then 91, beat metastatic melanoma that had spread to his liver and brain. Ask your primary care physician for a skin cancer screening at your next physical. 

The Future of Initial Coin Offerings

By Russ Banham

Perspectives

Until recently, Initial Coin Offerings, or ICOs, were perceived as a great way for startups to raise capital, in large part because of the unregulated nature. Experts pegged the amount of capital raised through ICOs from $4 billion to $6 billion in 2017, and nearly $3 billion to date this year.

Now this spigot is slowing due to growing legal and regulatory scrutiny around ICOs. The U.S. Securities and Exchange Commission (SEC) maintains that the sale of tokens that gives investors ownership in startups falls within its jurisdiction. But several other regulators, including the Federal Trade Commission (FTC), the Commodities Futures Trading Commission (CFTC), and the Comptroller of the Currency (OCC), have weighed in that they, too, should regulate ICOs and the sale of tokens.

This alphabet soup of oversight is making investors pause before plunking down on cryptocurrency. The caution is to be expected, said Joel Telpner, a partner at New York-based law firm Sullivan & Worcester, where he heads up its blockchain practice.

“ICOs, cryptocurrencies, and the blockchain technology that underpins them are such radically different concepts that they’re completely beyond current regulatory regimes,” Telpner explained. “Regulators are struggling to understand what these are, whether they should be regulated, and how that might happen.”

When a Rose is Not a Rose

As investors hesitate, ICOs are taking a breather. Funds raised in May are nearly one-third the amount raised this past December, according to ICO research firm Autonomous Next, which blamed the sluggish conditions in large part on “continued regulatory uncertainty.”

At its simplest, and ICO entails investors seeking a share in the startup venture to purchase virtual tokens, assuming enough capital is raised to launch the company. While the primary use case for ICOs is nothing new—“just another capital raising concept,” Telpner called it—the atypical nature of ICOs has caught the attention of myriad regulators, baffled if the tokens are a form of currency, a security, a utility or something else.

If deemed a security, then the SEC wants to regulate ICOs. “Some players have marketed the tokens at a discount to investors that get in early, giving them the opportunity to sell the tokens at the time of the ICO to make a quick return,” said Telpner. “To the SEC, that sounds a lot like a security.”

However, the blockchain platform that serves as the foundation of the ICO has the appearance of a utility, since the tokens also provide a way to access the blockchain’s products and services. Complicating the picture is that tokens also can be used to verify the data on a blockchain platform. Businesses or consumers wanting to access this data pay for that opportunity with tokens.

“In these situations, tokens are used as commodities or to buy or sell goods, making them different than a security,” Telpner said. “You’re now dealing with a form of commerce in which the tokens are equivalent to a real currency. You don’t take a share of Starbucks’ stock and buy a cup of coffee.”

These various scenarios emphasize why various regulators are giving closer scrutiny to ICOs, blockchain platforms, and cryptocurrencies. In May, for example, the FTC issued a temporary restraining order against four cryptocurrency investment ventures.

Under the Microscope

Although it may be too soon to predict the future regulatory landscape, companies dealing in blockchain and AI solutions are nonetheless optimistic that the current pause in ICOs is temporary. Still, Telpner said he would not be surprised if ICOs are regulated by several government entities at different stages.

“There is some talk now that a token would be regulated as a security the first year after the ICO, and then morph into a utility token afterwards,” he said. “Another idea floating around is to create different types of token categories—some securities, some commodities, and some utilities. Depending on the circumstances, different regulators would be involved.”

As the ICO market matures, at least some regulation is likely. “These are such radical technologies in their earliest stages of development; regulators are just trying to get a bead on what this all is and how it may change going forward,” said Telpner. “That’s a good thing, as it allows for more thoughtful treatment.”

The ongoing work of the Congressional Blockchain Caucus is to study blockchain technology for use by the government and industry, and to examine the actions of states like Arizona, that is writing its own legal definitions. “In Arizona, the legislation would allow an ICO to raise a certain amount of funds without risking violation of securities laws,” Ron Wince, founder and CEO of Myndshft, a healthcare AI and blockchain solution, said.

This regulatory action, most believe, is a good start. “The more clarity, the better for all concerned,” Wince stressed. “If regulators try to regulate this new animal using old regulations, we’ll just end up with a patchwork quilt. We need regulations, but we also need them to be as innovative as the technologies they regulate. Shortcuts are not to anyone’s advantage.”

Russ Banham is a Pulitzer-nominated business journalist and author who writes frequently about the intersection of technology and business.

Extraordinary Re’s Extraordinary Idea

By Russ Banham

Carrier Management

Imagine there’s a way for institutional investors to trade insurance risks much like they trade stocks. Well, imagine no more. A new and unique reinsurer, Extraordinary Re, has hit upon the novel idea of creating a trading platform run by Nasdaq for investors to trade assets tied to insurance liabilities.

