Fintech lenders are using new data sets and evaluation tools to measure the credit risk of new borrowers – and say the models are here to stay
Latin American fintechs are innovating their credit risk models and using alternative data sets to keep up lending rates amid the pandemic.
The innovative models could pave the way to a new methods of evaluating credit risk, post-pandemic, the fintechs say.
Rethinking risk scoring is critical given the impact of covid-19 on Latin American economies: GDP forecasts estimate a 9.4% contraction this year, employment has shot up, businesses are closing, and those that remain open are finding increasing delays in getting paid.
Amid this context, traditional risk evaluation methods are not always effective.
Findo, an Argentine fintech which lends to individuals, for example, has been evaluating loans based on borrowers’ contact books and interactions with apps on their phones.
“When we analyze a person, we ask them to give us access to the information that is on the smartphone and we see what applications they have used. Statistically, we can compare them with other people who have downloaded our application and see how they performed,” says Diego Varela, CEO of Findo.
The startup analyzes the apps, contacts, income and credit performance, where the user goes using location data (to verify their home and work addresses), together with a digital application process.
Faced with covid, the fintech has not had to modify its evaluation variables – except for the location data, which they have taken out given local pandemic lockdowns.
The approach represents a complete reinvention of traditional credit risk evaluation models. Other fintechs are innovating around the edges.
In Colombia, Gulungo lends to companies without a credit history, or with very large existing debts. It presents potential borrowers with six open questions and conducts individual evaluations for each microenterprise. “The model is flexible enough to understand each client, each situation and, furthermore, each scenario, like the one we are seeing now,” explains Juan Reyes, CEO of Gulungo.
In Peru, Altera generates its own score and places a high value on companies that have very high cash balances to see them through a tough patch.
“Of course, we never imagined that it could be Covid,” says Alberto Falcón, CEO of the loan fintech.
Profitable technologies, uncertain scenarios
Technology has helped many people and companies during the pandemic, allowing them to act remotely and lower costs. And for lenders, it has opened the way for gathering large amounts of information and analyzing behavior patterns.
“By collecting more data, we can better understand behaviour,” says Falcón. “The more data we can collect the better we minimize credit risk: we can see patterns that have previously failed us.”
The new risk evaluation models open access to credit to a wider potential group of borrowers, say the fintech leaders.
There is a “circularity” around loans granted and “check list” evaluations used by traditional financial institutions, says Reyes. With a slow economy, businesses need fresh capital, but credit histories and traditional evaluations can slow that process.
The rise of new socio-economic groups, new employment models and new behaviour patterns increase the need for typical credit evaluation processes to be reviewed, says Varela.
“The question is to understand how the macro-economic scenario is going to be for each of the types of work, because there will be changes in that sense,” he says. “There will be new ways of how the macroeconomy in the region will be related today and that is where we have to understand well how to accompany each of these segments.”
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