Fintechs: milking the poor

Every week or so, new articles pop up all around the Internet, lauding a new Fintech/Unicorn which will transform financial services in wonderful ways, facilitating payments, allowing for better money management, investment decisions or instant access to credit. While some of these undoubtedly carry the potential of serving consumer interests, others are closer to a scam.

While this short article will focus on some specific examples, there are a myriad more out there that are just as bad or worse.

Afterpay

A couple of months ago, news articles discussed a new form of payment facility called “Afterpay”. After creating an account, consumers can purchase goods without having to pay up front. Instead, the payments are due in four installments due every other week. The payments are interest free and the service advertises itself as a “try before you buy”solution for consumers. While such a service looks innocuous, the devil is in the detail, and in this case, the more or less hidden details. All Fintechs require a strong business model to convince investors and survive the initial”hype” phase. Looking at Afterpay’s business model, since consumers do not pay interest on their payments, where does Afterpay make money? One might speculate that Afterpay charges retailers for using their service, however, payment services get that luxury only when they have attained “critical mass”, meaning,once they can convince retailers that the price paid to use their means of payment will be more than offset by the increase in consumer purchases (hardly possible for a Fintech fresh out of the box).

After closely examining Afterpay’s FAQ section on the website, the enigma of the business model seems to find an answer: it relies on penalty fees for late repayment amounting to 10$ after midnight, and 7$ extra if the payment is not made within 7 days. Translating this into APR (Annual Percentage Rate), lets assume a shopper buys an item for 40$ and fails to repay the first installment of 10$, this automatically adds 10$ to the total amount. Assuming further that the consumer forgets to repay before the 7 days deadline, an extra 7$ are added to the cost, now a total of 57$. Rounding this up to a monthly APR, we get a 30% monthly APR, which translates to a yearly whopping 360%. Of course, since this is a flat fee, the APR is only an illustration. The lower the value of the good purchased, the higher it would translate into an APR and vice versa. Applying “late payment” fees is a smart business move since it allows Afterpay to settle in countries where laws have capped interest rates. And of course, even if Afterpay does charge retailers for their services, it is doubtful whether they would be open to disclose the detailed revenue and where their profits come from, not to mention the possible exacerbation of over-indebtedness of the most vulnerable consumers.

In summary, Afterpay is a service which encourages frivolous spending and consumerism, making sure that consumers can give in to their purchasing impulses, and, probably based on some market research which measures the likelihood of consumers to miss a payment, charge them a high fee for failing to repay on time. Maximizing sales and ensuring that clicks translate into more purchases instead of consumer abandonment (increasing the conversion rate) is one of their sales pitch for merchants by the way. Of course, Afterpay will claim that their intentions are pure, but in a finite world, where the purchasing power of consumers is relatively fixed, there are only so many ways that one can increase sales and create a payment system which is financially viable without extracting more money from consumers than they should rationally spend.
Dubious creditworthiness checks

Creditworthiness is an essential step in the lending process. Depending on how it is done, it can either be used to enhance responsible lending, making sure that consumers that do not meet certain criteria should not have access to credit, or on the contrary, segment the market and assess individual risk in order to increase or decrease the interest rate to cover for the risk. The latter is of course, highly controversial as such a practice almost certainly increases the risk to fall into over-indebtedness. The former, however, has its own problems, namely what are the criteria for assessing creditworthiness.

A number of fintechs, for instance, are looking at using data from a users’ mobile phone to assess their creditworthiness. This practice is especially targeted at the developing world, where the population is generally poor and therefore, there is no way to mutualize/socialize risk or only by creating loans which would be prohibitively expensive.

An article in the Wall Street Journal talks about fintechs which charge between 6% to 12% interest rate depending on the “creditworthiness” of the data collected from the consumers’ phones (the loans are repaid anywhere from 3 weeks to 6 months). Again, this is highly problematic since the algorithms which are responsible for calculating the likelihood of a consumer to repay looks at statistical correlations which cannot be deemed accurate. So called “innovative” practices to measure risk have proven to be highly “risky” themselves, since they have not been thoroughly tested. The case of the faulty loans granted by the “Lending Club” fintech are a case in point.

Many of these fintechs, however, will argue that thanks to them, consumers who were previously unserviceable due to the impossibility to assess their creditworthiness, now have access to credit. Most certainly, the volume of credit lent in countries where such innovative creditworthiness checks were introduced have increased. But is that a good thing? Of course, credit is an integral part of a functioning economy, allowing consumers to smooth out their expensive investments over a longer period like buying a car or renovating the kitchen without depleting all their savings. But this concerns middle income households, who have the financial resources and income to use credit for that specific purpose, hardly the situation of the poorest and most vulnerable elements of society in developing countries. In such countries, lending more money into the economy might simply equate to exacerbating over-indebtedness.

Looking at some of the “weirder” correlations found by the algorithm, apparently, sending more texts than you receive would indicate that you are more at risk of defaulting on a loan while gambling shows that you are more likely to repay. Criteria used for creditworthiness tend to create their own effects. For instance, if creditworthiness depends on successful repayment of previous loans, consumers will be forced to create a “successful repayment CV” in order to access future important loans like a mortgage at a cheaper price, thereby using credit to purchase everyday goods instead of their savings, just to prop up their credit score. Similarly, one could easily imagine users attempting to get a better interest rate by asking their entourage to send them more texts or engaging in more gambling! Ironically, gambling is seldom linked to responsible financial behaviour like repaying debt, but if an algorithm said it, it must be true, of course.

Besides the prudential and ethical issues that these fintechs pose, there is the more general issue of privacy. By allowing such companies to effectively “spy” on their users by pulling all and any data from their smartphones, the risk of misuse of this data skyrockets.

Safety Net Credit

Safety Net Credit is a company which prevents consumers from an unauthorized overdraft on their accounts by automatically “filling in” the necessary amount to balance their bank account. However, the consumer grants them the right to seize money when it is available to pay for the service and repay the loan at 0.8% interest per day (amounting to 292% per year on the company’s website). According to the company, they will always leave a financial buffer to ensure that the consumer does not face financial difficulty whenever they debit the money from their account.

This service is indeed a “better” alternative than pay-day loans to consumer in need of a short term financial buffer to meet certain commitments, but nevertheless fails at recognizing that their “target”customers, those who are “at risk” of going into overdraft, are among the poorest and most vulnerable, meaning that credit, under any format other than social micro-credit with an explicit aim to lift such households out of poverty, is never a long term solution to their precarious situation. A combination of savings, minimizing unnecessary expenditure, maximizing their revenue, receiving tailored advice/guidance and follow up from social or other independent services is the only “mix” that is likely to improve their condition.

As a general conclusion and advice to fintechs: stop developing services aiming to sell loans to the poor and most vulnerable. There may be a market for such products, much like there is a market for drugs, but you will not provide any service to society by serving it.