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How TPAs Can Use AI to Automate Claim Scoring and Predict Jumper Claims

Regardless of whether you manage claims for a carrier, an insured or a self-insured organization, it all boils down to the same thing: efficient claims resolution. The challenge is meeting everyone’s needs while still fulfilling the necessary but time-consuming tasks of claims administration — and doing so quickly.

That’s why so many best-in-class TPAs are turning to Artificial Intelligence (AI) to help them predict low-cost and high-cost claims earlier in the game. We’ve already discussed the ways AI can help TPAs promote operational efficiency and maximize customer retention, including fast tracking claims; communicating effectively with claimants, clients and vendors; identifying fraudulent claims; and maximizing operational efficiency.

In addition, there are specific ways TPAs can leverage AI to monitor, manage and predict the severity of claims earlier. Doing so can benefit both parties by ultimately helping to resolve claims faster.


The most beneficial ways TPAs can leverage AI in risk management software include:

Automate Claim Scoring and Reserves

By leveraging AI and vast databases of industry-specific, historical data, automating claim scoring and reserve recommendations reduces the effort for the adjuster, achieves far greater accuracy, and minimizes too-frequent changes in reserves.

Monitor and Predict Jumper Claims

Sleeper, or jumper, claims are those that appear to be minor at the beginning and then “jump” around the 90-day mark into high-cost claims that require close management, increased reserves and more resources. Jumper claims are known to account for as much as 40% of insurance losses.[1] The earlier TPAs and insurance companies can recognize them, the better.

TPAs can collect a variety of data to help them understand the likely path of a claim. With predictive AI, however, better-informed and timely decision-making is not only possible, but likely. AI technology allows real-time, continually updated predictive modeling. As the claim progresses and more information is gathered, predictive AI will re-score the claim for its potential to develop adversely, updating the predicted final cost in real time.

When new information comes in, the TPA receives an automated alert, which can help the claims manager to better allocate resources and execute the closure strategy. Identifying opportunities for litigation avoidance typically more than covers the cost of the technology itself.

Next Steps

TPAs are pulled in several directions when in the process of managing a claim. Those who leverage AI to better predict claim outcomes will come out ahead. Claims managers are much better off spending less time doing complicated predictive analytics and instead using their skills for collaboration and interaction, while letting AI do the heavy lifting.

For more information on using AI as a TPA to help improve service and outcomes, contact LESLIE SARGENT, Ventiv’s TPA practice leader.



May 11, 2021

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