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Insurance Moneyball – Winning in a New Age of Insurance

Aug 24, 2017 | By: | Topic(s): Changing Market Demographics, Data & Analytics, Data Strategy, Explosion of New Data, Fading Industry Boundaries

Insurers have been masters of data for centuries. But the digital age has ushered in dramatic changes in the types and volumes of data available as well as the tools and techniques to extract insight and real business value from that data. Once the leaders in data-driven decisions, many insurers now find themselves behind the curve. They are aware of the promise and potential of these advances, but stuck in their traditional methods made up of silos of internal data and dated analytic techniques suitable for limited, repeated decisions but not capable of making new discoveries, optimizing business decisions or uncovering strategic opportunities.

In many ways, it is similar to the now famous story of the Oakland A’s in the book Moneyball: The Art of Winning an Unfair Game by Michael Lewis. Similar to insurers stuck in centuries-old business assumptions, Moneyball shows that the collective wisdom of baseball insiders, including players, managers, coaches, scouts and the executive office was subjective, flawed and did not keep up with a 21st century reality. Traditional data analytics (statistics in baseball terms) such as batting average, runs batted in and stolen bases were used to assess a player’s value and potential, and influenced baseball teams’ investments in and acquisition of players.

However, the Oakland A’s’ executive office, led by a forward-thinking data analyst and statistician, uncovered better indicators for success, such as slugging percentage and on-base percentage, that could be acquired and invested in more cost-effectively. While these new data insights contradicted long-held business assumptions and historical beliefs, they proved to be an organizational winner … helping the Oakland A’s assemble a competitive team that took them to the playoffs against teams who spent far more money on players.

Why is this relevant for insurance? Because we are in the midst of the shift from the information age to the digital age, realigning fundamental elements of the insurance business that require major adjustments in order to survive, let alone thrive. One of those adjustments is around data and analytics.

Mastery of Data and Analytics

Just like mastering the game of baseball with data and insights about your team and competitors, insurers must master data and a range of analytics to compete in today’s new age of insurance, particularly with so many Greenfields and startups “shaking up the game”. New Greenfield and startup competitors are the Oakland A’s of the insurance industry. They are rising from within and outside every industry, including insurance. They are capturing the post-digital age business opportunities of the next generation of buyers by leveraging new sources of data and using sophisticated analytics to reinvent insurance.

Insurers who stick to the traditional, pre-digital age formula of relying on internal, historical data used only for pricing and underwriting, will put their businesses at risk … both in terms of retaining profitable customers and in capturing new markets and new customers. Companies that make the shift to leverage new data and analytics are positioning themselves to be the market leaders in the post-digital age.  Those who do not make the shift, risk not only the loss of customers, but also market share and relevance in a new age of insurance.

Factors for Winning in the New Age of Insurance

Just like the Oakland A’s in baseball, in today’s new age of insurance there are some key winning factors … some old and some new. We look in depth at these factors in Majesco’s recently released report, Winning in a New Age of Insurance: Insurance Moneyball. Here are some of the factors we consider.

 

The customer. The next generation of buyers, Millennials and Gen Z, have a very different view of the world, how they expect to engage with companies and what they consider “value” for their money.  These and other factors are driving their view of “what is insurance” and when they need it — on-demand, short-period needs versus ongoing, long-term needs. While their views and behaviors underpin this shift, the breadth of new data makes these new products possible.

The talent. Just like in baseball, there is a fight for talent in today’s data and digital-laden world.  Many insurers are challenged by staff capability, the ability to source new talent, and management bias toward traditional business practices that restrict insurers from leveraging new data opportunities.

The market shift. A shift from risk products to risk prevention services is creating market changes. To put this in Moneyball terms, a walk is as good as a hit. Both put a runner on base. Risk prevention can provide new sources of revenue that will mitigate the decline of traditional premium revenue due to the reduced risk environment. This applies pressure on traditional insurance players by creating and offering innovations and alternatives for customers, which are often driven by data, to minimally match the competition in order to continue to win and keep customers.

