In a day and age where our financial transactions are increasingly done digitally, the role of artificial intelligence is sure to expand. AI will inevitably merge with financial technology and services and be used in a myriad of ways, and payday loan companies, which have already had a profound impact on society with their concept of short-term loans, will be among the first to embrace it.
Readers might be forgiven for being alarmed by the idea of payday loan companies using AI. After all, both industries have a somewhat questionable reputation. Doesn’t the loan companies' use of AI mean people will be “targeted”? Does it mean they are trying to exploit the most vulnerable consumers? After all, they’re the bad guys, right?
While it's true that some payday lenders have a reputation for exploiting people with high interest rates, trapping them in a cycle of borrowing and debt, they also provide a necessary, and oftentimes vital service to people who are short on cash. And AI, although it may end up taking some people’s jobs, is undeniably a good thing in many other ways. For instance, it's helping to democratize knowledge, encourage creativity, make people more productive, advance medicine, and even combat sex trafficking, among many other benefits.
And so it shouldn’t be that much of a surprise to learn that payday loan companies are actually using AI to try and do some good, making their services more accessible, especially to the unbanked, and lowering the costs of borrowing money.
AI can improve creditworthiness assessments
AI can have a positive impact on payday lending in several areas. For one thing, it can process vastly more data than traditional data analytics models can handle, including information that’s scraped directly from someone's smartphone. AI can find patterns indicating creditworthiness that traditional systems based on credit scores wouldn’t identify, or alternatively show if someone should be declined, despite having a higher credit score. Moreover, it enables significant cost savings, as it automates the process of assessing creditworthiness, so there’s no need for lenders to pay salaries to loan officers who traditionally make the decisions. So AI-based lending systems can offer loans at lower rates, while still driving higher profits.
One of the key movers in the area of AI loans is NeurochainAI, which is building an advanced, decentralized AI-as-a-service ecosystem that helps to make AI more accessible to organizations.
The company’s platform provides everything a business needs, including AI model hosting, integration tools, training and high-quality data validated by its community. It’s focused on delivering a seamless experience, offering ready-to-use and pre-trained AI models that can quickly be customized to the specific needs of organizations. Among its creations is an AI model that’s specifically designed to improve credit assessments.
Neurochain AI claims that its creditworthiness model enables payday lenders to do things that many U.S. banks would love to do, but cannot. For instance, its AI models enable customers to prove their identities in seconds, so they can be onboarded using only their smartphone. Then they tap the user’s smartphone itself for data that’s crucial in assessing whether or not they’re creditworthy.
By doing this, Neurochain AI is paving the way for payday lenders to safely lend money to individuals with no credit history, and so at rates that few traditional banks can compete with. Moreover, those payday lenders can do this while still generating a healthy profit.
Why is AI better than BI?
NeurochainAI’s credit risk assessment model is based on an engine that carefully analyzes each customer’s smartphone bill payment history, bank account history (if the user has a banking app installed on the device) and information about their bill payments, purchases, geolocation and more.
Traditional lenders tend to use business intelligence software to make the decisions. When they use BI software, it means analyzing the customer's bank records and previous transactions, repayments and so on. But when a lender uses AI software, they no longer have to look backwards – instead they can look forwards, for AI has the unique ability to make predictions based on the data it sees. It can forecast what each customer will do, based on their similarity with existing loan customers. So the applicant doesn’t need a credit history to get past an AI creditworthiness assessment.
To use NeurochainAI’s credit risk assessment model, payday lenders can simply integrate it with a branded mobile application, ideally for Android, which is a more open operating system than Apple’s iOS. The great thing about Android is that it enables lenders to ask for permissions to scrape the user’s phone for masses of data, including their call histories, text messages, call logs, emails and GPS data.
By looking at the content’s of someone’s phone, it’s possible to discover a lot of information about that person, and make an accurate prediction as to their creditworthiness.
Payday lenders can customize NeurochainAI’s model to identify consumers who meet their predetermined loan criteria, and it can make a decision in seconds. What’s more, the model is designed to get more accurate over time, learning from its successes and its mistakes.
Will AI loans become the norm?
One of the biggest AI payday loan operators is the Germany-based fintech MyBucks, which began its operations in South Africa and now operates in 11 African markets. The company specializes in making loans to previously unbanked individuals that don’t have a credit rating. It offers competitive rates of less than 20% for short-term loans of six months or less, and higher rates of between 25% to 40% for longer durations. Its loans range from as little as $5 to a maximum of $5,000.
Business is going well for MyBucks, which reports that its current loan book stands at over $200 million, with its average loan being $250. It claims to be profitable, with a default rate of around 7% on all of its loans.
Another successful fintech leveraging AI is Branch.co, which has been downloaded more than 40 million times by users in India and Africa. It offers an extensive suite of digital banking services to customers, and it leans heavily on AI. It scrapes data from customer’s smartphones, encrypts that information and then runs machine learning algorithms on it to decide who is, and who isn’t, creditworthy. Having made a decision, it can immediately process successful customers' loan applications, and deposit the funds in their accounts within 10 seconds or less. Like MyBucks, it too has a default rate of around 7%.
Both MyBucks and Branch.co are doing something that wouldn’t be feasible in the U.S., due to its regulations that require an explanation for each loan decision. The overbearing requirements of the U.S. financial system, which are also present in many European countries, prevents payday lenders from utilizing AI to make more intelligent decisions about their loans.
Some western banks are warming up to the idea of AI credit assessments, though, thanks to the pioneering efforts of fintechs like ZestFinance, which has created software that can explain how AI algorithms come to the conclusions they make.
This year, ZestFinance said it has made significant progress, helping lenders assess over 39 million loan applications since it was founded in 2020, resulting in over $250 billion worth of loans being handed out to U.S. consumers. It now counts more than 175 customers nationwide, ranging from small credit unions to the largest banks.
The company doesn’t create AI credit assessment models itself. What it does is provide AI model explainability technology, which essentially reverse-engineers the decisions made by third-party models. It can then generate a report for each AI-processed loan application, and show clearly why it was rejected or approved. Although its most widely used by lenders in the mortgage industry, it’s just as applicable to the payday lending industry.
Conclusion
AI can provide significant advantages to the payday loan industry, improving its operational efficiency, enhancing risk management and dramatically speeding up approval times. The technology promises to automate many of the tasks that are traditionally performed by loan officers, which can help to reduce the costs associated with borrowing, resulting in lower rates for consumers.
Just as with any industry, there may be potential for AI to be abused by less scrupulous payday lenders, but those fears aside, its integration will likely result in far more positives than negatives. By adopting AI, payday lenders can help pioneer a more equitable, secure and responsive financial environment.
Disclaimer: This article is provided for informational purposes only. It is not offered or intended to be used as legal, tax, investment, financial, or other advice.
