Machine Learning Programs has won ‘Best Use of Technology’ in this year’s Broker Innovation Awards, for its Propensity to Defraud model.
Fraud is an enormous problem for the insurance sector – it drives up claims costs, eats into staff time and leaves honest customers losing out as it drives up premiums whilst affecting insurers’ bottom lines.
The ABI reported that, in 2022, insurers detected 72,600 dishonest insurance claims valued at £1.1bn. Importantly though, the body estimates that a similar amount of fraud goes undetected each year.
Identifying potential fraudsters at quote stage could save the industry millions and free-up budgets to support innovation, customer care and risk management. As intermediaries, brokers are at the vanguard of preventing fraudsters from getting into the insurance system and those able to block fraudsters at earliest stages are favoured by their insurance partners.
The Propensity to Defraud model helps brokers identify potential fraud quickly and ensures staff can save and prioritise time more effectively.
The product was originally designed for Adrian Flux to support Bike, Home and Commercial vehicle, and is now available for the wider market and adapted for multiple business lines.
Lee Westwood, Manager at Adrian Flux said: “We have been delighted by just how effective Propensity to Defraud has been for us. It ensures our teams can focus on helping the business to grow rather than spend time on administrative fraud checking tasks. It also means our book is cleaner and our insurers are happier.”
Gerry Bucke, Underwriting and Sales Manager at Adrian Flux, said: “Propensity to Defraud has helped our business save around £100,000 a year in person-hours. Working with MLP has been a really exciting, innovative process. What they are able to do with data and the intelligence their machine learning models bring within milliseconds is helping transform our business operations and the strength of our insurance books.”
