Are your adjusters making decisions based on past experience or gut feelings?
This happens because information is often limited and adjusters simply don’t have the time to sift through the data to properly evaluate each individual claim.
But what cannot be done at the adjuster level can be accomplished at scale through data analytics. Analytics can help to flag, process, and route claims in an effort to increase efficiency and reduce loss.
Here are 9 ways that data can improve the claims process:
1. Assigning Claims
You’re going to want your most skilled adjusters assigned to your toughest claims for obvious reasons. But claim value alone is not always the best indicator of difficulty.
Reassigned claims can negatively impact the claim’s duration, settlement amounts, and overall customer experience. Consider if you had the ability to automatically grade and assign claims based on loss characteristics so that you could match it to the adjuster with relevant experience?
2. Managing Caseloads
Not all claims are created equal. Therefore, the number of open claims alone cannot determine the caseload limitations of an individual adjuster. Again, the ability to score open claims based on difficulty can ensure a claims manager can effectively distribute caseloads.
If you want to take this a step further, measuring the capabilities of individual adjusters and pairing that with case difficulty can have a compounding effect.
3. Adjuster Performance
File reviews allow claims managers to assess adjuster performance. However, this process is typically a checklist or ratings based primarily on the process alone. Analysis of past claim results can enable a claims manager to compare the achieved outcomes for similar claims and the adjusters assigned to them.
Combining that data with standard file reviews allows for deeper insights into an adjuster’s ability to both manage the claims process and measure their results.
4. Claim Prevention
Data analysis of past claims can uncover commonalities that lead to loss. By understanding these factors, it’s possible to take preventative actions that reduce the likelihood of a filed claim.
Assume your analysis leads to the conclusion that workers who elect family leave to care for a sick parent have a high probability of filing a disability claim. The introduction of a disability assistance program that aids the worker while on leave can impact their need to file a disability claim.
5. Fraud
Most available fraud solutions are rules-based. The limitation here is that it’s too easy for scammers to manipulate or bypass these rules. With one out of ten insurance claims being fraudulent, it’s important to catch them before a payout is made.
That’s where predictive analytics can save the day. By finding trends and patterns in past cases of fraud, those data points can be used to identify the threat of future fraud.
6. Subrogation
It’s easy for subrogation opportunities to get buried in the caseload. And once a file is closed, it’s easily forgotten.
But the ability to search by keywords and phrases can simplify the process of identifying those opportunities to maximize loss recovery and reduce loss.
7. Settlement
Fast-tracking the claims process can help to lower the cost of claims processing but also increase the likelihood of overpaying.
By analyzing claims history, it’s possible to optimize the limits for instant payouts that can reduce the risk of overpaying.
8. Loss Reserve
Forecasting is essential for predicting accurate loss reserves. By comparing potential loss with similar claims, it can be easier to predict the size and duration of open claims and better prepare for the future.
There is also the ability to better account for natural disasters and seasonality based on claims history.
9. Litigation
The legal fees associate with defending disputed claims can add up quickly. Through analytics, it is possible to calculate the likelihood of a claim resulting in litigation. These claims can then be assigned to experienced adjusters who are able to settle these claims fast and at a lower amount.
The Power of Data
Insight into data can have a significant impact on your claims department through increased efficiency and reduced loss. However, it’s important to realize that the insights you glean from this data are only as good as the accuracy of that data itself. Collecting and managing data appropriately is an important first step.
But with a deeper understanding of your claims process, your customers, and your adjusters, data analytics can truly make a difference in your claims department.
Should you need help servicing your claims, US Claim Solutions is here to help, 24 hours a day, 7 days a week, nationwide.
Email us at customerservice@usclaimsolutions.co or give us a call at (888) 701-1153.
Sources:
- https://www.sas.com/en_us/insights/articles/risk-fraud/big-data-analytics-improves-claims-processing.html
- https://www.linkedin.com/pulse/claims-leadership-data-analytics-claim-process-howard-ehrlich/
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