Technology Transformation in Banking for Wider Credit Access

It goes without saying that traditional banking is a cornerstone of the global economy. In an era of technology transformation, though, banks face unprecedented competition from fintechs and other market players moving forward in great strides with technology behind them. For decades the banking system was seen as innovative because it adopted the best technology available, but with the arrival of fintechs and neobanks many of its processes, effective as they are, can now look slow and in some cases outdated.

To stay relevant and competitive, banking institutions need to speed up their adoption of advanced technology, especially in credit analysis, a process at the center of every lending decision. Credit analysis is how you evaluate a customer's ability to repay a loan or a credit line. Traditionally it is slow and prone to error, which costs business opportunities, extends credit to high-risk customers, or declines good potential customers.

Technology such as the uFlow decision engine opens the door to unbanked customers who do have a repayment history, by connecting to a wide range of data sources. Once that information is queried, applicants can obtain a card or a bank loan and step into the formal economy. Santiago Etchegoyen, CTO and cofounder, explains: "For years we have heard the phrase 'the first filter for the product is the door,' and in traditional banking that is how it has worked for decades. Someone walks into a bank, sees how polished, how structured, how elegant it is, and thinks: 'they are going to turn me down here.' On top of that, banks have chosen to focus on people with a banking record, and there is an enormous number of creditworthy borrowers who pay on time outside the banking system. Today, thanks to technology, that can change."

This is an opportunity for banks, because they can offer financial products based on each segment's ability to repay, drawn from how those customers have behaved at other institutions, rather than requiring a credit history at a bank. In Mexico, for example, carmakers extend credit to informal workers or "paisanos" without looking at their banking record or immigration status, and instead analyze only their repayment history at any institution.

At uFlow, we give banks automated access, in under a second, to commercial reports and to every kind of external and internal data source carrying data on these segments, because the decision engine connects via API to any data source or credit bureau. With advanced algorithms, the option to incorporate artificial intelligence models and the ability to connect multiple data sources, the risk decision engine analyzes large volumes of information in real time, predicts each applicant's credit risk and returns an approve or decline answer in seconds.

Using the rules engine, banks can identify and bring into their portfolios reliable payers who have no banking record, whether they work in informal commerce or have never held a bank loan. "Our decision engine can look at a person's entire repayment history and see immediately whether they qualify for a specific product. It does not matter that they have no banking record. It analyzes their history at every institution where they have ever operated, and it can determine whether the person is eligible for a loan or any other financial product," adds Etchegoyen.

By adopting the engine, built on automation and credit analysis technology, traditional banking institutions can speed up this process, reduce errors and improve the accuracy of their financial decisions. An agile, web-based, cloud decision engine built on algorithms, able to incorporate machine learning and big data, lets banks gather and analyze large volumes of information quickly and accurately, identifying the patterns and trends that matter most when assessing a customer's credit risk.

"The uFlow engine removes the subjective bias of a manual assessment process, and what remains is governed solely by the characteristics of each credit policy, which the financial companies themselves define based on the specific needs of each product," Etchegoyen concludes.

With a large informal market established across Latin America, and particularly in Mexico, Colombia and Peru, technological innovation is a fundamental tool for meeting the needs of population segments that are asking for access to credit. Given their sound financial behavior, and with banks adopting technology that carries information on every socioeconomic segment, traditional banks may finally be in a position to drive financial inclusion.