The Future May Be Closer Than You Think: Cat Bonds Traded on Blockchain

The Future May Be Closer Than You Think: Cat Bonds Traded on Blockchain

In June @JamieMacgregorC and I published a Celent report, Blockchain in Insurance: Use Cases which included a scenario we labeled “Alternative Marketplaces”. We described it as a blockchain that provided a:

shared environment for placing insurance risk, where brokers or the insured and the insurer capture the status of the risk, including exposure, risk share, and policy conditions. Smart contracts are then used to ensure collection and disbursement of premium amounts and the checking of coverage in the event of an incident. The distributed ledger acts as the record of risk placement, including layers and participants.

We didn’t expect that, in July, we would see an announcement that @Allianz and their partner, Nephila Capital, had completed a proof of concept around trading catastrophe bonds on a blockchain. http://www.carriermanagement.com/news/2016/06/15/155462.htm

In general, there are challenges with blockchain technology regarding handling large transaction volumes, managing complex rules, and delivering acceptable response time performance, but this announcement is an indication that the platform is moving forward.

$100million — Follow the Money: Investment in Innovation Ventures

$100million — Follow the Money: Investment in Innovation Ventures
The announcement yesterday that MassMutual has set up its own fund to invest in innovations that may/will affect life insurers is another move demonstrating how real money is being bet on disruption. Here is the link to their press release site: http://www.massmutual.com/aboutmassmutual/newscenter/pressreleases Celent is aware of several organizations which have set up similar funds. These are not 3rd party venture funds, but are managed, directed, and owned wholly by insurers. These moves signal that innovation leaders are increasing investments to discover new ways of responding to customers’ needs. The difference from past behavior is that insurers want to own the technology, not just buy it once it is available on the market. In these companies a first mover advantage strategy is replacing the age-old fast follower approach. The bet is that, as technology investments pay off, patents and expertise barriers will prevent others from even being able to follow. Insurers will gain advantage because they own a protected capability, or they will be able to license it and capture an alternative revenue stream. Stay tuned. It’s going to be exciting!

Innovation that Delivers on the Brand Promise at USAA

Innovation that Delivers on the Brand Promise at USAA
The announcement today (http://www-03.ibm.com/press/us/en/pressrelease/44431.wss ) of the use of IBM’s Watson platform by USAA demonstrates several of the current research themes at Celent. The move is an excellent case of innovation at the intersection of brand, risk management and technology. First and foremost, this is another example where USAA is delivering on its brand promise – to improve the lives of active duty and veteran military members and their families. The company will use Watson will to answer the questions of service military members who are transitioning to civilian life. An firm’s brand promise is at the foundation of the Celent customer experience model. It is the key characteristic that signals the evolution from a customer relationship management (CRM) to an experience approach. Second, this development is an illustration of an increased focus on prevention and risk mitigation. Traditionally, insurance has been a backward-looking, financial indemnification product (we pay you when there is a loss). This approach shows how insurers will innovate to apply technology to help insureds more effectively manage the risk in their lives (reduce or, avoid risk, altogether). This redirection will occur in commercial, as well as personal lines (see previous post on this blog: “My Risk Manager is an Avatar”). Finally, this is a business application of a computing approach that, up to now, has been closely held in the laboratory, in select pilot accounts, and in a custom, controlled environment (such as Jeopardy!). It will be fascinating to see what we humans, and the machine, Watson, learn in from this insurance debut.