The Extraordinary Re platform, which will be launched this year, offers the opportunity for investors to diversify their portfolios outside traditional stocks and fixed-income assets with a new investment class that does not correlate with the risks of other investments. For insurers and reinsurers, the platform presents an innovative way to access the capital markets to buy reinsurance capacity to absorb a wide range of risks.

If this sounds like insurance-linked securities (ILS) or catastrophe bonds, it should. But there’s a difference between such financial instruments that are bought by insurers and reinsurers on a one-off basis and what Extraordinary Re has in mind. First of all, the company’s trading platform would comprise property and casualty risks beyond property catastrophe, such as terrorism, aviation, marine, workers compensation and product liability exposures. Even life and health insurance risks are on the menu.

That alone is disruptive. But where Extraordinary Re shatters paradigms is the idea of creating a trading platform composed of these diverse perils, in which an investor can sell an interest in a Florida hurricane risk to invest in a business interruption exposure or the mortality risks of people in their 60s.

“We’re building the world’s first liquid marketplace for a wide range of insurance and reinsurance risks,” said Will Dove, Bermuda-based Extraordinary Re’s chairman and CEO. “Hedge funds, pension funds, sovereign funds and other large investors interested in balancing or readjusting their investment portfolios with short-tail, long-tail and even life insurance risks will soon be able to do that.”

Dove, an insurance industry and capital markets’ veteran, projects that the platform will unlock more than $20 trillion of existing liabilities held on insurance company

balance sheets while enabling institutional investors to access an attractive return from an uncorrelated asset class. “We see it as a 21st century version of Lloyd’s of London,” he said.

The comparison is apt. Like Lloyd’s, Extraordinary Re offers a marketplace in which people can examine different risks to determine their interest in absorbing some or all of the exposure. At Lloyd’s, these people work for insurers and reinsurers, while at Extraordinary Re, they’re investors. In both cases, if there is a loss, the insurers/reinsurers or investors pay up. If there’s no loss, they come out ahead.

This is a simplification of very complex transactions, of course. But it points to the innovations under way today that could disrupt the historic functions of the insurance industry.

“We’re rethinking how risks are transferred,” said Dove. “There is no particular reason why a single [insurance or reinsurance] company must be responsible for underwriting, marketing, distribution and service to provide all the capital for a risk. A distributed value chain, on the other hand, will result in more flexible availability of capital, reducing overall expenses that lower the cost of products for consumers.”

This value chain is Extraordinary Re’s digital underwriting platform, which offers new ways to connect risks with capital. When the company is up and running—by the end of the year, if not earlier, Dove said—an insurer, reinsurer or broker would present a typical submission for risk capacity, much like the current process. Once received, Extraordinary Re’s underwriters will prequalify the submission to ensure it is a class of risk its platform can support. Assuming this is the case, the submissions are posted electronically.

Investors now come into the picture, reviewing the submission to determine if it fits their portfolio diversification objectives. This is somewhat similar to how the Lloyd’s market operates—brokers calling on insurance syndicates to determine their interest in a submission. “The difference with our platform is that it happens electronically and much more quickly,” said Dove.

Of course, that’s not the only difference, but it is helpful to understand the platform in the context of current practices. For instance, multiple investors would participate in different tranches of a specific risk, much like reinsurers do today. This limits the investors’ loss exposure and gives them room to assume portions of other risks in additional tranches, increasing their portfolio diversification.

In essence, investors would create portfolios of different insurance liabilities, trading in and out of them as they see fit. Hence the “liquid” nature of Extraordinary Re’s trading platform. (See related article: Liquid Gold.)

With regard to the platform, the company worked with Nasdaq to adapt the firm’s proprietary matching-engine technology to suit its needs. While Nasdaq will host the platform, Extraordinary Re will manage the underlying transactions. “Will and his team came to us and expressed an interest in deploying our current technology platform to trade insurance-linked securities,” said Paul McKeown, senior vice president of market technology at Nasdaq Inc., a provider of trading, clearing, depository and surveillance solutions in addition to its well-known public company listing services.

Following Extraordinary Re’s launch later this year, the company plans to work with Nasdaq to deploy a blockchain-based ledger system to enable its investors to subscribe to real-time data feeds of transactions in the investors’ accounts at Extraordinary Re.

The blockchain technology will capture and transmit insurance underwriting and exposure data to the investors. “We’re giving investors access to more detailed and timely data than many traditional reinsurance companies ever see,” Dove said, adding that a possible future application of blockchain technology is the ability to create smart contracts between Extraordinary Re and insurer clients.

Pouncing on Cat Bonds

Aside from its strategy to create an insurance liability trading platform, Extraordinary Re is disrupting the catastrophe bond market by reimagining how investors and insurers/reinsurers come together to execute deals.

