Three Simple Auto Repair Claims Analytics That Can Seriously Improve Profitability For Property/Casualty Insurers

By Rejean Godin, Partner, InEdge

Montreal, QC (Sept. 2, 2015) – In the quest to gain a competitive advantage in today’s aggressive marketplace, insurers can overlook a valuable asset already in their possession: auto repair claims servicing information. By putting analytics to work in this area, insurers can improve all aspects of the auto repair claims servicing process, from appraisals through the repair costs themselves to claim payments. In particular, with careful monitoring of the insurer’s relationship with repair service providers, it’s not just the bottom line that improves, but experiences by the clients themselves stand to benefit.

Three main areas stand out for optimizing with analytics: appraisals, body shop management, and parts and labor. Using analytics to focus on these three areas – with information already available to the insurer – will lower costs, improve relationships, and improve service. In addition, claims managers obtain a better overall picture of the state of affairs and are better informed, ready to extrapolate future trends.

In the area of appraisals, analytics provide claims managers the ability to assess the overall performance of all types of appraisers, from employees through external contractors to the body shop employees themselves. Metrics of special interest in this area include the time required to complete an estimate, the number of supplements and/or revisions required, the distribution of estimates between regular and preferred body shops, etc. With this information at their fingertips, claims managers can improve appraiser-related activities and structure their information and relationships more effectively.

With respect to body shops, analytics supply the intelligence needed to accurately measure different aspects of body shop performance. For example, tracking the ratio of OEM to generic parts can be used to control costs. The average length of time required to complete an estimate can be used to compare the efficiency of different shops. Similarly, knowing the percentage of payments processed electronically can be leveraged to reduce operational costs. Information such as this can not only improve the bottom line, but can be used to incentivize body shops through performance recognition programs.

The third area where analytics have a big impact is in parts and labor. Controlling costs here is an ongoing challenge. In this respect, analytics provide direct insight into the efficiency of repair activities, by providing a statically sound view on such things as the types of parts being used to carry out repairs. In seeking to improve profitability, two metrics stand out. First, the average number of labor hours by category, in comparison to the estimates for similar incidents. Second, the ratio of OEM to generic parts used in the estimates provided by the body shop.

Viewing claims and estimates at the parts and labor level of granularity gives claims managers direct influence on the efficiency of the most fundamental repair processes and activities.

Auto repair claims analytics becomes possible by integrating and conforming data from two distinct systems: the body shop management and claims management data systems. This includes data from the insurer’s operational systems, its BI environment, as well as external body shop management feeds. The transactional data is fed into the analytics application from which the most valuable information is derived in support of the new analytics engines.

Implementing a system that fits this description is not prohibitively expensive. Modern auto repair claims analytics systems are supplied with pre-packaged reports, eye-friendly dashboards with key performance indicators (KPIs) addressing the most pressing needs of claims managers. For optimal efficiency in usage, a well-designed auto repair claims analytics system leverages the toolsets with which claims managers are already familiar, greatly reducing the learning curve. The key is leveraging and enriching the insurer’s already-existing information assets to give claims managers what they need, when they need it, reinforcing this crucial link in insurance value chain.

For more on Auto Repair Claims Analytics, download your copy of the white paper Optimizing the Claim Servicing Process with Auto Repair Claims Analytics.

About the Author

Rejean Godin is a founding partner of the company and has more than 25 years of experience both as an entrepreneur and a manager, including 20 years in information technology, specialized in large insurance companies. Rejean was also the founder and senior partner of a financial and investment consulting firm that achieved significant growth. Rejean graduated from HEC Montreal in 1986 with a degree in business administration specializing in finance.

About InEdge

InEdge is a leader in Insurance Analytics solutions. Experienced at quickly leveraging data, InEdge seamlessly and powerfully creates business advantage for its clients. Since its creation in 1994, InEdge has designed and implemented some of the most sophisticated analytical applications available today. Our clients add up to an impressive roster of Property & Casualty and Life Insurance companies. Our Analytics solutions improve and make easier decision-making at all levels for our clients. For more information, visit

Source: InEdge