Table of contents for Decision Management and Insurance
- Decision Management and Insurance – A Series
- Decision Management and Insurance – Putting the Data To Work
- Decision Management and Insurance – Apply Smarts to Underwriting
- Decision Management and Insurance – Rethink Legacy and Fast Path New Product Development
- Decision Management and Insurance – multi-channel distribution and customer communication
- Decision Management and Insurance – Capitalize on Intelligence to Manage Losses
- Decision Management and Insurance – Business Optimization and Governance
At the core of the Top 10 Imperatives for Insurers is putting the data to work – across channels, in day-to-day operations, in customer interactions and more. Putting data to work means leveraging the historical data you have about your operations, performance and policy holders to systematically increase the value of your corporate decision assets. It means going beyond information reporting, dashboards and visualization. Reports and visualizations don’t impact business performance – the decisions a company makes do. Especially operational decisions.
To illustrate why there is so much advantage to Decision Management; consider an operational decision take at renewal time to retain (or not retain) a customer. A retention decision for a specific customer will be made once every year or two. But it is one of thousands, maybe hundreds of thousands, of similar decisions made within that timeframe. These operational decisions determine the actions the company takes in regard to one of its most valuable business assets—a portfolio of customers worth millions in customer lifetime value. The value of each decision may be small but it is multiplied by the number of customers in the portfolio. The cumulative bottom-line impact of such high-volume decisions is huge.
Decision Management puts data to work by applying business rules and analytics in operational systems, making better operational decisions from the data you have. Many companies are successfully gaining insights from their analytics efforts, but there remains an insight-to-action gap (as we discussed in Smart (Enough) Systems). Your analytics might show you that customer renewal dates are dropping, but there is a gap between this insight and influencing the behavior of agents or customer service representatives.
Decision Management is a systematic way of implementing analytical insights in operational systems, closing the insight-to-action gap.
For example, Infinity Insurance is a $1Bn writer of insurance for classic cars, commercial auto and personal auto. The claims department at Infinity signed up with predictive analytics software from SPSS Inc. (now part of IBM) in 2007 to target process change in a couple of areas – fraud and subrogation. Infinity had some great results when they put their data to work with Decision Management and predictive analytics in their claims operations, including:
- 1100% increase in fast track rate
- 33% higher returns subrogation returns
- Analytic software investment paid off in 3 months
- Subrogation recovery up by $10m/year
Subrogation turned out to be the quickest payoff, with analytically-derived rules being deployed in about 9 months. Read more about their story in my earlier post on putting analytics to work at Infinity Insurance.
Decision Management scales to accommodate decision volume and speed requirements, and so highly leverages the value of predictive analytics and puts your data to work where it has the biggest value, in your business operations.
Next up, Decision Management and Underwriting.