Three main parties currently are involved in the issuance of a catastrophe bond—a sponsor, the investors and a special purpose vehicle (SPV). Sponsors include insurance companies, reinsurance companies, large multinational corporations and governments—all looking to spread the risk of loss from hurricanes, earthquakes and other natural disasters. Investors generally are pension funds and hedge funds looking to diversify their investment portfolios with a new asset class. An SPV is typically a tax-exempt company that issues the catastrophe bond in a tax-friendly domicile like Bermuda, Ireland or the Cayman Islands.

Liquid Insurance Contracts

By creating a new nexus between the sponsors and investors, Extraordinary Re does away with the need for an SVP, offering liquid insurance contracts as opposed to a multiyear bond. For many investors, the ability to trade in and out of an investment position in an insurance liability will be more attractive than investing in a bond that doesn’t pay out for a certain number of years.

“One of the valid criticisms of catastrophe bonds is that there isn’t a lot of liquidity,” said Robert Hartwig, associate professor and co-director of the Risk and Uncertainty Management Center at the University of South Carolina’s Darla Moore School of Business. “While the yields might be relatively high and the risks are generally uncorrelated with traditional economic and financial risks, liquidity has been a weak spot.”

The lack of liquidity—the ability for investors to trade in and out of catastrophe bonds—made some institutional investors leery of catastrophe bonds as an asset class, he said. “What Extraordinary Re is doing is bringing together as many different market participants as possible to participate on its platform in a wide variety of insurance-linked securities that provide the same traditional benefits as high-yield and uncorrelated returns as cat bonds but with real liquidity,” said Hartwig, who teaches insurance and finance at the university. “The benefits of liquidity will expand the pool of investors and traders willing to participate.”

He added, “The fact that this is more than just catastrophic property damage risks also will be of interest, as it eases the way for institutional investors to create a portfolio of uncorrelated insurance risks.”

Not only can investors diversify their portfolios to include uncorrelated catastrophic property risks—the case for the past 20 years with catastrophe bonds—they now can further diversify their portfolios with a growing variety of other uncorrelated insurance liabilities like cyber exposures and mortality risks.

“There’s a lot of innovation going on here—not just the platform but also the company’s use of blockchain technology,” said Hartwig. “Most InsurTech startups tend to be involved in building a better mousetrap for distributing insurance. Extraordinary Re is bringing together new ideas in a completely novel platform that relies on several disruptive technologies.”

At the Helm

The company’s chairman and CEO is no newcomer to insurance. Across Dove’s nearly 30-year career in the property/casualty insurance and reinsurance industry, he’s been an actuary, underwriter and senior executive with such leading companies as Centre Re, ACE Ltd., Cigna, Continental Insurance and Tower Group International. At ACE, he was a member of the team that put together the company’s first ILS issue in 2007, giving him entrée to the capital markets.

Dove’s expertise is a key factor in Extraordinary Re’s appeal to deep-pocketed backers, among them Silicon Valley’s premier startup accelerator, Plug and Play Tech Center, an early investor in Google, Dropbox and PayPal. Asked what encouraged the venture capital firm to invest in Extraordinary Re, Ali Safavi, a Plug and Play principal and global head of InsurTech, said it was a combination of its leadership team’s domain knowledge of both insurance and the capital markets as well as the positive feedback the firm received from insurers and reinsurers it had contacted about the trading platform.

“We’re also aware that the model used today to spread risks is old and cumbersome,” Safavi added. “The technology is legacy, and innovation is needed. We also liked the connection to Nasdaq and especially the team’s connections with brokers, carriers, reinsurers and investors in the insurance and capital markets spaces. Ultimately, we felt they were approaching the problems from the right angle.”

The proof is in the pudding, which won’t be fully cooked until Extraordinary Re makes the leap from concept stage to actuality—possibly this summer, if all works according to plan.

Still, just the sheer invention at play evidences how new technologies will change the way insurance risks are absorbed and spread in the future.

Russ Banham is a Pulitzer-nominated business journalist and author of 27 books.

Catastrophe Bonds A to Z

By Russ Banham

Carrier Management

A reader of this publication, the president of an insurance agency, recently wrote to say he kept hearing about catastrophe bonds but had little knowledge of what they were. He was curious if these instruments would replace traditional reinsurance and was particularly concerned about a scenario that would result in the catastrophe bond market’s collapse, resulting in widespread financial problems for primary insurers and economic calamity.

His timing was excellent. Catastrophe bonds, also known as cat bonds and insurance-linked securities (ILS), passed an important threshold in 2017, successfully weathering Hurricanes Harvey, Irma and Maria, three of the five costliest hurricanes in U.S. history. Altogether the storms produced $217 billion in damage-related costs, of which $92 billion was insured, according to Swiss Re’s research publication “sigma.”

