Articles - Connecting the dots to identify Named Driver Fraud


As motor insurance costs have continued to rise, shopping around for cover is not just part for the course, it’s positively encouraged as insurance providers are now obliged to confirm last year’s premium with this year’s quote. The average motorist will normally obtain 4 or 5 quotes for their insurance.

 By James Burton, Director of Product Management, UK and Ireland, LexisNexis Risk Solutions
  
 The ease with which consumers can obtain quotes online has been good for consumer choice, good for the buying experience and good for lowering acquisition costs for insurance providers. But this faceless way of obtaining insurance cover has also created the problem of data manipulation and ‘named driver’ fraud.
  
 29% admit to fronting
 In our own survey of motor insurance policyholders , 29% of people admitted to ‘fronting’, i.e. naming someone else as the main driver on their insurance policy to reduce their premiums, potentially invalidating their cover. 43% stated they believe it is acceptable to misrepresent data in some form in their insurance application or claim and 55% of drivers believe an insurer should still pay out on a claim, even once it has been found to contain false information.
  
 Fronting is a particular problem amongst young drivers who tend to pay the highest premiums due to their perceived risk.
  
 Ghost brokers
 In other cases, the manipulation of the data is an act of organised fraud by ‘ghost brokers’. In a campaign launched by the City of London Police’s Insurance Fraud Enforcement Department in February this year it was revealed that ghost brokers have defrauded the public of £631,000 over the past three years. One of the tactics used is falsifying details in an insurance application to bring the cost down. In some cases ghost brokers will add named drivers to a genuine policy without the policyholder being aware.
  
 Understandably, identifying when and how data has been manipulated at point of quote and identifying named driver risk has been a key focus for the insurance sector over the past few years. No insurance provider wants to be in the position of having to tell a parent that their son or daughter’s car insurance is invalid following an accident and all insurers have a duty to protect their honest policy holders from the costs associated with fraudulent activity.
  
 Database of insurance quotes
 The solution started with one centralised database which records insurance quotes generated by motor insurance providers and price comparison websites, the data provided for those quotes (name, DOB, address, vehicle information, named drivers, past claims and so on) with the ability to match, compare and identify manipulation of data.
  
 For the last couple of years, the quotation database has enabled insurance providers to see if the customer had obtained a price previously via a price comparison website and whether the details matched those provided for any previous quote or quotes in the past 90 days. What it did not do is directly identify the risk of named drivers on policies.
  
 New attributes to determine named driver risk
 The next step has been building named driver attributes based on patterns of behaviour. This is achieved by connecting different quotes by the same person or for the same address or the same vehicle, identifying where data may have been manipulated for named drivers and the time span in which this activity took place in the 90 day window.
  
 The process starts by looking at the surname of the proposer to see if it is different to the named driver. A potential fronting indicator could be where the individual has appeared as the person taking out the policy for one quote then appeared as a named driver on a separate quote for the same vehicle. The following factors would then be verified and combined to provide a risk assessment of the named driver or drivers as an addition to the risk assessment of the main driver.
  
 Is the surname of proposer equal to the surname of named drivers?
 The number of drivers and how this changes through the quoting journey
 Potential same family relationships between proposer and named drivers
 Maximum/minimum of named drivers who all have the same surname as the proposer
 Maximum/minimum of named drivers who all have different surnames as the proposer
  
 This knowledge enables insurance providers to ask the right questions at the right time, prior to policy inception to help determine if that risk is right for their business and to identify possible cases of fronting.
  
 By looking at how things change in the quoting journey, named driver attributes are going to bring more accurate pricing for insurance providers and peace of mind for consumers too.
  

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