Identifying Fraudulent Claims With AI

The Problem

Different government departments earmark large sums of money for welfare and benefit programs. It is a known fact that fraudulent claims cost departments billions of dollars yearly. For instance, fraudulent claims by criminal gangs cost the Department of Work and Pensions in the UK nearly £2.1 billion in 2016. How can emerging technology be leveraged to identify and prevent fraudulent claims?

Solution

Machine learning models deployed on Kranium can analyse huge volumes of historical data to identify patterns in claims that help departments identify fraudulent claims. These models can provide instant inferences and are much faster and efficient that human investigators.

Also, NLP systems can be used to analyse call recordings to identify various aspects about the reporting person (like nervousness) and can flag suspicious reports.

These systems can help governments save billions of dollars in fraudulent claims annually.