“The final loss total will only be known once all claims have been processed, but even so, 2017 is likely to go down as one of the costliest North Atlantic hurricane seasons on record,” the publication stated.

While exact figures are unavailable on the losses endured by investors in the exposed catastrophe bonds, ILS analysis organization Artemis stated in April 2018 that the market had endured its largest losses to date. But it was the market’s ability to take a hit and recover that testified to its ongoing viability.

“In the first quarter of this year, a record $4.24 billion in new catastrophe bonds was issued in 17 separate transactions,” said Robert Hartwig, associate professor and co-director of the Risk and Uncertainty Management Center at the University of South Carolina’s Darla Moore School of Business. “What this says is that cat bonds are no longer the interloper or the disrupter. They’ve become a mainstay fixture.”

Where There’s a Need

So, what are catastrophe bonds? First, a bit of history: In 1992, Hurricane Andrew caused $17 billion in insured losses in Florida—a loss figure double the modeling estimates at the time for the financial costs emanating from a severe hurricane. Several insurers were forced into bankruptcy, and reinsurance capacity dried up for the remainder. A new source of capacity outside traditional reinsurance was needed to fill the void. In 1996, according to Aon Securities, the first catastrophe bond drawing risk-bearing capital from the capital markets to satisfy this need was developed by St. Paul Re UK.

Two main parties are involved in the issuance of a catastrophe bond—a sponsor and investors. Sponsors include insurance companies, reinsurance companies, large multinational corporations and even governments, all looking to spread the risk of loss from hurricanes, earthquakes and other natural disasters. Investors generally are pension funds and hedge funds looking to diversify their investment portfolios with a new asset class.

For sponsors, catastrophe bonds are a complement to traditional reinsurance, presenting the opportunity to hedge the risk of loss from a natural disaster. The bonds function just like a reinsurance contract structured over several years or a single year. When the sponsor’s property damage losses exceed a specified indemnity trigger ($2 million, for instance), the bond kicks in to absorb the financial impact up to a stated limit (say $3 million), making it similar to traditional reinsurance, in which reinsurers assume layers of risk within a so-called tower.

Other catastrophe bond losses are pegged to parametric triggers like earthquake magnitude or wind speed. When a hurricane exceeds a 7.4 magnitude, for instance, the bond would kick in to pay losses up to the stated limit. Issuers have experimented with other payout scenarios, but most bonds involve an indemnity trigger. As a result of the development of this sector, there is now an additional option to spread catastrophic property damage losses.

“For insurers and reinsurers, cat bonds fill an ongoing need to spread catastrophic property losses,” said Hartwig. “They’ve allowed for an important extension of capacity on a global scale for a type of risk where capacity has historically been constrained.”

Catastrophe bonds also present value to investors. The yields generally are higher than traditional bonds like Treasuries, exceeding 5 percent in 2018, according to emailed comments from Daniel Ineichen, head of insurance-linked securities at Schroders Investment Management.

The bonds’ returns also trade at a slight premium to other investments like asset-backed securities and commercial mortgage-backed securities, said Paul Schultz, CEO of Aon Securities.

Catastrophe bonds generally have maturities of three to four years. The premium to acquire the bond funds are invested in high-quality securities like U.S. Treasury Money Market Funds and held in a collateral trust. These investment returns, in addition to the initial premium paid by the issuer, constitute the coupon payment to investors, assuming there are no losses.

Institutional investors are particularly interested in catastrophe bonds because of their portfolio diversification benefits, since catastrophic property damage risks do not correlate with the risks of other asset classes. “A hurricane or earthquake is not correlated with movements in interest rates or the stock market, making them a valuable hedge for investors,” Schultz said.

Added up, the bonds have legs. “With more than $100 trillion, the capital markets have the potential to be the most efficient provider of catastrophe reinsurance the world has ever seen,” said John Seo, co-founder and managing principal of Fermat Capital, an investment management company specializing in structuring catastrophe bonds.

A Long Time Coming

For investors, on the other hand, their hunt for yield played a major role in the growth of catastrophe bonds following the 2008 collapse of the subprime mortgage market, ushering in the financial crisis and Great Recession.

“When all other markets like fixed income and equities were going south fast, a huge uptick in capital suddenly flowed into cat bonds, which offered more attractive yields,” said Judy Klugman, managing director and global co-head of the ILS team at Swiss Re Capital Markets. “After that, the market really took off and hasn’t lost steam since.”

Others agree. “It took 10 years for investors to accept cat bonds as tried and true,” said Seo. “Finally, after 20 years, the ILS market is accepted and appreciated by both parties—investors and insurers/reinsurers. Their sound performance through the 2008 financial crisis was the reason.”

