07 Feb The Value of Predicting Claims Litigation with Artificial Intelligence
There is a great deal of information contained within the first notice of loss (FNOL), claims representative notes, interviews, and statements by the insured and claimant. A domain expert can glean a lot from this unstructured data and make effective predictions such as the likelihood of the claim going into litigation and indications of organized activity. Replicating the above process in software is a challenging task. Most machine learning models perform poorly or become biased in the presence of skewed data.
Less than ten percent of a carrier’s claims typically end up in litigation or become extremely severe. However, that ten percent claims have the biggest impact on the company’s bottom line. Accurately identifying those claims early in the process can save the carrier millions of dollars. This requires novel approaches using a combination of various artificial intelligence (AI), natural language processing (NLP), machine learning (ML) techniques and most importantly EXPERT SYSTEMS KNOWLEDGE-BASE.
The Infinilytics advanced analytics solution with artificial intelligence (smartC™) is comprised of several AI solutions, including machine learning, NLP, and Expert Systems. Our Thought Leadership Team has over 60 years of experience in reviewing and investigating thousands of claim files for all types of insurance fraud schemes. Infinilytics leverages the domain expertise into the expert AI systems with the goal of replicating the expert’s knowledge and skills. Infinilytics’ smartC™ captures the expert’s knowledge into its database. The smartC™ solution also learns of new behavior patterns from the corpus of claims using unsupervised learning techniques along with its built-in expert system. This hybrid approach of using machine learning along with expert knowledge base helps smartC™ build a strong context around its analysis and perform accurate predictions like an expert. In our proof of concept, smartC™ was able to predict litigation before the claim actually went into litigation.
Imagine if you could do the following:
1) Predict with a 90 percent accuracy if a claim will fall into litigation upon receipt of the first notice of loss.
2) Take immediate steps to prevent the claim from falling into litigation.
3) Significantly reducing your litigation costs by taking action before it is too late.
4) Keep your customers satisfied with their claims experience, and further increase your book of business.
The Infinilytics Team with their smartC™ solution can help your team achieve these outcomes.