Published by Gary Roy Markham on Jan 27, 2021
Time is incredibly important when it comes to complex claims management. With more time, insurers can devise better strategies for claims litigation, as well as gain the flexibility needed to handle difficulties within the litigation process. In turn, insurers can better execute their claims litigation plans.
Identifying the severity of a claim before it is litigated can save a significant amount of time. Furthermore, this kind of knowledge allows insurers to have an increased amount of control over the litigation process. This control extends to jurisdictional selections, dispute durations, and many other pivotal decision points. If the claimants are the first to make a decision, they then achieve the space necessary to dictate the litigation narrative.
An early warning system can ensure that insurers do not shoulder the costs of a claimant-controlled case. These kinds of systems can help insurers measure the risk factors of complex claims, which can help them determine facts of the case before the claimants do. Early warning systems also prime insurers to safeguard evidence and correct any errors. They can also obtain primary access to witnesses and bring in external counsels as early as possible, if needed. These kinds of defensive strategies often convince claimants to simply abandon their litigation pursuits. Regardless, early warning can improve insurer’s claim outcomes dramatically.
Insurers typically struggle to identify heavy-impact claims before the costs are accrued, largely because they rely on their memory to identify such claims. Fortunately, artificial intelligence-based software systems can easily pinpoint these claims, allowing insurers to handle them more effectively.
A predictive model can sort through an organization’s entire claims database and report on key insights about trendlines and risk. These insights can then be used to flag high-risk/high-complexity claims and their trajectories. Then, insurers can make more effective plans to deal with those claims.
Predictive models are built out with artificial intelligence and machine learning, and are fed data from past claims and their outcomes. This allows the model to relate claim trends to costs and litigation durations. The model can then be presented with new claims information to predict likelihoods and probabilities.
Like any predictive analytics system, claims-focused models cannot predict the correct outcome for every single claim. However, predictive analytics systems do have a better prediction rate than human claims adjusters. The best approach is to empower human adjusters with the insights of a predictive model, ensuring a balanced human and machine mix.
Apart from claim costs, predictive models can help insurers in predicting:
These predictions can help insurers manage their resources more effectively.
Early warning systems can help insurers construct effective claims defense strategies. AI- based predictions can do more things for insurers than just identifying heavy-impact claims. The software can also assist insurers with planning, budgeting and settlement strategies.
Early warning systems powered by AI-based predictions can help insurers with:
AI-enabled tools such as ExpenseCore Legal can analyze new claims and past claims histories to inform predictive models, which can be very beneficial for insurers looking for an edge in the market. Early knowledge of claims severity can reduce the claims cycle times for insurers, as well as dramatically impact incurred ALAE and indemnity. Faster claims cycles also help drive down labor costs while keeping customers happy with the speed of claims handling.
AI-based predictions facilitate quick claims closure for insurers through early settlement, and if that’s not possible, then they help insurers achieve the best possible outcome in litigation. With this, insurers can reduce their allocated loss adjustment expense (ALAE) per claim by up to 10%. ALAE is the aggregation of total expenses incurred by insurers during claims defense, including fees for legal representation and private investigators, amongst other things. Therefore, avoiding litigation whenever possible works in insurers’ favor when it comes to keeping claims costs down
Early claims settlement achieved with AI can also reduce indemnity for insurers, with claimants accepting a lower payout during an early settlement than if it were to go the distance in litigation. Additionally, the quick closure of claims can also mean that insurers may process more claims each year.
Insurers should remember that early warning systems do not guarantee successful claims outcomes. Instead, they allow the balance of power to shift in favor of insurers. Furthermore, the cost savings potential of early warning systems for insurers are endless.