My Risk Manager is an Avatar

My Risk Manager is an Avatar
In the world of Commercial Insurance there exists the very curious role of Risk Manager. I mean curious in the sense that successful risk managers appear to have superpowers. They are charged with taking the actions necessary to avoid or reduce the consequence of risk across an entire enterprise. Their knowledge must extend deeply into a variety of subjects such as engineering, safety, the subtleties of the business of their employer, insurance (of course), physics, employee motivation and corporate politics / leadership. Their impact can be wide-ranging, from financial (eg., dollar savings from risk avoidance / mitigation) to personal (the priceless value of the avoidance of employee death or injury). Sadly, the tyranny of economics restricts the access that businesses have to continuous, high quality risk management. Full-time risk managers are prevalent in huge, complex, global companies. These firms often self-insure, or purchase loss sensitive accounts and the financial value of a risk management position (or department) is clear. The larger mid-market firms can afford to selectively purchase safety consultant services, their insurance broker might perform some of these tasks (especially at renewal), and their insurers may have loss control professionals working some of these accounts. However, for the majority of small businesses, risk management at the professional level is not affordable. Over the past year, I have toyed with different ideas about how to automate this function in order to bring the value of a risk manager to the small commercial business segment. My attempts were always unsatisfying (and one reason I have not blogged this idea before). However at The Front End of Innovation conference last week in Boston, a presentation by Dr. Rafael J. Grossmann (@ZGJR) crystallized the vision. I can now clearly see how existing technology can be combined to create a Risk Manager Avatar. Dr. Grossmann is a trauma surgeon who practices in Maine. In addition to the normal challenges of his profession, he is one of only four trauma surgeons servicing a very wide area. Although sparsely populated, the challenge of distance and time complicates the delivery of medical services. Dr. Grossmann presented his vision of a medical avatar, a combination of technologies which will perform 80% or more of the routine medical cases in a consistent, timely, and cost effective manner. Combining the technologies of mobile, voice recognition, virtual reality, artificial intelligence, machine learning and augmented reality forms a new silicon entity – a medical doctor avatar. He also introduced a company, sense.ly, that is now working to deliver similar services (video here: http://www.sense.ly/index.php/applications/). If such systems can deliver medical services, then why not risk management? For example, given permission, a system would monitor the purchases of a small company and identify when the historical pattern changes, eg., when the company begins to buy new types of materials. Using predictive algorithms, the pattern can be compared against others to evaluate if there is likelihood that the company is now performing new business operations. The avatar could then contact the small business owner to consult on options (endorse policy, retain risk, cease operations). It could also escalate the issue to an underwriter to evaluate more complex options. Someone will build a Risk Management Avatar. The question is, who will do it first?

If only we could trust data available on social networks…

If only we could trust data available on social networks…
Some insurers are starting to launch e-reputation insurance products for individuals. Indeed, in France Swiss Life started to launch last year an insurance product targeting students about to start a professional career or any persons worrying about all data and information about them on the web. Very recently Axa France also launched a similar insurance product. While it’s been a while that we have been speaking about how insurers can leverage social network data in claims or in underwriting, it seems some of them just apply the simple rule that consists in recognizing these types of data just represent a new business opportunity. With the importance taken by the notion of self-image and reputation in the public (not only the young one), I tend to think this is an interesting field to investigate. In the case of Swiss Life, the insurer uses a dedicated e-reputation agency called Reputation Squad and, for a bit less than €10 a month, the insured can action the insurer’s e-reputation agency, who will try to put pressure on website or social network owners and ask them to erase data using the threat of a battery of juridical means. Of course, it’s almost impossible to erase all kinds of data related to a person from sites and social networks on the net and it is here that the real issue appears. Actually if there are still data left after all the juridical measures have been triggered, the insurance service proposes to flood existing data with a massive positive information and data content about the insured. While I think there is certainly a need to fulfill when insurers propose specific juridical assistance to erase data about their insured from social networks and specific Internet websites, I think flooding the web with exclusively positive information about a person demonstrates how harmful open data on the web can be. It raises two simple but important questions for insurers: Can we trust information publicly available on social networks? If external sources – in our case here insurers in the frame of their obligation towards insured with regard to e-reputation insurance products but we can assume insurers are not and will not be the only external sources playing a role in here – start flooding the web with biased data about individuals, is it really a case to leverage social network data for claims and underwriting in the long run? Addressing these questions should be according to me the starting point of an evaluation to invest in technologies whose objectives are to leverage social network data.