Globally, the Buy Now, Pay Later (BNPL) phenomenon is rapidly gaining ground. The vertical grew 197% year-on-year in the second quarter of 2020 alone, according to a report from Cardify.
But in Latin America, ‘buy now pay later’ has not yet taken off. Some players argue that the lending model is still in an early stage of development, while others suggest that access to information is its main obstacle.
“It’s not such a clear vertical,” Fabrice Serfati, director and partner at IGNIA Partners, a fintech-focused venture capital firm, told iupana.
“Mexico, for example, continues to be a place where any fintech has an impressive growth possibility. There is a very low level of banking, but at the same time there is a very great need. All that digital divide was shortened throughout the pandemic, so these people want to consume. The big problem is the lack of information.”
The ‘buy now, pay later’ model facilitates purchases by deferring payments into installments, without the need for a credit card. Depending on the model, either the buyer or the seller will pay a fee for the service.
For businesses, the advantage is that it offers an alternative payment method for high-value purchases, while increasing the average purchase ticket by up to 60%. For the consumer, it offers transparency over the all-in cost of borrowing, and greater control over monthly spending.
In Spain, where there is a lot of credit information and a low level of informality, the model has been successful.
“[BNPL] becomes interesting because it adds liquidity to the consumer market over and above the traditional lines,” said Serfati. “The problem is that, in Latin America, where you don’t have that amount of information, it is very difficult to do so.”
Lauren Connolley Morton, partner at QED Investors, a VC firm with a focus on Latin America, also said that the model needs highly robust data to succeed.
A BNPL model is “not easy to build”, she cautioned, as it requires scaling sales and customer success across three different components: companies, store sales reps, and end consumers. “The value proposition and experience have to work in each of these segments to achieve massive growth,” she said.
BNPL in Latin America: The Data Challenge
Given the lack of data, it can be difficult to development algorithms to evaluate a borrower’s credit risk.
Credit algorithms use a range of data, such as home address, consumption of basic services, and income, among others. However, Serfati says a lack of data makes it difficult to build strong risk models.
“The flow of information around people is still very poor. The issue is to demonstrate that there are recurring purchases or payments, with which you can build a proxy of credit quality, or improve credit information systems and thus generate some idea of credit risk. ”
Wenance, an Argentine consumer credit fintech began operations in Mexico just over a month ago. There, the low access to information is something that they are experiencing first hand, said Salvador Calogero, director of expansion and new business at the fintech.
“You have to take a reverse path of taking non-traditional variables, and learn little by little. From this learning, you can build an internal scoring model,” he said from Buenos Aires.
Wenance started its expansion in 2018, and operates in Uruguay, Spain and Mexico. It plans to begin offering BNPL credits in Spain soon, and then take the product to Mexico and Argentina.
“In Argentina we are thinking of granting BNPL credits for just 30 days, not much longer considering inflation. Then, probably, we will extend it more, perhaps two months, but no more, at least for the time being,” he anticipates.
To achieve this, the fintech -which serves the underbanked population in all its countries of operation-, will consider variables such as the history of the portfolio, behavior patterns according to the source from which the client comes, the type of device they use, among other factors .
Expanding the base of information
Other players such as Atrato, a Mexican BNPL lender, also say that data is a key element for success in the vertical.
“If you want to offer this service in segments that have little credit history, it is difficult to make a good decision. Something we do is integrate information sources that allow us not to depend on conditional variables, such as credit bureaus, bank account information, etc.”, explained Rogelio Rea, CEO of the fintech.
Atrato’s decision algorithm analyzes more than 400 data points that are extracted directly from the customer as well as from affiliated businesses, in addition to information from social networks, email, telephones, and more.
With this, the company can accept or reject credit applications, as well as sidestep risks, by identifying anomalies and suspected cases of fraud.
Impersonation and bank identity theft are among the most recurrent financial frauds in Mexico. And during the pandemic, these online crimes increased by more than 400% compared to 2019 figures.
Lateral moves into BNPL
Data from alternative sources can substantially assist BNPL companies in the difficult task of assessing credit risk.
The big players that offer debit products, online purchases or payment solutions have insights from their millions of users. These databases could pave the way for strong BNPL models.
“The problem is that the businesses that exist now are not born from a deposit account, but directly as small or medium financers of the liquidity cycle of individuals who they acquire through digital means. So they don’t have much information,” Serfati said.
As examples of possible future disruptions in this vertical, Serfati points to Amazon and Mercado Libre, two relevant players that are collecting information on product consumption and could easily extrapolate it to BNPL products.
By offering other financial products, potential BNPL lenders can better analyze the risk of a potential borrower when they get to the point of sale.
Flexio, for example, a platform that helps SMEs manage and automate customer collections and supplier payments, seeks to orient its model towards the ‘buy now, pay later’ scheme. This would not be a model aimed at the consumer, but at SMEs, offering them financing for their own purchases.
“When SMEs start using our platform, we will get to know them even better and we will be able to help them to pay for certain services or products from their own suppliers, but in installments. Everything goes through our pipes,” said Nathan Schorr, co-founder and CEO of the Mexican fintech.
In Mexico, 73% of SMEs are not financially supported by a bank, according to Schorr. Yet Flexio getting to know their customers very well, so the next step will be to offer them the BNPL model.
“It’s a very safe business model, I’m not going to have to charge an interest rate,” he predicted.
Although there are many factors that are slowing the growth of BNPL lending Latin America, fintechs’ ability to build databases of information themselves could spur it forward.