Data is the WMD against insurance fraud
On 20 August 2012 I was fortunate to attend the Discovery Invest Leadership Summit. One of the dynamic presenters was ex-Tesco PLC chief executive, Sir Terry Leahy. Leahy took the reins at the London-listed retailer in March 1997 – and by the time he vaca
Data and the smart application of data were among the topics discussed at the FAnews Data is Priceless seminar held in Johannesburg, 22 October 2012. Event sponsors TransUnion, Lightstone and STRIDE took to the podium to share the latest developments in the complex field of insurance data as well as how data can assist insurers in reducing fraud. Guest speakers from the South African Insurance Crime Bureau (SAICB) and the South African Insurance Association (SAIA) were also on hand to update attendees on recent initiatives at their organisations. First to take the floor was CEO of TransUnion Credit Bureau, Geoff Miller.
A company that understands big numbers
TransUnion has plenty of experience with the ‘big numbers’ that confront 21st Century financial services businesses. And by ‘big numbers’ we do not mean revenues and turnovers; but transaction volumes and ever-expanding databases. The group has a presence in 32 countries and handles the credit data and associated information of some 500 million consumers worldwide. South Africa – with 46 million consumers – is the firm’s second largest region outside the US. The firm’s unique local data assets include details of 19 million credit active consumers, 1.5 million active businesses, a database of handset and SIM-card IDs, and a shared forensic database where firms can update data of confirmed and suspected fraud…
Data assets in the insurance space include a medical schemes transaction database and the centralised Insurance Data System (IDS) managed in partnership with SAIA. IDS stores short-term policy and claims information to provide a single integrated view of policyholders. TransUnion also maintains more than 13 million vehicle profiles to access and verify a vehicle’s details and existence, and deliver solutions built on current, accurate and reliable vehicle data – something of great interest to the short-term motor industry. Miller says the group holds approximately 16.8 million VIN records as well as 6.3 million unique vehicle valuations and 2.8 million vehicle finance deals. “When you are dealing with this amount of data, how you validate it and ensure its integrity is absolutely critical,” he says.
Inaccurate data a nightmare for local insurers
If insurers want to tackle the scourge of insurance fraud they will have to ensure the timely and correct capture, validation and reproduction of client data – across the product lifecycle. “South African insurers do an extremely poor job of capturing data such as VIN and Engine numbers,” observes Miller. “Financial institutions, on the other hand, struggle with registration numbers”. He backed up this observation with some shocking statistics. Of the 7.8 million short-term motor claims in TransUnion’s database only 43% had valid VIN numbers… And although this reduces to 38% with some minor tweaks it still means that 4.9 million claims are processed without a valid VIN. Six million claims have no Engine number and some 316000 no registration number!
Why should insurers care? “The more data points you capture the more fraud you detect and the better you underwriting,” he says. “It is therefore critical that before an insurer allows data into its system the proper validations have been put in place. Each and every industry stakeholder must be vigilant about what data they let in”. The best way to address data quality is to make it a business priority and senior executives at insurers should take more interest in protecting their valuable data.
Bad data drives up costs and fraud risks
There is a reason why statisticians use the phrase “rubbish in; rubbish out”. The fact is poor data drives up legal costs and increases the risk of fraud. Incomplete data is a problem too. “Many local insurers are guilty of underwriting at claims stage,” says Miller. He believes that the introduction of the Treating Customers Fairly (TCF) regime will force insurers to improve their data validation at point of sale… Insurers will no longer be able to defer finding out about a policyholder’s prior claims until claims stage because such oversights will be looked on extremely negatively.
It is difficult to put a number on the fraud afflicting the South African insurance industry. Assuming 20% of claims have an element of fraud we are dealing with a very large number indeed. “The amount of fraud in South Africa is overwhelming,” notes Miller. He adds that the frightening thing about fraud is “you don’t know what you don’t know”. The bottom line is that inaccurate data increases the risk of making incorrect underwriting and claims pay-out decision… And inaccurate controls and reporting make it extremely difficult to run a successful and profitable operation.
Fixing the data problem
The solution to data integrity issues is for industry leaders to make data quality a priority. Businesses across the financial services sector should conduct extensive audits to find out how ‘bad’ data is getting into their systems and subsequently root out the causes. “You must align people and processes, give your staff the tools to ensure data quality and clean up any legacy data flaws,” says Miller.
Clean data has major benefits for any organisation. It helps you to make decisions quicker, be more sophisticated about these decisions, and drives cost efficiencies. A popular method in quoting and claims processing is to make use of pre-populated forms. Miller uses the new business quotation process as an example of how sensible data management can save time and free up resources. “The average short-term insurance quote takes between 30 and 45 minute to process,” he says. “Imagine the time and costs savings if you can pre-populate driver and vehicle identification fields, for example”. By pulling in clean and accurate data from external sources you make it easier on both the client and agent while eliminating so-called “fat finger” mistakes.
“If you apply data validation and ensure quality data on the front-end you will reduce data handling time and be more efficient when quoting, underwriting and processing claims,” Miller concludes. “Unless there is an attitude shift with regards data quality nothing is going to change”.
Editor’s thoughts: Based on my attendance at Momentum’s recent Myriad / Multiply launch the pre-populated data idea is catching on at our leading insurers. Smart data management will certainly free up financial intermediaries to spend more time doing what they do best – giving advice. Are you satisfied with the accuracy of your client data in the hands of insurers? Please add your comment or send it to [email protected]
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