Data Driven – The Future Is Now For Auto Claims Technology


If you’ve been following the news lately, it’s quite apparent that the hunger for data and the ability to parse and analyze it goes straight to the highest levels of our government. While we in the claims industry are not involved in international intrigue or attempting to create a spy grid, we can however harness data to effectively influence our decision making.

As  technology  continues to advance exponentially, much can be done to radically improve the auto claims process. For many years, traditional thinking and status quo management methods squashed innovation in favor of tired, cost cutting measures and recycled material damage trends that rotate from DRPs to independent appraisers to staff appraisers and then back again. At the same time, popular metrics also emerge on a cyclical basis with the usual suspects of cycle time, average appraisal value, parts usage and correctly documenting total loss options often rounding out the list. But these are all “flavors of the month” and don’t fully address or reveal the root causes. We need to dig a bit deeper.

Today, there is so much more that can be done if data is effectively analyzed. A claims manager could nearly predict outcomes and channel resources for the best results based on an aggregation of data and using it to forecast. Need more staffing in the field? What are the historical repair costs of a certain year, make and model with a matching impact location? Where are higher labor rates going to result in more total losses? Which companies allows their policyholders excessive rental on subrogation demands?

Here’s a few examples of how auto claims  technology  and resulting data can be channeled to improve workflows, eliminate unnecessary touch points, and create a more efficient process.

1. Intelligent dispatching. Imagine putting the right claims into the right hands every time. A robust dispatching solution could identify a field representative based on closest location, past performance, experience levels, historical cycle time results, CSI ratings, language if translation needed, estimating software platform, workload volume, current volume for the day, and comparisons of other representatives resulting in an algorithm that instantly give the file to the person who is most likely to provide the most successful outcome.

2. Subrogation settlement analysis. What would it be like to analyze the subrogation process beyond just the demand in hand? Find out which companies tend to put OEM parts on every estimate, even if alternative parts would be completely acceptable. Which companies overpay their insureds for rental when the repair is minor? Do a large number of your files end up in arbitration? If so, what are the triggers that can be identified prior to this? Over time, a subrogation specialist can focus on certain trends when analyzing and reviewing demand files from various companies.

3. EXIF photo data. Where and when? For quite a while now, most digital cameras have had information embedded in each photograph. With the advent of smart phones and tablets being more widely used, geocode location data can also be included. What does this mean? The era of date stamping a photo on the front is gone. If the detailed information needs to be used for litigation, the EXIF data can document what camera took the photo, the time it was taken, and often the exact coordinates. This means a field representative’s day can be reconstructed or a re-inspection date can be confirmed to ensure the condition of a vehicle at a specific point in time. This is far more accurate than an imprecise date stamp that requires user programming on a camera.

4. Claim delay analysis. Every claims manager wants a 48 hour cycle time average for an auto damage appraisal claim. Can this always be achieved? If each step of the appraisal process was documented from assignment to completion, any issues and resulting data points along the way lead to a treasure trove of information. You might discover that an incorrect phone number or vehicle location leads to 25% of all delayed files. This could be a valuable training tool to discuss with adjusters and stress the importance of inputting accurate information prior to a dispatch. On the other hand, data may show that a certain percentage of files are delayed due to an appraiser being overloaded. This could lead to an immediate focus on better allocating field resources.

5. Location volume analysis. Do you need to increase your field staff? How about adding more DRPs to your network? Just think if you could pull up a map at a moment’s notice and track volume in a certain location. You could track average appraisal values in various zip codes, cities and states and break the information down to an even more granular level. Detailed data can be run over a period of time and compared to newly written policies to predict staffing needs in certain areas before the losses even occur. This can help in forecasting and budgeting for future years.

Data, when simplified and made usable, is incredibly powerful. Nary a one of us leaves the house today without a smart phone is his or her pocket packed with valuable data. To some, this may represent important phone contacts, mapping directions or family photos. Nevertheless, we are constantly surrounded by data. In the claims industry we must innovate and develop in the same manner which will ultimately allow claims leaders to manage from quantifiable data instead of day to day survival.

Source by Ernest B Bray

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