The insurance business is where the theory of risk meets the reality of reward or ruin. In that light, success shines on those with the best and brightest underwriting. Knowledge and insight are the essential elements for proper risk-based pricing, while listening and learning are needed to retain happy customers and attract new ones. Competing on more than price is the next level of profitable growth. However, for the majority of companies today, getting to the first step of pricing accurately is a strategic necessity. Fortunately, even for small carriers, pricing is a solvable problem with the right data, resources and staff. But it takes something special to thrive.

Getting pricing right is a good starting point for insurers, even as continuous improvement and smart execution is fundamental in insurance operations.


With the introduction of predictive models, the recipe for success now contains a "secret sauce." Companies must move from simply having data available to seeing what the data tells them in a competitive environment, then knowing what will enable them to exploit strategic opportunities by acting on those insights across the enterprise.

Having, seeing, knowing and acting on a range of data assets through predictive models unlocks the management team's abilities to sustain growth and the lifetime value of policyholders. It solidifies the abilities of insurers to manage pricing, marketing, distribution, claims and customer retention.

Insurers must become relentless in using predictive analytics in pursuit of optimal business outcomes. They must be persistent in finding continuous improvement and insight through better data, added data and more elegant problem formulations based on rational models. Nevertheless, extracting new and better data from insurers' operations can be an ongoing struggle. And using external information to validate internal data remains an analytic problem, not an IT or operational challenge.

In fact, integrating viable external data can, at times, be more productive because it takes some risk out of integration efforts, and enables quicker return on investment. To this end, insurers can let business intelligence vendors assume some of the risk of innovation where the costs are significant and timelines are long. But they also must remain nimble in deploying emerging solutions to maintain competitiveness.

Most enlightened carriers have translated analytic opportunities into four basic categories: loss control, cost avoidance, cash flow opportunity and better decision making. The last category includes an understanding of cost drivers, pricing, risk selection, cross-sell and up-sell, portfolio management, agent analytics, medical management, litigation management and claims settlement. Iteration of the have/see/know/act cycle, as well as analysis of feedback from observed results, can be the foundation of successful and continual operational improvement by insurers.

Now that the majority of industry stakeholders have adopted at least some elements of the predictive analytics process, the latest and greatest options for improving models are coming from newly created levels of analysis and data. In addition, third-party vendors are providing deeper insights and wider applicability than ever before. With the help of knowledgeable industry consultants, second- and third-tier carriers are increasingly finding access to the latest modeling know-how, and to the capacity for harnessing powerful new forms of decision data.


Companies must develop the drive to evolve and the passion to survive and thrive in the current business environment. Today's economy will not tolerate a static strategy. Only those companies that embrace improvement should survive. While smaller firms may look to consultants for help in applying the secret sauce, larger enterprises can work harder at inspiring their people to take on more predictive analytic sophistication across the spectrum of their portfolios. Mid-tier companies must continue to innovate and execute, or they could become targets of choice for acquisition-minded larger companies.

Yet, the goal of applying the secret sauce of predictive analytics is about more than just pricing. In an intricate insurance ecosystem, strategic growth can be enhanced as companies work more collaboratively and efficiently to satisfy market demands. With good analytics, insurers are better able to address product distribution and deal with the challenges of incomplete underwriting and customer information. Predictive modeling helps carriers to adapt those links in the industry's overlapping value chain that are critical to service and operational relationships.

Invention, innovation and inflow of talent and ideas across national borders, industry boundary lines and academic specialties are driving the adoption of analytics and decision support solutions faster than ever before. The convergence of knowledge, the fusion of data and business insight, and a momentous investment in expertise are not going to stop anytime soon. By executing on the latest developments in modeling, data quality, customer metrics and portfolio management, P&C insurers can establish a measurable competitive edge.

Marty Ellingsworth is president and David Cummings is VP of research for ISO Innovative Analytics, a unit of Jersey City, N.J.-based ISO.

(c) 2009 Insurance Networking News and SourceMedia, Inc. All Rights Reserved.

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