3 ways machine learning is transforming insurance Posted on : Nov 17 - 2017

The insurance industry is no stranger to machine learning and predictive analytics. In fact, it's arguably the most sophisticated, having pioneered some of the most advanced statistics and modeling techniques more than a hundred years ago.

With mounting pressure from increased competition, a highly elastic marketplace, complex claims and fraud behavior, and a tighter regulatory environment, insurance carriers can no longer maintain a competitive edge without predictive modeling and machine learning.

For smaller companies that may not be investing as heavily in machine learning as some of the larger, well-known giants, it is important to realize how this technology can help improve organizational compliance and cost structures. Here are three practical ways the insurance industry is using machine learning today that can immediately improve business efficiency.

Submission prioritization

Insurers use machine learning to predict premiums, conversion, and losses for the policies that brokers submit based on the data available on the first day. This practice helps underwriters focus on the most valuable business. Detecting good risks early in the process enables insurers to make better use of underwriters' time and delivers a huge competitive advantage.

Fraud detection

Insurance fraud is one of the biggest issues in the industry… and it's escalating. Conservatively, fraud steals $80 billion a year across all lines of insurance (Coalition Against Insurance Fraud). Fraudulent claims are costly, but it is too expensive and inefficient to investigate every claim. Even if possible, investigating innocent customers could prove to be a very poor experience for the insured, leading some to leave the business.

Machine learning enables insurers to sift through claims and identify those that warrant deeper investigation. Once fraudulent claims are prioritized, fraud units can then create a data-based queue — investigating only those incidents likely to require it. The resulting benefits are two-fold. First, your resources are deployed where you will see the greatest return on your investigative investment. Secondly, you optimize customer satisfaction by not challenging innocent claims. View More