Do you know how much money is lost to fraud in insurance?

According to National Health Care Anti-Fraud Association
(NHCAA), healthcare insurance fraud costs more than $68
billion annually. Evidently, the industry is plagued by rising
insurance fraud incidences.

Regulators like California’s SIU regulations contemplate
million-dollar fines on insurers failing to implement anti-fraud
measures. The Department of Health and Human Services
expects to collect a whopping $4.7 billion from insurers post
the related audits.

Consequently, the payer ecosystem is bracing itself up to use
data-driven technology to mitigate these incidences with the
growing domain of “Fraud analytics”. A few people are calling
this “the uberization moment” of the insurance industry, while
others hail it as just another fad in the industry’s evolution.
However, no one is denying this new vision of predictive
reality in insurance analytics is here to stay.

Here’s a sneak peak into Jasper Colin’s latest dive into the
deployment of predictive analytics in insurance, where our
research reveals that predicting bogus claims will save at
least 20% of claim losses for insurers.