Fair and affordable lending for all
According to the World Bank, 1.7 billion, or around 30% of people across the globe lack access to useful and affordable financial services and products that meet their needs.
Access to financial services has been shown to play a huge contributing factor to social mobility and to positive economic outcomes. Those with a basic bank account are more able to apply for credit and savings products, to purchase insurance, to own their own home and are even more likely to be able to access proper healthcare and education. It vastly improves economic outcomes, encouraging entrepreneurialism and boosting consumption.
The global financial inclusion picture has already vastly improved over the past 10 years. Since the last financial crash, an estimated extra 1.2 billion global citizens have gained access to basic financial services, driven in part by the rise of Fintech, putting the overall inclusion figure at around 70%.
Yet, inequality is rife. At 72% for men and 65% for women, the gender gap in bank account ownership globally is huge and hasn’t moved in the past 10 years. Those from poorer households, rural areas and ethnic minorities are also disproportionately underserved.
At the heart of the issue is the way in which providers traditionally determine risk as a basis for granting access to finance. Credit checks pull data from credit bureaus (CRAs), which only look at a very narrow view of an individual. And they don’t just discriminate against bad credit history, but also look disapprovingly at so-called ‘thin credit files’ – a lack of detailed credit history or activity.
Even in a developed nation like the UK, a surprising number of people can find themselves with a thin file, or poor credit history. Migrant workers are one example, but native UK adults can be equally affected if through personal circumstances they’ve been invisible to the financial system most of their adult life, or they fall into low income and minority categories, or tend to use alternative credit products.
Where FinTech alone can’t solve this issue, data can help. Using alternative data sets to credit score individuals – e.g. identity records, property and asset ownership, occupational licenses, public records, business associations and academic achievement – has been shown to dramatically improve credit decisions for the underbanked.
In one US study1, almost a quarter (24%) of consumers were considered ‘un-scorable’ – i.e. CRA data was insufficient to adequately score them for credit products. When re-examined using alternative data however, 86% of the ‘un-scorables’ were able to be scored. And remarkably, two thirds (64%) of them were found to be high scoring, low risk consumers that would make good, profitable credit customers.
Apply this uplift to the global financial exclusion figure, and some 1.46bn people could get access to products and services for the first time, assuming a thin or no credit file is the underlying cause of their exclusion.
In the UK, LexisNexis Risk Solutions research shows some 7.4 million adults (13.74%) have no active bank account and a further 456,000 (0.84%) have no CRA data attributed to them, meaning around 6.6 million people could benefit from alternative credit scoring methods to meet their needs.
The applications and benefits of alternative risk score modelling extend far beyond financial services, too, having the potential to help individuals access a host of products and services from which they’ve been excluded in the past – utilities, car rental and broadband and streaming services providers, to name a few.
It’s becoming clear that a one-size-fits all approach to credit risk profiling is no longer suitable within a modern developed, global economic model. In the same way that customer identity verification is evolving from physical only, to incorporate multi-factor physical, biometric and device-related attributes to build a trusted assured digital identity, so the financial system needs to evolve to incorporate a far wider range of attributes to build a genuine risk picture of customers. Not only does this broader view open up a rich stream of new customers, but it should also help financial service providers and others understand their customers altogether better and be able to offer them more, tailored, appropriate and affordable products.
1: Alternative Data and Fair Lending Whitepaper, LexisNexis Risk Solutions, 2013 https://insights.lexisnexis.com/creditrisk/wp-content/uploads/2013/09/alternative-data-and-fair-lending-wp.pdf
Nina will discuss this topic in more detail during the panel session 'Financial Inclusion, how to unlock digital finance for all' at our Open Finance and Inclusion Summit on 20 April, visit the event website now, to book your place.
To read more from #OpenFinanceInclusion Campaign Week check out our landing page here.