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Re-Cognition Factor: Changes Coming to Insurance Risk Management

Jennifer Overhulse | May 23, 2016

For fans of science fiction, it truly is a fantastic time to be alive. For conspiracy theorists, not so much. Movies like “Terminator” brought a baseline familiarity of cognitive computing into the mainstream via the human-extinction-seeking, self-aware software solution, Skynet. More than 30 years later, self-awareness is still not on the immediate horizon and many have yet to realize the real ways intelligent machines can change the ways in which we live, play, and work.

During the recent ITA LIVE executive event held in Ft. Lauderdale, Craig Bedell, ARM, global insurance industry executive for IBM, talked about the ways in which insurance in particular is recognizing the benefits of cognitive computing, and the ways in which cognitive computing may (or should) be utilized for insurance in the future. Designed largely to enhance and not replace human expertise, cognitive computing is part of a new and heightening wave of innovation washing over the insurance industry.

Ready for Insurance?

Cognitive computing is the simulation of human thought processes by a computer, typically involving a learning process in which computers analyze information gathered via data mining, pattern recognition, and natural language processing as the primary inputs. Not only does it sound sophisticated, it is, and in an industry often accused of being digitally deficient, it may seem logical to ask if insurance is ready for technology as advanced as cognitive computing. The less obvious question, though, is to ask whether cognitive computing is ready for insurance.

How can cognitive computing go where other technologies have tried and failed? It turns out, it is more than just legacy systems and processes hindering technology adoption in the insurance industry, it is the complexity of the business itself. Insurance is a highly-regulated industry with specialized processes and “language,” if you will. Therefore, it has long been assumed that human hands and minds—knowledge workers—had to touch everything, to control every process, and to manually input every decision. Perhaps insurance is just too complicated for cognitive computing to penetrate?

If that is true, then the success of IBM’s artificially-intelligent lawyer, AI Ross, should also be impossible. Universally recognized for specialized language, difficulty in gaining a degree in the discipline, and the rapidity of change within the profession itself, the legal field has many similarities to insurance. But, according to a recent article published on Futurism.com, law firm Baker & Hostetler is now “employing IBM’s AI Ross to handle their bankruptcy practice, which at the moment consists of nearly 50 lawyers.”

Ross is built on the same IBM Watson technology platform Bedell discussed with insurance executives at ITA LIVE, and which he indicates “uses natural language processing and machine learning to reveal insights from large amounts of unstructured data.” Again according to Futurism.com, Ross can “read and understand language, postulate hypotheses when asked questions, research, and then generate responses (along with references and citations) to back up its conclusions. Ross also learns from experience, gaining speed and knowledge the more you interact with it.”

And, as if that wasn’t enough, Ross monitors legal decisions for relevant, emerging case law in real time. If “intelligence is a learned behavior” as Jag Randhawa emphasized in his ITA LIVE keynote, then isn’t cognitive computing the natural next step for insurance?

Not So Fast

By simulating human thought processes, cognitive computing “scales and accelerates human expertise,” according to Bedell. “But, cognitive systems don’t do your thinking for you.”

Instead, cognitive systems “utilize advanced analytics to bring facts into context and enable humans to make more informed decisions, faster.”

Considering the relatively outdated, and largely manual, state of affairs (and processes) in terms of technology in the insurance industry, it is going to take some time for insurers to go from 0 to 60 in terms of cognitive computing. In fact, there are many facilitating technologies, such as the advanced analytics Bedell references, which must be implemented before the full benefits of cognitive computing can be realized by insurers.

“For the most part, cognitive insights enhance existing decision-making by providing enhanced insights to existing systems from call center systems, underwriting, claims, or website capabilities such as rate/quote,” said Bedell. “That's not to say cognitive is magically plug-and-play. There is a significant amount of data population and training that cognitive systems demand. IBM has taught IBM Watson to speak a number of languages including English. We've also taught it, to a degree, the language of certain industries, including insurance. However, as we all know, each company has its own parlance and proprietary approach to insurance and the businesses, operations and coverages it handles.”

Bedell’s point about Watson is well-taken about cognitive computing as a whole. There is work to be done, but at the end of the day, cognitive computing “will affect nearly every aspect of the traditional business model, let alone the quickly emerging modern model for insurance companies. Systems that read, see, hear and understand will advise professionals, enrich the interactions of our clients and fundamentally alter our appreciation for risk and risk management, let alone customer service.”

The Most Immediate Return

Obviously, before full-on business model transformation takes place, incremental incorporation of cognitive computing into day-to-day insurance processes must begin to happen. And, in terms of testing the waters, many insurers will likely prefer to silo cognitive, at least slightly outside the enterprise, by housing it within call center operations. In a call center setting, cognitive computing can deliver immediate benefits since the technology thrives in an environment with high volumes of unstructured data, enables text-to-speech and speech-to-text, as well as language detection, tone and sentiment analysis, personality insights, and even relationship extrapolation.

“One of the most popular applications of cognitive in insurance is clearly in the area of providing expert advice,” said Bedell. “Whether it be delivered through a call center channel to answer the questions of customers or to provide them advice; to enrich the services provided by call center reps; as a virtual agent on a website; providing expert advice to employees or to insurance agents; insurance companies across the globe are deploying cognitive virtual agent capabilities.”

Further, and because of its ability to find patterns, identify exceptions, and predict outcomes, cognitive computing’s other most intuitive use is in underwriting, where much work is still performed manually. Even as it frees up underwriters for other tasks, cognitive computing can enable an increase in straight-through processing (STP), improve underwriting effectiveness and risk assessment by getting more insights out of unstructured data, and scale an insurer’s underwriting capabilities.

“IBM has clients utilizing cognitive to improve customer interaction, underwriting, and claims decision-making, and to harness the insights stored away in documents, records, notes, and voice messages, as well as journals, surveys, case studies, manuals, and industry literature—to name just a few sources—where this information created by humans for the consumption of other humans has heretofore remained unusable by systems,” said Bedell. “This is what makes cognitive so exciting to me as an old time underwriter, branch manager, and home office professional, let alone analyst.”

As one might imagine, call centers and underwriting are just the tip of the large cognitive iceberg. The short-term implications for claims adjusting, fraud detection, and marketing optimization are potentially transformational. Companies like RiskGenius, for example, are already putting elements of cognitive computing and machine learning to work analyzing the language of insurance policies and contracts faster than it can be done manually.  These efforts can quickly and easily identify common clauses and terminology to serve as the basis of libraries which have the potential to reduce completion time for contract and policy review.

“I’ll Be Back.”

So, how do we have this conversation without industry insiders and old-timers going all “Terminator” and Skynet? For now, the important thing seems to be striking a balance and moving incrementally and responsibly to implement cognitive computing solutions and begin to realize the benefits available throughout this risk-averse industry.

“You can't have a conversation about cognitive computing without this sort of question coming up,” said Bedell. “It’s a great, exciting, and sometimes uncomfortable subject. Here's my short answer to that question. Cognitive is going to change the nature of some jobs for sure, every technology has. …cognitive will, in fact, affect routine tasks in the underwriting, rating and claims processes. It may even replace certain functions altogether. It may affect the numbers of employees needed to support certain aspects of insurance operations, but it won't be cognitive alone that's responsible for that. …finding a place for cognitive, and fitting it in to an organization that also attracts and retains talented professionals, will be the charter that successful insurance companies achieve. This is by no means the end of the line. In fact, I argue that it's the next generation of risk management that we are just entering.” 

 


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