One of the toughest challenges in the financial lending industry is the ability to identify qualified borrowers who will be able to repay their obligations and not default. This task has plagued lenders for thousands of years.
Recently, however, fintech collaborations have made this task significantly easier by expanding the prospective borrower pool to include those who would have previously been regarded as ineligible despite their creditworthiness, due to inherent racial and ethnic biases. Let’s look at how these changes have created a more inclusive lending experience.
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- What Inclusive Lending Means in Today’s Financial Landscape
- How Fintech Is Reshaping Traditional Lending Models
- The Role of Data and AI in Expanding Access to Credit
- Examples of Fintech-Financial Institution Partnerships
- Benefits of Collaboration: Speed, Scale, and Smarter Risk Assessment
- How Fintechs Help Reach Underserved and Underbanked Communities
- Challenges and Considerations in Building Inclusive Lending Networks
- What This Means for the Future of Consumer and Small Business Lending
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What Inclusive Lending Means in Today’s Financial Landscape
According to a study by the Consumer Financial Protection Bureau, applicants in majority nonwhite areas tended to have significantly lower credit scores across the board compared with their counterparts who lived in majority-white neighborhoods.
Inclusive lending means the ability to identify qualified applicants from all races and ethnicities equally, which increases the number of minority borrowers by using all available data to capture a better image of a person’s creditworthiness rather than relying exclusively on traditional factors
How Fintech Is Reshaping Traditional Lending Models
Financial technology, also known as “fintech,” reshapes traditional lending models by including additional datasets. Instead of looking only at a person’s credit score and job history, fintech applications can help provide lenders with a fuller understanding of an applicant’s ability to repay their obligations.
Under traditional systems, the lending process has been marked by exclusivity. Only borrowers with established credit histories and credit scores higher than a certain number could borrow the money they needed. Due to various socioeconomic factors, this artificially reduced the number of successful Black and Hispanic applicants. Through fintech-powered partnerships, this disparity can be resolved by allowing lenders to go beyond outdated metrics and see the bigger picture.
The Role of Data and AI in Expanding Access to Credit
One main driver of the newer, more inclusive model is AI lending, which uses artificial intelligence to examine additional data and make a more accurate determination about whether a prospective borrower should receive a loan.
This additional data includes things like social media activity, utility or streaming bill payments, and more, which provides a clearer picture of a person’s total financial situation. For example, let’s say someone from a minority population makes a Facebook post about the new car they just bought with cash they’d saved up over the past few years, as well as the proceeds of selling their old car.
Neither these savings nor the new vehicle ownership would be reflected under the traditional system. Despite the applicant’s clear ability to save money and make good financial decisions, they would be denied under the old system.
Examples of Fintech-Financial Institution Partnerships
Although banks initially saw fintech as a threat, they quickly realized that a collaboration would be mutually beneficial to not only each other, but consumers as well. A 2019 survey by PricewaterhouseCoopers (PwC) revealed that 42% of financial institutions had some sort of fintech partnership.
These include mobile banking apps, identity protection software, customer experience improvements, and more. Deutsche Bank famously partnered with TraxPay, for example, to create a real-time payment platform for its customers.
Benefits of Collaboration: Speed, Scale, and Smarter Risk Assessment
Among the many benefits of these fintech collaborations are speed, scale, and smarter risk assessment. Unlike normal credit checks that can sometimes take a while, AI-based digital lending checks take a matter of seconds.
It also allows for increased lending scale. Lenders can now reach more qualified buyers and therefore increase revenues while being less dependent on larger clients to keep them afloat.
Lenders also enjoy the benefits of smarter risk assessment and can increase the amount of successfully repaid loans. This helps achieve the necessary balance between providing enough loans to make it financially worthwhile for the lender and anticipating that the money lent will likely be repaid.
How Fintechs Help Reach Underserved and Underbanked Communities
By revolutionizing the lending industry’s understanding of creditworthiness, fintech collaborations make it possible to reach underserved and underbanked communities. Traditional lending methods often create a “Catch-22” situation in which a person cannot borrow money without previously having borrowed money from a similar institution, making it difficult for a person to get the initial approval.
However, by expanding the criteria and better understanding a person’s financial situation, people and communities that would traditionally have been excluded can now have the chance to fulfill their dreams thanks to a business or personal loan.
Challenges and Considerations in Building Inclusive Lending Networks
Unfortunately, the new system of AI lending isn’t foolproof, and there are certain challenges to overcome and factors to consider when building inclusive lending networks.
First, many aspects of AI are still a work in progress. It’s relatively accurate overall but still leaves room for error. Second, some potential borrowers will still fall through the cracks. For example, someone who doesn’t use social media, pays for everything with cash, and lives with their parents might still be rejected, regardless of creditworthiness.
No lending system can ever be perfect. However, AI can close the gaps and make lending more fair, equitable, and inclusive.
What This Means for the Future of Consumer and Small Business Lending
AI lending has forever changed the landscape of consumer and small business lending for both parties. Lenders can have greater confidence in their ability to issue loans to qualified applicants who would have been ineligible under traditional metrics, allowing them to increase their customer base while simultaneously reducing their overall risk.
Potential borrowers can now receive the startup money to open the businesses of their dreams or use their loans for another life-changing purpose, even if they don’t have a perfect credit score — or don’t have one at all. Under the new and more inclusive system by digital lending solutions, both the lender and the borrower benefit.
