In emerging economies, many borrowers lack any kind of credit history, making it almost impossible for lenders to a build a reliable picture of a prospective borrower’s creditworthiness. For underbanked populations, this absence of data deprives individuals of much-needed credit.
So how can digital lenders in emerging economies like Nigeria and the Philippines clear this hurdle? The answer lies in alternative data.
What is alternative data?
Alternative data goes beyond the data typically found in a credit report.
Instead of relying on traditional sources such as credit history, loan repayments, and debt to build a picture of a borrower’s creditworthiness, alternative data gives lenders the opportunity to create a credit scorecard using non-traditional data.
Lenders can instead use a borrower’s rental bills, income, payments for utilities, bank statements, and even information gleaned (with permission!) from their digital footprint and social media to get an idea of an individual’s ability to make regular loan repayments.
They can also gather data from alternative types of credit more common in emerging economies, such as buy-now-pay-later, which has grown enormously in popularity in Africa and Asia over the last few years, and may provide a valuable alternative “source of truth” to lenders.
And because it is not included in a typical credit report, lenders can give as much weight to alternative data as they wish, adding more flexibility to the credit scoring process.
This varied data helps lenders generate a more holistic picture of a borrower’s creditworthiness and ability to make loan repayments without being limited by a lack of traditional credit history. In this way, it can significantly raise the likelihood of a loan approval.
Why is alternative data important?
Globally, there are perhaps 1.7 billion people without access to financial services, mostly in rural areas in emerging economies. With no financial history to call upon, this makes credit scoring almost impossible for lenders operating in these markets.
Poor financial inclusion means most borrowers do not have any proof of income, payment, spending, or debt. This puts lenders at risk of defaulting from exposure to bad debtors, and borrowers in danger of falling prey to cowboy lenders.
As a result, tech-enabled lenders are increasingly investing in advanced loan management platforms that allow them to access, gather, and analyse alternative data about their customers’ behaviour.
Data analysis has enabled lenders to gain a holistic understanding of customer behaviour, giving them a new vector for credit underwriting and monitoring.
Pulled continuously from various sources, this data also provides a real-time picture, so lenders can quickly assess the creditworthiness of a customer based on their spending and borrowing habits.
Not only does this help lenders make smarter decisions, reducing their risk of default, but it also increases the fairness and accuracy of credit reports, providing much-needed access to credit for some of the world’s most underbanked communities.
Are there concerns about alternative data?
There are, inevitably, concerns about the use of alternative data. In particular, some borrowers and regulatory authorities have raised the alarm about the potential misuse of personal data, especially that gained from borrowers’ social media accounts.
Indeed, in Nigeria, concerns about data private recently led Nigeria’s central bank to ask lenders to adopt a common standard to share authorised consumer data with third-party firms, including financial technology and e-commerce companies. This has been designed in part to prevent predatory lenders from using personal information to harass and threaten borrowers.
Lenders must take data protection into their own hands by underpinning their data strategy with a robust technology platform that allows them to collate, share, and report their data according to national and international standards.
But this must be supported by government regulations that are both strident enough to protect consumers, and flexible enough to allow digital lenders to operate nimbly and effectively.
The promise of alternative data.
Adopting alternative data would give hundreds of millions of people access to credit. This is transformative, not just for those individuals, but for the digital lenders that serve them.
However, using alternative data requires the right technology platform. While digital lenders are already tech-enabled, do they have the best tools for the job?
Systems like Oradian’s digital loan management and core banking platform are designed to enable smart loan decisioning by providing not only in-built data gathering capabilities, but also through API connectivity with third-party systems.
By leveraging this technology, lenders can gather the data they wish and make accurate, timely reports about potential and existing loan customers, substantially improving their loan decisioning.
In this way, they can provide valuable access to credit for millions of underbanked people, enriching individuals and communities, and also enabling their businesses to grow and scale and reach new customers.