Record Highs

Since then, the market has been on a tear. Aon Securities’ 2017 year-end report tallied 35 catastrophe bonds issued by 31 different sponsors during the year, hitting a total capacity of $10.7 billion—a first-time achievement. If the remaining quarters of 2018 duplicate the first quarter’s record catastrophe bond figures, the year will be the best by far in the ILS market’s history.

“At present, total reinsurance capacity including cat bonds is at record highs with stable pricing, despite last year’s hurricane losses,” said Hartwig.

The exact amount that catastrophe bonds paid out last year has not yet been tallied, although Artemis posited that the losses were heavy. Why then has pricing remained stable?

“There are two ways to read this: either the ILS market is well structured and priced to pay out only in truly extraordinary circumstances, or the modeling associated with cat bond risks has dramatically improved to become quite accurate,” Hartwig replied. “In either case, investors can have some confidence in terms of understanding the risks they’re assuming.”

These risks are not for the fainthearted, given the ferocity of recent storms. Investors must proceed with caution.

“Insurance-linked investment funds span the full spectrum of risk—from ‘you could lose it all’ to a high level of protection for investment principal to everything in between,” said Seo. “Most catastrophe bonds absorb catastrophic risks modeled with a 1-in-50-year risk of loss, although there is a material part of the cat bond market that absorbs risk at the 1-in-10-year level.”

More than 600 catastrophe bonds have been issued since the first one in 1996, according to Aon Securities. Given the record issuance of catastrophe bonds in the first quarter, it is obvious that the hurricane losses of 2017 have not deterred demand from investors.

“We assumed everyone would trade forward, but the speed and quantum of dollars was much faster and bigger than what we had anticipated,” Schultz said.

Seo agreed. “Despite the financial impact of the three major hurricanes, the active returns helped offset the losses to deliver a net positive return [to investors],” he said.

For Klugman, who has been structuring catastrophe bonds since Swiss Re unveiled one of the first ones in 1997, the market’s robustness is especially sweet. “I was hired from Morgan Stanley in 1999 to find an institutional investor base for this,” she recalled. “When I sat down with investors, they had no idea what a cat bond was, much less reinsurance. I had to give them a primer. Today, the investors know what this is, how it works, understand the risks and realize there will be losses. This hasn’t diminished the value they see in the asset class.”

A similar optimism prevails among sponsors, with issuers running the gamut from insurers and reinsurers to big corporates and governments. The latter include Mexico, Colombia, Chile and Peru, among others. Some insurers have sponsored multiple bonds. USAA, for instance, has sponsored dozens of catastrophe bonds through the years to spread its risks from natural disasters in different indemnity layers. The company’s most recent $175 million bond included aggregate protection for automobile policy flood losses—an industry first.

Too Good to Be True?

All the interviewees (other than Hartwig) are engaged in the ILS market, so their optimism must be leavened with a pinch of skepticism. Yet, Hartwig, a finance and insurance professor with a Ph.D. in economics, also believes catastrophe bonds fulfill a unique need for issuers while presenting an alternate class of investments for investors.

“There’s little question that the catastrophe losses of 2017 put cat bonds to the test and they performed admirably, with record issuance in the aftermath,” he said. “This speaks volumes about their value.”

Returning to the reader’s query about the possibility of insurance-linked securities causing a global financial calamity along the likes of the 2008 financial crisis, the interviewees downplayed the risk, citing fundamental differences between catastrophe bonds and credit default swaps and subprime mortgages.

“For one thing, carriers own their policies and are forbidden to sell them onward, whereas mortgage originators are allowed to sell their mortgages into the securitization markets,” said Seo. “As a consequence, carriers use cat bonds to manage their risk, not to rid themselves of all responsibility for all time.”

Unlike mortgage-backed securities portfolios that were leveraged 30 times and more, catastrophe bonds are not generally leveraged.

“In the cat bond market, leverage financing is not widely available,” said Seo. “Even when it is, the gearing is modest—maybe no more than two times capital on a practical basis.”

Schultz noted that catastrophe bonds are collateralized entirely with high-grade collateral solutions like U.S. money market funds. The bond offerings also are “very transparent” in terms of risk assessment and documentation, and an independent assessment of risk is included in the offering materials, he said.

“With no leverage in the products, risk-free types of underlying collateral, and transparent and independently assessed risk analysis, we don’t see any way that an analogy could be made to highly leveraged derivative products with minimal to no disclosures,” he concluded.

Hartwig concurred that these fundamental differences create a sound foundation for catastrophe bond market stability. “While it’s true that a mega-catastrophe or series of mega-catastrophes could produce losses across a broad range of cat bonds, the losses would be confined to these securities for the year in which they occurred—unlike credit default swaps and mortgage-backed securities that mushroomed as the contagion spread,” he said.

