Moneyball for Insurance

The Need and Rationale for the Formation of RAS

Improve Your RBIs (Risk Business Indices)!

Create An Analytical Method for Reducing Insurance Cost

Baseball’s Oakland A’s became World Series Champions when  they  found  an  Analytics   Methodology   to exploit their data. Similarly, Risk Analysis Services, RAS, created a novel solution to better discover the value in insurance data.

The Weakest Point in creating a viable insurance product is the Estimate of Expected Total Losses. This centers on Historical Losses and Analytics to produce credible Estimates of Ultimate Total Incurred Losses.

It is the Value and Credibility of this estimate on which the total and the overall multi-layered pricing structure is based.

Exhaustive Analysis means that the estimate is based on the most thorough possible analysis of all the loss and exposure data.

A thorough analysis leads to a more reliable estimate of total incurred losses. This estimate is even more credible when the process is transparent and includes full audit trails, from the original data to various analy- ses  and  projections,  including  and  not  limited  to:

• Original Source Data

• Automated Ingestion of Loss-Run Lists of Claims

• Excess Loss Analysis showing totals at varying SIRs (to shed light on layering)

• Loss Triangles

• Loss Development Analyses

• Loss Forecasting – projected estimated ultimate total incurred losses

• Inflation-adjusted developed losses

This is not Rocket-Science. But it is a lot of number crunching with different slices of data, all targeted to project ultimate expected losses. We built a platform that allows you to visualize this data with a series of metrics from total losses to frequency and severity and total incurred correlations and volatility metrics. We wanted to make it as easy as possible to provide greater understanding and assurance of the nature of the risk to the reinsurance underwriters.

The objective is provide greater Detail and Clarity. That’s why RAS analyses provide “views” from “3 feet to 10,000 feet” to provide many varying perspectives which yield greater clarity.

In  2011,  we  had  the  idea  of  creating  a  Money- ball   style   toolset   for   the   insurance   industry. The Goal: to build a platform that would enable us to economically provide exhaustive multiple-level ana- lytics, revealing virtually all the possible estimated Total Incurred Losses, evaluated and projected from multiple slices of historical annual data.

We first created system specs for the three automation key pieces (1. Loss Run Data Ingestion, 2. Inflation Adjusted Developed Losses, and 3. Regression Analyses: frequency, severity and total incurred).

Our first big project was with ServPro’s Restoration Risk R etention Group. It was an overwhelming success, saving RRRG over 15% in insurance premiums and freeing up collateral.

Over the last six years of practice, our clients have discovered our exhaustive analytics process works in delivering a more nuanced, granular and credible estimate of Total Incurred Losses.

SUMMARY: Our methodology incorporates common actuarial elements including Loss Development Fac- tors, Inflation-adjusted Developed Losses and Regres- sion Analysis. It produces credible estimates by Successive Loss Layers, in addition to the Ultimate Total. This “deep dive” exhaustive analytics provides insights that help many types of organizations benefit by better knowing their risks and lowering costs.

This deep-dive exhaustive analytics provides insights that help you win!