The finance industry has long been riddled with criticisms of biased lending. Studies show that minority groups often face discrimination when applying for loans. Usually, this results in higher interest rates or even outright rejection. This way inclusive lending can become another opportunity to differentiate from competitors.

However, such a promising marketing idea of fair lending paired with social care is associated with higher risk.

In this text, we dwell upon the idea of using AI technology to take the advantage of inclusive lending and avoid uncontrollable financial risks. 

The usage of AI technology might initially seem like an easy fix due to its capacity to reduce labor costs, automate processes, and potentially remove the human element of lending by basing decisions on data, not bias. But is all as it seems, and how can companies harness the power of AI correctly to make smarter, more profitable lending decisions?

Why Inclusive Lending Is a Win-Win For All Parties

• For lenders: inclusive lending is a combo of an up-to-date socially-oriented strategy with a great marketing tool

• For borrowers: inclusive lending means a higher chance to receive financing (even for thin-filed borrowers) and is a realistic evaluation of their financial capabilities

• For the whole financial industry: increased access to finance without compromising the financial stability of lenders and borrowers looks like a great match. 

...And Not-Obvious Reasons Why Unfair Lending Is Bad

Less money = lower growth rates. Financial access means economic participation. This reduces the flow of money in the economy, taxes, and more, reducing a country’s overall spending power. 

Increases risk of predatory lenders. Primed to pray on the misfortune of minority groups, predatory lenders thrive in an unfair lending economy. Meanwhile the human cost of predatory lending is estimated at around $1.9 billion to US families.

Stunts small business growth. Small and medium businesses rely on loans to scale. To highlight the value of alternative lending for small businesses, in 2018, big banks approved just 58% of SME loans, compared to the 82% approved by alternative online lenders.

AI For Inclusive Lending: totally helpful or full of hidden pitfalls? 

AI technology uses complex algorithms that allow financial companies to automate and undertake a number of processes. Empowered by Big Data, they can undertake sophisticated calculations and give surprisingly accurate results with a minimum error margin. 

Challenges of AI usage in finance

Critics of the technology highlight the potential for AI in finance to become biased, as it works off the data, it is provided with. Such examples can be seen in Microsoft’s Tay. Other challenges occur when algorithms use faulted data to make conclusions or work in areas where not enough data is available, such as less competitive environments or low-shopping behavior. This can occur in minority groups where not all transactions are made using cash or card. 

A report by the Consumer Financial Protection Bureau (CFPB) stated that 26 million in the US were credit invisible. This was a particular problem for those with Black and Hispanic backgrounds who were 15% credit invisible. Blacks also were noted as having 13% unscored records, while Hispanics had 12% unscored, compared to 7% of whites. This indicates that race plays a factor in credit approval and can include the data used by AI technology to issue loans.

Benefits of using AI for fintechs

Henry Ford once said, “failure is only the opportunity to begin again only more wisely this time.” Recognizing the initial challenges in artificial intelligence technology, we can move forward more fairly and intelligently. By knowing the obstacles, companies can adapt solutions in smarter ways to target and reduce instances of bias in lending. Here are some of the ways AI can be adapted to facilitate fairer lending.

Allowing access to a broader range of financial products

Previously, the variety of lending products on the market was as limited as the number of methodologies used to calculate risk and assess data, which in turn gives information into the types of lenders and products they use. The capabilities of Big Data now allow companies to expand this list, tailoring their services to meet the needs of the actual, not presumed, market. For those who find challenges in accessing credit, this offers the possibility to tailor services and repayment more accurately while lowering the risk for the business.

Automates internal services, allows more client focus

From filling in the application form to managing an account to organizing repayments and calculating risk, AI empowers companies to automate processes, making them faster than ever before. For companies, this allows them to focus on customers more intensely. This can mean everything from consulting on the best loans available for the particular client to ensuring less risk for the company if something is off with the client’s data. 

Marketing in financial services is strongly based on customer-centered concepts, and inclusive lending can become a source of inspiration for a powerful marketing campaign. 

Streamlines the applications process and makes it more accessible

For some from minority backgrounds, the process of applying for a loan itself becomes a blocker. Complicated language and endless forms create inaccessibility, and some give up before completing the very first step. AI-based chatbots can help make the process more accessible by streamlining the application process.

Creates optimization in credit scoring

Credit scoring shouldn’t be a black and white process, but that doesn’t mean it has to be complicated. Correctly implemented and carefully chosen AI technology may help lending businesses optimize their credit scoring process, create tailored loans and provide unbiased scoring free of human factor. This may include optimizing systems related to the risk of default, adding custom repayment rates, or adjusting for the risk of an individual or business. 

Move towards fairer credits

Profit is no longer King. Instead, inclusivity is the way forward in banking. By focusing on sustainable, inclusive lending, led by AI technology, credit providers can access a broader market and provide services to those with lower incomes, minorities, and other marginalized groups in a more responsible way.