An Empirical Study of Insurance Performance Measure
In the ninth article from the (JACF Spring/Summer issue) this author applies Insurance Performance Measure (IPM) to a set of Indian insurance companies over the period 2005-2016. This is the first article published that applies the IPM model on real industry data and studies its implications.
The IPM was introduced in a Winter 2002 JACF article by Joseph Calandro, Jr., then at General Star management, a subsidiary of Berkshire Hathaway and by Scott Lane, then an accounting professor at the University of New Haven. Those authors explained why financial reporting for insurance companies was so challenging and presented the IPM metric as a better way to assess industry and company performance. Evaluating P&C companies is difficult because the unique format of insurance company financials does not lend itself to traditional financial accounting analysis and because the industry’s preeminent performance measure, the Underwriting Ratio, captures underwriting and claims activity but says nothing about investment and risk distribution (reinsurance).
By contrast, the IPM represents the interrelation of underwriting, investment and reinsurance along with a hurdle rate and is quite consistent with Warren Buffett’s expressed desire for a balanced overview of industry performance. IPM uses financial data without modification thereby simplifying and fastening computation. Operationally, it could help in negotiations for reinsurance renewals and identify “Maximum Profitable capacity”—the threshold limit for overall profitability.
Authored by Sai Ranjani Bharathkumar, XLRI Jamshedpur, India
How advances in behavioral science and financial analytics offer an effective way to bridge this gap between marketing and finance.
Our fourth article from the (JACF Spring/Summer issue) discusses how finance executives are often frustrated by spending proposals from their marketing colleagues but cannot seem to be able to quantify the putative benefits. Similarly, the marketing staff is frustrated by the finance team’s inability to convert soft marketing metrics, such as “awareness” and “customer satisfaction” into financial forecasts. The challenge is that neither marketers nor finance executives have been able to articulate a single analytical framework which both explains how and why brands come to flourish or flounder and how brand growth contributes to the business’s short and long term bottom line.
Lacking an effective way to do this now, most managers default to using the hard data they do have, namely how marketing investment is likely to impact sales this quarter and next. This reinforces the widespread focus on quarterly EPS and reduces the perceived value of the marketing department to their ability to hit three month sales targets. This degraded view of marketing’s contribution and the inability to link “soft” marketing metrics to longer term financial returns impedes building long-term brand value. This article focuses on how advances in behavioral science and financial analytics offer an effective way to bridge this gap between marketing and finance.
Building that bridge requires better measures of brand health and financial performance to allocate capital and marketing resources. Undoubtedly, brand building is both an art and a science. But, the finance people can develop an evidence-based framework explaining how some of the “softer” investments such as brand building, contribute to the value of the firm.
Authored by Ryan Barker, BERA Brand Management, and Greg Milano, Fortuna Advisors