Consumer attitudes to data sharing are changing
In this age of diminishing brand loyalty, the survival of consumer credit providers hinges on two things: their ability to differentiate and to exceed their customer expectations. Data holds the key to both. Creditworthiness assessments are, of course, the
starting point for lenders’ use of data. But thanks to the increasing variety of data and available data sources lenders can now go much further, generating customer insights that open the door to all manner of tantalising new activities, that enhance up and
cross selling, power product diversification and opening new markets by enabling, for example, credit to be granted to applicants who would previously have been excluded.
With data such a valuable commodity, lenders should welcome the news that consumers are increasingly willing to share it. Research into UK attitudes to unsecured credit shows that only 18% of credit applicants still think that a loan application asks too
many personal questions. Consumer confidence is also growing in how lenders use data, and where they collect it from. Half of all consumers, for example, are now happy for a lender to consult their social media channels to help inform a credit decision - a
figure that rises to 58% for the millennial generation. Times are indeed a-changin’.
Put simply: the new data-driven lending economy is a big opportunity for lenders to make better decisions, attract more customers and broaden their base.
Analyse this, that or the other?
Where data collection is concerned, however, just because you can doesn’t always mean you should. While consumers might be willing to offer more, lenders need to evaluate carefully whether requesting new information will add tangible benefit. Social media
for example, is a window into a consumer’s personal lifestyle – their job history, likes and interests. This
could be indicative of financial stability/ responsibility, equally it might not. This example poses broader questions: is social media data a genuine and reliable representation of an applicant? If not, should it be used as a factor in credit decisions?
While half of those surveyed by Equiniti said they would be happy for social media data to be integrated into credit applications, over a third of the market remains resistant. This suggests that lenders need to tread carefully; merely posing questions could
turn applicants away.
Making smarter use of more conventional data sources is a safer bet. Through open banking APIs, for example, lenders can now access (with consent) an applicant’s detailed payment history (including utility and rental payments, for example) – data that is
likely to be far much more valuable for assessing ability and willingness to repay.
Fair exchange is no robbery
It’s important also to note that an open data culture doesn’t equate to a free-for-all for lenders – consumers expect a reward in return. The ‘you scratch my back, I’ll scratch yours’ sentiment has been successfully embodied by other financial markets -
‘black box’ telematic devices have revolutionised segments of the car insurance market, for example, where policy holders consent to the collection of driving data in return for lower premiums. In consumer credit, the notion appears also to hold sway: 63%
of Equiniti’s respondents said they would happily share more data if it meant they were offered a lower interest rate on their loan. More personalised loan products are fast becoming the trend, and it’s easy to see why.
Pinpoint accuracy requires both flexibility and technical prowess
Identifying gaps where more data is needed, and incentivising consumers to help lenders plug them, is also important. But creating real value comes as much from the analysis and interpretation as the collection. The ability to identify trends and generate
insights that can be used to achieve differentiation and deliver better customer experiences is the key to success in an increasingly overcrowded marketplace. While this is a resource intensive task for lenders, automated technologies and APIs are already
making life easier, for example, by matching an applicant’s data with a market-wide panel of loan scorecards to match them to the best product for their financial circumstances. Having a lendtech infrastructure like this in place, one that delivers the technical
agility and tools needed to integrate with new data sources as they become available, is crucial to freeing up lenders’ time so that they can focus on using data insights to create the products that strike the right balance for their businesses and their customers.