Effects of Rising Interest Rates

A more likely challenge to the ILS market is rising interest rates, he said. “There’s a case to be made that the surge in interest among investors in cat bonds over the years was due to the global collapse in interest rates,” Hartwig explained. “Institutional investors in search of yield found what they were looking for in the ILS market. For several years running, they enjoyed relatively high yields with very few bonds being triggered. It seemed like a money-making machine.”

This machine may grind down as interest rates continue to turn upward, encouraging institutional investors to take a closer look at rising yields in both government bonds and corporate bonds.

“I wouldn’t call it an existential threat,” said Hartwig, “but it may result in diminishing interest in 2019.”

Russ Banham is a Pulitzer-nominated freelance business journalist and author.

Data Marketplace: Sharing Data in the Insurance Industry

By Russ Banham

Leader’s Edge

In Lloyd’s coffee house in London more than 330 years ago, the property and casualty insurance industry was formed to spread the risks of cargo-carrying ships plying the world’s seas. The industry grew and prospered, with little change in the underlying model. Now, an entirely new structure is taking shape.

The compelling reason for building this new model is the existential threat of keeping things as they are. If insurers and brokerages don’t begin to share their own and client data in novel ways to reduce acquisition costs and operating expenses, some other entity—like, say, a giant technology company—might squash them like a stack of yesteryear’s CDs.

“The cost base from which we all are working is fast becoming unsustainable,” warns Alastair Burns, chief marketing officer at London-based insurance holding group Navigators International. “A war on cost must be waged in the insurance marketplace.”

This cost base is predicated on the traditional ways of providing insurance to businesses that have not changed much since Edward Lloyd ground his first cup of coffee. Companies from the largest corporations to the smallest Main Street businesses rely on an insurance broker or agent to understand their risks and transfer them to an insurance carrier willing to absorb these exposures. The insurer then spreads these risks through global reinsurance markets.

This system has worked pretty well for centuries. Then along came data analytics—the ability to search through massive volumes of data to discover useful information for decision-making purposes. This technology and others—machine learning, robotic processing automation and artificial intelligence—have created a dangerous entry point for non-insurance entities to potentially compete against brokers and carriers, leveraging capital in some cases from institutional investors.

Other industries have collapsed from such incursions. The new insurance model under discussion would fortify the barricades. By sharing client data, brokers and carriers can reduce the cost of insurance, pave the way toward the development of innovative new types of insurance, and, most important, keep non-insurance entities at bay.

“Whoever has data is king,” says Jonathan Prinn, group head of broking at Ed Broking, a wholesale insurance and reinsurance brokerage company based in London. “If this data isn’t shared amongst us, we will fail to provide value to our clients. And if we fail, someone else will provide this value.”

Need for a New Model

One of the clear concerns facing the industry is client acquisition costs, which are much higher than the acquisition of new customers in other industries. Prinn blames high acquisition costs for Lloyd’s of London’s dismal 114% combined ratio in 2017, meaning the venerable insurance marketplace paid out more money in claims than it received in premiums.

“The cost of underwriting and broking commissions at Lloyd’s was about 42%, which is unacceptable and untenable in the world going forward,” he says. “No intermediary model I know of is anywhere close to 42%.”

In the United Kingdom, Prinn says, “real estate agents charge around 2%, credit card companies like Mastercard charge around 1.3% and moving $2 from a bank account to buy coffee using Apple Pay is free.”

The 42% figure he cites is composed of 30%-plus broker commission levels and the carriers’ administration costs, which last year ranged between 10% and 12%.

One could argue these expenses are less in the United States—according to A.M. Best, incurred broker commissions/expenses plus underwriting expenses are between 30% and 31%—but that’s beside the point. “Too much of the money that comes into the system is now consumed by acquisition and operating costs,” says Jamie Garratt, who heads the digital underwriting strategy at Talbot Underwriting, a London-based underwriting services provider.

The culprit, the interviewees contend, is the traditional linear process of transacting insurance, whereby a business goes to a broker who goes to a carrier that goes to a reinsurance broker who goes to a reinsurance carrier. The alternative is the sharing of data among brokers and carriers in a free marketplace. “If brokers share client exposure data with all and not just some insurers, everyone’s cost base reduces,” Burns says.

Garratt agrees. “If we can move data quickly and with much less friction between a client and the end risk bearers,” he says, “we can remove the replication of work up and down the value chain, reducing the high cost this produces for all of us.”

An Architecture Emerges

How might this new model look and operate? Instead of the customary linear progression, clients would share operating, financial and other data with brokers; the brokers would evaluate and package these data into discrete elements of risk; these elements would be submitted to the global insurance markets for their review; and insurers and reinsurers would decide whether to assume these risks based on their underwriting appetites and portfolio diversification objectives.

