The technology breakthrough during the last years have brought an increase in insurance fraud and, as a consequence, they are changing the landscape in the sector. From Pricing Comparison Websites (aggregators), to Telematics and Usage Based Insurance, to Internet of Things, the increasing demand for Cyber Insurance and new Peer to Peer insurance, traditional insurers have to adapt quickly to new trends and compete several times nontraditional firms with big data processing capabilities (e.g. Google and Walmart selling auto insurance in U.S., IKEA selling healthcare insurance).

At the other hand insurers are suffering from fraud costs and as insurance products become more complicated and the channels of interaction with customers and possible fraudsters are increasing, the level of intelligence and automation for tackling insurance fraud overwhelms traditional fraud detection and prevention organizational structures, processes and technological infrastructure.

As an example we can reference the latest report from Insurance Fraud Taskforce of UK Government January 2016 it is estimated that fraud costs 50 UK pounds per year for each policy holder and £3 billion to the UK economy. Further drill down shows that the value of detected fraud is in excess of £1 billion and undetected insurance fraud is estimated to cost more than £2 billion a year! Unfortunately these figures do not sock those who are working in the insurance claims industry.

New data sources provide new fraud indicators

Insurers are used to collect and analyze structured data from traditional information systems like underwriting, policies and claims.

In the new era the fast and efficient utilization of structured and unstructured data from call centers, direct insurance internet sites, mobile apps, social media, telematics, aerial and digital imagery, data sharing in insurance consortium level etc. can make or break an insurer’s operation, business goals for claims fraud reduction and profitability, e.g.:

• Text analytics in unstructured data from call centers can reveal potential fraud behavior in a claims process.
• Event stream telematics data can reveal the true parameters of an accident and provide an detail view of the accident’s scenery.
• Social media data can uncover suspicious customer activity and workers compensation fraud
• Social media data can uncover also suspicious links between connected parties like claimants and others.
• Aerial and digital imagery can evaluate the damages incurred in an area (for crop insurance) or the proximity to risks in a specific area or asset.
• Direct insurance internet sites for spotting out suspicious customer behavior in the application stage, such as manipulating application details to achieve a cheaper quote.
• Price comparison websites (aggregators) are collecting important prospect customer behavioral characteristics again for manipulating applications.
• Data sharing in insurance consortium level can uncover customer link suspicious networks and organized fraud rings.
• Data available in fraud databases and fraud sharing schemes (e.g. MyLicense , CUE in UK )

A modern, insurance fraud combat squad

The shift from a traditional fraud prevention perspective with few experienced claim handlers utilizing brains, memory and some rules based reporting and alerting mechanisms, to a modern organizational  structure with some full time dedicated resources (Fraud Investigation Unit) and a technological infrastructure for big data fraud analytics, in not a “nice to have vision”. A modern, fraud combat squad is the critical factor which will give the competitive advantage to the modern insurer to tackle fraud, increase profitability, bit competition and expand to new business challenges based on a robust and low risk customer base.

A counter-fraud team with an arsenal of modern anti-fraud technology is the only way forward for the insurance sector. New insurance challenges require new plans and fast actions. Data science and big data analytics is nothing to afraid or hesitate for. Insurers are the most mature organizations in that area, taking into account their great actuarial data science history in measuring risk, applying statistics and predictive models with forward looking calculations in all business lines. The new era need is that they apply the same disciplines with and extended umbrella of advanced technological capabilities also in the claims handling and fraud prevention area, which leading and modern insurers already do.

If you are interested in learning how Fraud Analytics can be your additional line of defense helping you tackle Claims and Underwriting Fraud in the digital age you can register for the Insurance Fraud Webinar series. Also for more updates from SAS fraud experts from all over EMEA, don’t miss to subscribe to our twitter list.