The Race to Find the Next Insurance Credit Score (or How, Maybe, to Reinvent P/C Insurance Pricing)

The Race to Find the Next Insurance Credit Score (or How, Maybe, to Reinvent P/C Insurance Pricing)

What is an insurance credit score? Basically it is a set of algorithms applied to data from credit reports which provide guidance for pricing and underwriting personal lines insurance. Although it has been a source of political and regulatory controversy over the years, the use of insurance credit scores is now widespread.

Much of the controversy has been over possible disparate impacts on various societal groups. But a root cause of the controversy has been the non-intuitive relationship between a given person’s use or misuse of credit on the one hand—and that person’s probability of incurring insured losses on the other hand. It just doesn’t seem to make much sense. But statistically there are correlations, which in general have passed regulatory review.

Insurance credit score controversies now ancient history (i.e. were settled before most millennials graduated from high school).

But suddenly something interesting is happening.

The race is on to find the next insurance credit score—and the winners (if there are winners) will gain a pricing (and underwriting) edge.

There are only two requirements to enter in this race.

  1. You have to forget about all the kinds of data and information that insurers have been using to price and underwrite risks.
  2. You have to use your digital imagination to find some new data and models which provide the same or better lift as the old data and models which you have just thrown out the window. (Lift is the increase in the ability of a new pricing model to distinguish between good and bad risks when compared to an existing pricing model.)

So what kind of new data might a digital imagination look at?

  • For personal auto, connected cars will provide a rich data set to mine. How about whether a car is serviced at the manufacturer’s suggested intervals (correlated with whether the car is serviced by a dealer or by an independent repair shop)? Or the use of a mobile phone while the car is in motion (correlated with time of day, precipitation, and whether satellite radio is also playing)? Or use of headlights during daylight hours (correlated with the frequency of manually shifting gears in a vehicle with an automatic transmission).
  • For homeowners insurance, connected homes could supply all types of new data. For example, whether Alexa (or other IPA) controls the home’s HVAC systems, correlated with setting security alarms before 11 pm). Or, electricity and gas consumption, correlated with use of video streaming services on week nights. Or the number and type of connected appliances, correlated with the number of functioning smoke, CO, and moisture detectors.
  • For commercial liability insurance, telematics and IoT will be the key data sources. Does a business with 10 or more commercial vehicles use both fleet management and telematics solutions? What mobile payment options are offered (correlated with dynamic pricing capabilities)? The business’ use of social media and messaging apps, correlated with the degree of supply chain digitization.

Of course obtaining a lot of this data will require permission from policyholders—and even with permission these methods may raise social or political issues. But premium discount and loss control incentives for telematics programs have proven effective. And for better or worse, Scott McNealy got it right in 1999.

Social Networking, Meet Underwriting

Social Networking, Meet Underwriting

Our esteemed social networking guru, Craig Beattie, circulated a blog posting that he found at

It describes an internet company, Social Intelligence that monitors social networks to help companies with hiring decisions. Their data mining tool collects information from the major sites looking for behavior-based information about job applicants and summarizes what is found in a report. It uses only publically shared data and includes a review by humans to eliminate any “false positives”. There is also a service for continual monitoring of existing employees. According to the blog posting, the company makes the point that with the emergence of social networks, shareholders will expect companies to use such services to evaluate new and existing hires and reduce the liability of the company from lawsuits, damage to reputation, etc.

Celent has not reviewed this company or its solution. However, in discussing what this approach might mean from an insurance perspective, several questions arose. Will such monitoring be considered a mainstream risk management technique one day? Would an insured using such a tool be rated a lower risk than one that does not? Should the shareholders of an insurance company reasonably expect the underwriting process to include the monitoring of social networking sites, especially for the general liability, disability and workers compensation lines of business? In the past, such data mining has been blocked by regulators based on privacy issues, but if all this information is willingly made public will those objections still be valid? Social networking, meet underwriting.

If You Build It, Will They Come?

If You Build It, Will They Come?

What is the link between improving service technology and improving sales incentives? This was the topic of a very insightful conversation that I had recently with an insurance CIO. It highlighted how interrelated the processes are in the insurance value chain. Investments can be made in one area, but if other, correlated areas do not receive attention, the benefits from the initial investment may be less than expected.

The two areas in question are policy administration and distribution management. This company has determined that the key to managing their profitability properly is the ability to change their mix of business in order to respond to market conditions. This strategic imperative led to a recent investment in best-in-class rating technology to increase the responsiveness of product updates and the speed of new product introductions. The company also upgraded their BI and analytic capabilities, allowing their actuaries to develop new discounting and pricing methods.

The CIO shared that they were pleased with the cycle time reductions and productivity increases that resulted. However, he reports that they only got full benefits they sought after they updated their compensation system. They needed to be able to change incentives in line with product modifications in order to effectively modify their portfolio and manage profitability. In other words, they had to be able to give their distribution force a reason to sell the new products, not just deliver product changes.

This was a twist on the phrase “if you build it they will come” and a reminder to be sure and consider the interplay between separate processes when evaluating investments. In constructing a product administration roadmap, an assessment of incentive management should be made. Incentive system upgrades may be necessary in order to fully benefit from administration enhancements.