The technology. Emerging technologies (including analytics) are creating new capabilities, and they are bringing with them an explosion of new data sources. New data contains unique insights regarding asset-related risks as well as consumer behavior, attitudes, and preferences. Insurance products and services of the future will utilize these insights extensively in design, pricing, risk understanding and consumer engagement. Can we use data to select and choose segments and niches that are missed by traditional product development philosophies? This is another Moneyball concept.

The analytics spectrum.  “Analytics” is a term with a very wide spectrum of definitions both within and across insurers, from Excel reports to cognitive computing and everything in between. Insurers require all the different types of analytics from the simple, informative “what happened” data analysis to the proactive, contextual-based analytics at the other end of the spectrum. Each of these varying analytic types requires different approaches or solutions but must first be grounded in data governance and strategy driven by business goals and objectives.

The New Stadium – Data Lakes

Just like baseball, insurers need to rethink their “stadium” … from a data warehouse to a data lake. The abundance of data that proliferates the world of insurance has always been difficult to centralize effectively for distribution to users across the enterprise. The old stadiums (aka data warehouses) were touted as a single version of truth where all data would come together to give a holistic view of the business.

Unfortunately, the promise of the data warehouse has repeatedly been found to be elusive. The reason for this was simple; today’s version of “all of your data” is not the same as yesterday’s and will not be the same as tomorrow’s. The constant evolution of business makes the promise of a perfect data warehouse the goal you reach for, but never meet. We create data lakes to address that.

A data lake, by its design, does not set a finish line that you will never hit. Instead, it sets a framework in place to consistently acquire “all of your data” but allows you to deliver that data on a use case by use case basis so that you win not only the inning and game…but the series.

Change your Game to Win in a New Age of Insurance

The insurance industry is in the midst of profound change fueled by trends that are converging and pushing a sometimes slow-to-adapt industry into the digital age. The insurance industry’s historical business model primarily rests on the two pillars of gathering and using information regarding risk and deciding which large bucket of similar risks are consolidated; then acquiring capital to manage risk. These two pillars, combined with a bifurcated and inconsistent state regulatory system and the heavy investment in marketing brands for personal lines (such as the Gecko, Flo and others), have consistently conspired to keep new competitive entrants out of the traditional insurance ecosystem.

However, the digital shift is creating leaps in innovation and disruption, challenging the traditional business assumptions, operations, processes and products of the last 30-50 years. The fast growing field of new entrants and investors eyeing the insurance industry see it as a “prime opportunity” for disruption. Increasingly insurers are seeking paths to grow their businesses by capturing the next generation of customers with new engagement models, products and services. The increasing transparency and empowerment afforded by data, the Internet and digital technologies is leveling the playing field.

For traditional insurers to rise to the competitive forefront, it will require them to rethink their business models and realign them with the digital age and the massive sources of new and innovative data that will redefine the business for the next 10-20 years, not those sources from the past 10-20 years.  Insurers must rapidly recognize the relationship to game theory regarding their risk models.  In short, insurance companies are the house taking bets from their customers. Those customers are betting on winning a game whose rules they will never fully understand while playing against a constantly changing cast of characters they don’t know.

Yesterday we automated existing processes, and we continued to battle underwriting — thinking in terms of “intangibles” that couldn’t be automated. Tomorrow we need to start thinking coverage by coverage / game by game, “How do we win? Can we re-engineer our formula for growth?” How do we find value in the market that others can’t see?

In this new age, value is not just in underwriting the right customers, but also in underwriting the right risks, under the right constraints and in the right markets. It is a new game of Moneyball … are you ready to join?

About the Author

Kris Moniz

VP - Data Services, Majesco

Kris Moniz is VP Global Data Services at Majesco and leads the Majesco Consulting Services, Data Division. A twenty two year veteran of Information Technology, Kris has spent the last seventeen years focused on Business Intelligence and Data Strategy. Prior to coming to Majesco he spent ten years working for insurance carriers large and small where his work ranged from Application Developer to Solution Architect to Data Governance Lead.

Kris currently manages a variety of accounts all focusing on complex data projects including historical conversions, platform migrations and data lake implementations.

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