It’s not news that motorists are hugely motivated by price, when shopping for car insurance. The popularity of price comparison websites attest to this and have made it very easy for consumers to compare and switch providers. However, new research by LexisNexis Risk Solutions is revealing a worrying picture of data manipulation in insurance applications.
This not only renders policies potentially invalid and consumers exposed, it results in losses for insurance providers who may pay claims on policies without ever knowing that the risk was misrepresented.
Motorists are far from complacent when it comes to their insurance. According to our survey of 1,500 motor insurance policyholders, 84% take some time to check what is covered by their policy at the point of renewal and 58% consider adjusting cover at this point. 13% only look at the cost and just 4% let the policy renewal happen automatically.
Considering that 59% of the motorists we surveyed think insurance providers consistently charge too much for motor insurance, it’s perhaps little wonder the majority take some time to check their cover.
However, more alarmingly, seven out of ten of the motorists surveyed in our study admitted that they believe it is acceptable to alter details they provide, in order to manipulate the quote and obtain a lower premium. Consumers may not see it this way, but this is potentially fraud and ultimately leads to higher premiums for everyone.
The influence of Price Comparison Websites
Although motor insurance premiums have fallen in recent months last year’s rises combined with the requirement for insurance providers to confirm last year’s premium with this year’s renewal quote has encouraged a high level of shopping activity. Our research found that 68% shop around for a better quote every time their insurance reaches the point of renewal with the same proportion (68%) buying online.
Furthermore, the vast majority (84%) of respondents used a price comparison website as part of their policy selection process. Even amongst the people who did not purchase cover online, three quarters of those did use price comparison websites at some point in the process. It is also worth noting that 15% of purchases were made through cashback websites.
While some consumers do still value human contact when buying insurance: 24% buy their policy over the phone (a rise of 4% since 2015), including more than one in three of those aged 55 and over, overall the findings reveal the huge influence of price comparison websites in this market.
It is this faceless transaction process that is at the crux of the data manipulation challenges currently being faced by the sector and there is an urgent need for insurance providers to leverage predictive data analytics to help identify possible cases of misrepresentation at point of quote.
The data solution
In such a competitive market, and where consumers are disillusioned over the cost of insurance, insurance providers need to be able to offer accurate, right-first-time quotes. Quoting for the true risk represented by an applicant ensures the policy is written at the right price on day one, bringing the best chance of ultimate conversion. This enhances the customer journey, and in turn helps to retain profitable customer relationships.
Identifying where details may have been manipulated or misstated is clearly a priority within the quoting process, prior to policy inception. To this end, contributory databases have a significant role to play, allowing participating insurance providers to quickly verify details such as No Claims Discount. Public records data is also valuable in supporting the verification of customer details and more recently, contributed policy history data can support a greater understanding of risk at point of quote.
But ultimately what insurance providers need to know is if customers have given different details to different insurance providers to secure a lower premium.
Responding to this challenge, a centralised quotation database was created which now comprises quote data from over 80% of the market. Insurance quotes generated by motor insurance providers and price comparison websites can now be compared with previous quotes provided in the past 90 days, to identify key variables, helping to spot potential fraud or claims risk.
The risk associated with this ‘quote behaviour’ is summarised along with other rating factors including No Claims Discount information and policy history data and delivered directly to insurance providers to help them deliver right first time quotes.
Access to this quote behaviour rating factor has been real step-change for the sector but the next stage in its development is already underway.
Recognising the significant problem of named driver fraud known as ‘fronting’ the insurance providers can now identify the risk of named drivers on policies 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 – again in the 90day window.
These developments are focused on helping insurance providers deliver the most accurate insurance quote to customers and equip them to ask further questions before cover is placed.
While insurance costs have recently fallen, consumer dissatisfaction along with the temptation to manipulate quote information remains a challenge for the sector. The application of data to support accurate and fairer pricing can help address this problem but this needs to go hand in hand with greater consumer education around the risks of quote manipulation.