In an age of increasing digitalization of financial transactions, the role of artificial intelligence is set to expand. AI will inevitably merge with financial technologies and services and be applied in a variety of ways, and payday loan companies will be the first to embrace AI, having already had a profound impact on society with the concept of short-term loans.
Readers may be understandably shocked by the idea of payday loan companies using AI. After all, both industries don’t have the best reputations. Doesn’t the use of AI by loan companies mean that people are being “targeted”? Does it mean they’re trying to exploit the most vulnerable consumers? After all, they’re the bad guys, right?
While some payday lenders do have reputation By exploiting people at high interest rates, trapping them in a cycle of borrowing and debt, they also provide a necessary and often Important Services For those who are short of money. And artificial intelligence, although it may eventually Take away some people’s jobsis undoubtedly a good thing in many other ways. For example, it helps democratize knowledge, encourages creativity, makes people more productive, promotes medical progress, and even Fighting sex traffickingand many other benefits.
So we shouldn’t be too surprised to learn that payday loan companies are actually trying to use AI for some good: making their services more accessible, especially to the unbanked, and lowering the cost of borrowing.
Artificial intelligence can improve credit assessments
AI can have a positive impact on payday lending in several areas. First, it can process far more data than traditional data analysis models, including information scraped directly from someone’s smartphone. AI can find credit patterns that traditional credit score-based systems can’t identify, or show whether someone should be rejected despite having a high credit score. Additionally, it can result in significant cost savings because it automates the process of assessing credit, so lenders don’t have to pay salaries to loan officers who traditionally make decisions. As a result, AI-based lending systems can offer loans at lower interest rates while still generating higher profits.
One of the key movers in the AI lending space is Neural Chain Artificial IntelligenceBuilding an advanced, decentralized AI-as-a-Service Ecosystem This helps make AI more accessible to organizations.
The company’s platform provides everything enterprises need, including AI model hosting, integration tools, training, and community-validated high-quality data. It focuses on providing a seamless experience, offering ready-to-use and pre-trained AI models that can be quickly customized to an organization’s specific needs. One of its innovations is an AI model designed specifically to improve credit assessment.
Neurochain AI claims that its credit model enables payday lenders to do many things that American banks want to do but cannot. For example, its AI model enables customers to prove their identity in seconds, so they can join using just their smartphone. They then use the user’s smartphone itself to obtain data that is crucial to assessing whether they are creditworthy.
In this way, Neurochain AI paves the way for payday lenders to safely lend to individuals with no credit history at interest rates that traditional banks cannot match. Furthermore, these payday lenders can do so while making 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 their device), and information about their bill payments, purchases, geographic location, and more.
Traditional lenders tend to use business intelligence software to make decisions. When they use BI software, this means analyzing a customer’s bank records and previous transactions, repayments, etc. However, when lenders use AI software, they no longer need to look back to the past, but can look forward to the future because AI has the unique ability to make predictions based on the data it sees. It can predict what each customer will do based on their similarities to existing loan customers. Therefore, applicants do not need a credit history to pass AI credit assessments.
To use NeurochainAI’s credit risk assessment model, payday lenders simply need to integrate it with a branded mobile app, ideally Android, a more open operating system than Apple’s iOS. The beauty of Android is that it allows lenders to request permission to grab a ton of data from a user’s phone, including their call logs, text messages, call history, emails, and GPS data.
By looking at the contents of someone’s phone, a wealth of information can be discovered about that person and an accurate prediction can be made about their creditworthiness.
Payday lenders can customize NeurochainAI’s model to identify consumers who meet their predetermined lending criteria, and it can make a decision in seconds. In addition, the model is designed to become more accurate over time, learning from its successes and mistakes.
Will AI lending become the norm?
One of the largest AI payday loan operators is a German-based fintech company My purseThe company initially started operations in South Africa and now operates in 11 African markets. It specializes in lending to individuals who were previously unbanked and had no credit rating. It offers competitive interest rates of less than 20% for short-term loans of six months or less, and higher rates of 25% to 40% for longer-term loans. Its loan amounts range from as little as $5 to as much as $5,000.
MyBucks is doing great business. Report The company has loaned more than $200 million so far, with an average loan size of $250. It claims to be profitable, with a default rate of about 7% across all loans.
Another fintech company that has used AI to great success is Branch Officesdownloaded more than 40 million times by users in India and Africa. It offers a wide range of digital banking services to customers and relies heavily on artificial intelligence. It scrapes data from customers’ smartphones, encrypts that information, and then runs machine learning algorithms to decide who is creditworthy and who is not. Once a decision is made, it can immediately process loan applications for successful customers and deposit funds into their accounts in 10 seconds or less. Like MyBucks, it also has a default rate of about 7%.
Both MyBucks and Branch.co are trying to do something that’s impossible in the U.S., where regulations require an explanation for every lending decision. The onerous requirements of the U.S. financial system (which also exist in many European countries) have prevented payday lenders from using artificial intelligence to make smarter decisions about their loans.
But some Western banks are beginning to warm to the idea of AI credit scoring, thanks to pioneering efforts by fintech companies such as ZestFinance, which has developed software that can explain how AI algorithms reach their conclusions.
This year, ZestFinance said it has Significant progresshas helped lenders evaluate more than 39 million loan applications and issued more than $250 billion worth of loans to U.S. consumers since its founding in 2020. The company currently has 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 do 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 clearly explain the reasons for rejection or approval. While it’s most widely used among lenders in the mortgage industry, it’s equally applicable to the payday loan industry.
in conclusion
Artificial intelligence could bring huge advantages to the payday loan industry, improving its operational efficiency, enhancing risk management, and significantly speeding up approval times. The technology is expected to automate many of the tasks traditionally performed by loan officers, which could help reduce the costs associated with borrowing, thereby lowering interest rates for consumers.
As with any industry, AI could be abused by less scrupulous payday lenders, but putting those concerns aside, the integration of AI could do far more good than harm. By adopting AI, payday lenders can help create a more fair, secure, and responsive financial environment.
Disclaimer: This article is for informational purposes only. It does not provide or is intended to be used as legal, tax, investment, financial or other advice.
