CLARA Analytics launched of a fraud detection product for insurance claims

CLARA Analytics, a provider of artificial intelligence technology for insurance claims optimization, has launched of a fraud detection product that leverages the company’s AI platform and large workers’ compensation datasets to increase visibility into suspicious claims.

The new product, CLARA Fraud, provides alerts and data-driven justification for special investigation unit (SIU) referrals.

It builds upon the company’s industry-leading expertise in AI-enabled claims management to analyze millions of case details, billing records, medical transcripts, and legal demand letters.

CLARA will give claim professionals confidence to refer suspicious claims for investigation with limited false positives and uncover fraudulent activity from bad actors across millions of claims.

CLARA Analytics launched of a fraud detection product for insurance claims

Fraud continues to be a heavy burden on employers and insurers. The National Insurance Crime Bureau (NICB) estimates that workers’ compensation fraud costs the insurance industry over $30 billion annually in the United States.

The Coalition Against Insurance Fraud suggests that about 1-2% of all workers’ compensation claims are fraudulent, although the financial impact is disproportionately large.

Recently, law enforcement organizations have published even higher rates, estimating that 10-30% of workers’ compensation claims have elements of fraud.

The company’s CLARAty platform uses machine learning, predictive AI, natural language processing, and generative AI (GenAI) to power a suite of products aimed at improving efficiency and accuracy in claims management.

Heather H. Wilson, Chief Executive Officer at CLARA Analytic

The workers’ compensation industry has a significant gap in fraud identification capabilities. CLARA Fraud mines workers’ compensation claims data to spot behavior that wouldn’t otherwise be apparent

Heather H. Wilson, Chief Executive Officer at CLARA Analytic

“Today, for example, most individual adjusters can only see one or two claims from the same attorney at the same time. Our platform looks for patterns and clusters of abuse across a very large dataset, so it has the potential to discover suspicious patterns that would otherwise remain hidden.”

CLARA analyzes a wide array of factors, including servicing locations, claimants having multiple claims open at the same time, the same attorney working similar claims, and even exaggerated claims. The factors not only identify potential network fraud but also assist adjusters in justifying referrals to the SIU.

CLARA Fraud is different from competitive products in several important ways. Foremost among these is the extraordinarily large body of data available for analysis.

The new product examines the behavior and relationships between medical providers, legal counsel, and claimants across millions of workers’ compensation claims.

“Over the past 10 years, CLARA has consistently delivered outstanding ROI for our workers’ compensation customers, often exceeding 500%,” added Wilson.

“The new product takes that a step further, helping carriers to significantly reduce losses on fraudulent claims that were previously difficult to identify. The product enables insurers to identify previously undetectable fraudulent claims and also gives the adjuster the confidence to refer the claims to investigators without the fear of false positives.”

By taking full advantage of CLARA’s industry-leading platform and subject matter expertise, the new product is capable of analyzing and monitoring claims at a level of detail that has never previously been possible.

Where other fraud detection solutions focus on scraping publicly available data, CLARA’s AI digs deep into detailed claims documents to look for suspicious markers, using supervised and unsupervised learning to enhance its accuracy.

CLARA helps carriers to make sense of voluminous information, streamline claims management, improve medical outcomes, and reduce administrative burdens for adjusters.

Peter Sonner   by Peter Sonner