Prinn provided the example of how this might work in the commercial aviation insurance market, which is currently divided between one set of carriers that provide insurance to smaller courier-type aircraft and another set that services large commercial airlines.

“The reason for the split in the market is risk—smaller aircraft take off and land a lot to drop off freight, and the biggest risks in flying occur when landing and taking off,” he explains. “Consequently, the risks for the smaller air carriers are significantly higher.”

Assuming all aircraft owners provide their altitude, speed, turbulence and other data to a broker, cost theoretically would come down. “Airplanes produce an extraordinary amount of data coming off sensors that could be dropped into a blockchain or other type of distributed ledger technology,” Prinn says. “If the data from every airline was available in this platform, there would be many thousands of data items related to every step of the journey, fundamentally changing how insurance is structured.”

The job of the broker would be to gather and assess these granular levels of exposure data and present them to the insurance markets for consideration. Were this to occur, Prinn describes what might happen next: “An insurance carrier might say it will insure this many planes taking off to 1,000 feet in particular regions of the world; this many planes going from 10,000 feet to 20,000 feet across the Atlantic; and this many planes going from 25,000 feet to 35,000 feet across specific land masses.”

The carrier might also decide to insure similar elements as the plane makes its descent to the ultimate landing. “If this happened,” Prinn says, “the need to separate the aviation insurance market into two sectors would be eliminated.”

What he has just described is a far cry from the current model of providing commercial aviation insurance, in which a broker representing a specific airline submits that company’s breadth of risks to an insurer with which the broker often does business. The new model would democratize the process to offer pieces of risk to all aviation insurance carriers in a free marketplace.

Can the risks of other industries be similarly sliced and diced by brokers and offered to the insurance markets? “Absolutely,” says data scientist Henna Karna, chief data officer at global insurer XL Catlin. “We’re continually looking at data that exists in our environment and creating ways to measure it.”

These data are not limited to a company’s internal financial and operating data. “Exogenous credit data, political risk data, cyber risk data, and unstructured data can all be part of the picture,” Karna says. “The goal is to model the risk by considering every available and quantifiable factor that may affect it. We’re getting closer and closer to mining, analyzing, modeling and managing all this data for insurance purposes.”

Better Data, Better Risks

The sharing of detailed client exposure data in a digital platform provides the opportunity for insurers to diversify their risk portfolios by reducing exposure accumulations in specific areas. Karna provides the example of a global manufacturing plant that operates 9 a.m. to 5 p.m. Monday to Friday.

“Say the data coming from the sensors attached to factory equipment indicate the company makes most of its products on Tuesdays and Wednesdays, with the bulk of these items coming off the production line between 9 a.m. and 11 a.m.,” she says. “A blackout or machine glitch during this period on a Tuesday or Wednesday would cause a much bigger business interruption risk than other times of the day the rest of the week.”

Today, the company’s insurance policy from a single carrier does not distinguish these risk factors. By breaking up the risk into difference pieces, and bringing in other quantifiable data like seasonal weather and machine maintenance, other carriers have the opportunity to choose which exposure elements they may want to bear. In turn, this helps the insurers balance their risk portfolios with exposures that are uncorrelated, Karna says.

Burns agrees. “By modeling and sharing risks, carriers can avoid aggregating too much of a single risk,” he says. “Insurers have a finite amount of exposure they can take. Their balance sheets are only so big.”

The new model would present a way for brokers to spread risks among different insurers to their clients’ benefit. “If we have a system where brokers share client risks with all the insurance markets in a centralized shared services model,” Burns says, “this would be a far more efficient way for insurers to spread their risks and for clients to receive more competitive premiums.”

Current expenses up and down the insurance value chain would wither, Garratt says. “If clients share their data with brokers, and brokers share this data with insurance markets, it will result in reduced costs for all parties,” he explains. “All those inputs, calculations and equations that each broker and carrier must do on their own would be removed from the process. There would be no more need for rekeying all this data as it’s passed along the value chain. Instead, the exposure data would move seamlessly and transparently from the client to all potential risk bearers, dramatically reducing acquisition and operating costs.”

This would certainly be a positive development for business clients. “If a broker presents a good commercial risk to all the insurance markets—which is apparent in the client’s exposure data—carriers can compete to charge less in assuming this risk, based on their respective underwriting appetites,” Garratt says.

Although the new model would produce less traditional income for brokers, the loss of revenue would be offset by heightened efficiencies. “Brokers have significant operating expenses that are a reflection of the current inefficiencies in the market,” Garratt explains. “If you remove these inefficiencies, brokers can reduce their costs to maintain current profit margins.”

