Busting Ghost Broking with Analytics

Auto insurance is a sector that is inundated with fraud, and one of the commonest tactics used by swindlers is 'ghost broking'. Unauthorized insurance agents use falsified details and fraudulent policies to set up low premiums for their customers, causing the insurance industry major losses each year. For instance, a broker may fake the birth date of a 1990 born driver as 1963, thereby turning a 24 year old into a 51 year old driver who is entitled to low premiums.

One way to beat ghost broking is to employ smart statistical analysis methods such as cross referencing date of birth, marital status, and important dates such as when the driver's license was issued. Policy records and quote records should also be checked and addresses should be verified to see if the same address has been used to obtain several quotes. Suspected cases of ghost broking can be referred to a team of special investigators for a thorough enquiry.

An example of using antifraud analytics was on show when WNS was called in to identify suspect ghost brokers as part of an insurance analytics initiative. The teams reviewed policy and quote data from a top insurer's database, and cross referenced the data with a motor insurer database and a ghost broking database. WNS checked policy details and exceed claims, and even issued letters and fielded complaint calls to address the issue. Following this, WNS handed over names of suspected ghost brokers to a police investigative team and enabled the client to cancel associated policies or allow them to lapse.