Moreover, the broker’s enhanced knowledge of clients’ exposures presents the opportunity to become more involved in mitigating clients’ risks. “If a broker comes to us with a client whose exposure data indicates is risky, we would charge more to assume the risk or not take it at all,” Garratt says. “But crucially for the client, the broker and the underwriter now have the ability to help the client manage these exposures, working to reduce the activities and behaviors that resulted in the company being perceived as a higher risk.”

This creates value for the client and possibly a new revenue stream for the broker, while furthering the closeness of the relationship brokers enjoy with clients. “Less money is consumed by process and transaction, and more is used to pay claims, provide value-added services and develop new products,” he adds. “The outcome in all cases is better, quicker and cheaper service for our clients, which is what we all must focus on.”

Customized, Complex Products

By participating in the proposed data-sharing model, brokerages and insurers will be in a more opportune position to create bespoke insurance products. “All that exposure data in the hands of a carrier or a broker can be an engine of innovation,” Karna says.

She provided the example of a large retail chain caught in the crosshairs of a reputational disaster. By mining social media data, the company’s broker may learn that flash mobs are forming to protest the business in a variety of store locations.

“For the sake of argument, let’s assume the organization has comprehensive property insurance absorbing losses caused by vandalism that occur in its stores’ parking lots, which generally have 300 to 400 cars parked per lot,” Karna says. “Now let’s assume the financial limits on this insurance policy are $1 million. Would this amount cover the potential vandalism of cars in the aggregate?”

Possibly not. Even if it did, how much of the total limit would be left over to absorb additional property losses throughout the remainder of the policy duration? “The opportunity now exists for the broker to craft a bespoke insurance policy absorbing the one-time property damage losses caused by vandalism and present it to carriers for their consideration,” Karna says.

Prinn cites similar value. “Brokers and carriers have the ability to take a very complex commercial insurance program like one sees in the oil and gas sector and ferret out comparisons across different oil and gas companies,” he says. “You now can take a common look at these risks, which wasn’t possible before, allowing complex (insurance) products to be packaged.”

There is even the opportunity for brokers and carriers to share customer data with other industries, assuming the owners of the data opt in for this use to avoid privacy regulations.

“Wouldn’t it be great if I bought travel insurance and the carrier shared this data with a rental car agency to set up a vehicle for me when I landed?” Prinn says. “Or the pension side of my insurance company knows I have children and recommends setting up a college plan at a local bank? The future broker or carrier might well be able to help with these things, which is very exciting. And we’re still really at the beginning of all this.”

Nevertheless, he is confident the current model of insurance will be relegated to the trash bin of history. “I was a street broker at Marsh placing Fortune 500 risks for 20 years with carriers that I knew from pure personal experience alone could take on these risks,” he says. “I can tell you unequivocally that this art form is dying. The broker of the future will know how to use data and analytics to find the right insurance markets for their clients, as opposed to relying on experience alone. The model of tomorrow will be a blend of art and science.”

Whenever he talks on the subject, Prinn frequently mentions his 10-year-old daughter’s interest in playing the online game Minecraft. She listens to the YouTube videos of a young man in his 20s named Daniel Middleton, a professional gamer who plays Minecraft and comments about the game’s intricacies to his online listeners.

“I mention Dan because last year he made something like $16 million,” Prinn says. “If you told me five years ago that some guy who sat in his home commenting to kids on a video game would make this kind of money, I would have fallen over laughing. In no way could this have been predicted.”

He feels the same way about the new model of insurance. “Ten years ago, if you told me the traditional model would change so the customary parties to the transaction could share data, I would have dismissed it out of hand,” he says. “And now it is upon us.”

The Tools Are Here

Change is tough for any industry, but the alternative is stark. Just look at the many industries that failed to heed the disruption caused by a technology interloper. “If a broker believes its future value remains as a middleman, where it is being paid merely to access an insurance market, it is dead before it knows it,” Prinn says. “The entire industry is under siege by technology companies that will create better models unless we do it first.”

Down the line, as the internet of things becomes ever more mainstream, millions of sensors will produce an abundance of data, sharpening the ability of brokers to analyze complex risk exposures to a fine point—if they take pains to make this happen.

Yes, there are obstacles to be overcome, including the need to structure data into common formats. But these are relatively easy hurdles to surmount, and organizations like ACORD are already tackling the problem. “Once we have structured data, the entire ecosystem can move in sync to share information and bring down costs,” Burns says. “There’s no going back to the ways things have been.”

Others agree. “We now have the tools to do things we’d only dreamed about before,” Karna says. “Much of our work here now with data is focused on seizing these opportunities.”

The future is as bright as the industry allows. “There’s a tremendous amount of excitement now why the traditional insurance market must change and how this can occur,” Garratt says. “And that can be a catalyst for needed change to occur at a really fast speed—to the benefit of the insurance market and our clients.”

Banham is a Pulitzer Prize-nominated business journalist and author who writes frequently about the intersection of technology and insurance.