AI-powered debt collection may help avoid another P2P lending crisis

Peer-to-peer, or P2P, lending should have been the long-awaited answer to a complex problem of financial inclusion: how to help the poor break out of the cycle of poverty?

Finally, there is a commercially viable way to lend money to the “riskier” segments of the market thanks to the high penetration of mobile internet and the elimination of expensive intermediaries.

Sixty-six percent of Indonesia’s population was unbanked in 2018 and cash was king. P2P lending platforms, which typically match promising borrowers with private lenders, offered the perfect solution to the problem. Ordinary Indonesians gained much-needed access to credit, while lenders were given the opportunity to earn higher returns than many other investment opportunities at the time.

Then everything went wrong.

Loan sharks hide behind the P2P lending mask

In January, P2P lending was the third most criticized sector in Indonesia. Stories of stalking can still be found on social media grouped under the hashtags #korbanpinjol or #korbanfintech (“victims of online borrowing” and “victims of fintech” respectively) with sordid story after sordid story of victims warning against online borrowing.

Borrowers are crushed by impossible interest rates (up to 2% per day) and administration fees that result in bloated debts from unscrupulous lenders, no matter how low their initial borrowed amounts were. Desperate borrowers then refinance their loans with other P2P lending companies over and over again. They are now trapped in a vicious circle.

Then comes the time of collection. Bullying, sexual harassment, data privacy breaches, blackmail, and harassment of friends and family are all part of the horrifying norm. One of the patented debt collection tactics is to create WhatsApp groups and add the borrower’s friends, family and colleagues to shame delinquent borrowers. In these groups, the borrowers are described as “fugitives” who must be tracked down. Debt collectors will often demand that members of these groups reveal where borrowers are “hiding”.

Unfortunately, even legitimate businesses can fall into dire straits due to high default rates, and without a viable collection strategy planned, may unknowingly employ third-party debt collection agencies who use these barbaric tactics to chase their debts.

One of the victims of this harassment was a Jakarta taxi driver who committed suicide last February after failing to repay outstanding loans from 20 different lenders.

His suicide note contained a plea for the Financial Services Authority (OJK) to eliminate online lending, which he called a “devil’s trap”.

The case of the taxi driver presents two of the biggest problems with P2P lending – borrower harassment and borrowers inevitably defaulting on their loans if they borrow from too many lenders. OJK found at least one instance of a single borrower borrowing from up to 40 platforms.

The OJK tried to regulate the market, but found itself faced with an uncomfortable truth: the Internet is impossible to regulate. I can speak to these issues in Indonesia with some first-hand knowledge, but we are not unique.

The lessons we haven’t learned

China’s problems with P2P lending more often stemmed from defaults that forced even higher interest rates and the shutdown of P2P lending platforms, and from taking investors’ savings with them. .

The Philippines, another infamous recipient of P2P loans, has faced problems that ring closer to those of Indonesia. Vietnam too.

The trajectory, however, is always the same.

P2P lending is gaining attention for providing “a real solution”, and investors are starting to pour funds into these platforms. The industry is increasingly blighted by ridiculous bad player fees. A combination of this and no real debt collection strategy leads to increasingly desperate lenders. Borrowers are starting to report harassment by lending platforms. Lives are lost.

Regulators rushed to prevent the situation from getting worse. Now we come to an important question: could we have prevented all this?

Borrowers need to learn the financial basics

Low-income people often can’t quite grasp the idea of ​​interest rates, making them easy choices when sold on weekly payment schedules. If lenders take advantage of this, they cannot identify the harm done to them, or what they can do about it.

In fact, those earning lower incomes may not even be equipped with the financial management skills necessary to manage their debts, which can contribute to higher default rates and an inability to find real solutions to the problems caused. through their debts other than refinancing with disreputable lenders.

Any social good that might have been felt from increased access to financial products is undermined by the lack of knowledge about how to truly maximize these offerings.

KPMG noticed the problem as far back as 2017, and today it rings truer than ever. Educated borrowers are better equipped to protect themselves against bad lenders and, more importantly, can make decisions that will actually benefit their long-term financial situation.

Credit check: a necessary evil?

Credit checks were the very reason why P2P loans were needed, but industry failures can sometimes remind us: there was a reason they were needed in the first place.

The P2P lending industry needs to perform strong credit checks, and it needs to do so without preventing previously underserved segments from entering the market.

Fortunately, alternative third-party credit scoring solutions have been launched to fill this significant gap. Solutions such as smartphone-based credit scoring solutions use robust artificial intelligence to obtain information about an applicant’s creditworthiness solely through their smartphone and could help P2P lenders provide funding on fair terms to borrowers. whose traditional systems have failed.

There are also solutions based on artificial intelligence to collect debts.

Ethical and personalized collection

Companies like AsiaCollect strive to help businesses maximize their non-performing loans, from offering credit management counseling and Software-as-a-Service (SaaS) solutions, to purchasing debt portfolios.

AI and machine learning can be used to analyze the behavioral and emotional psychology of borrowers, allowing call center operators to communicate more effectively with different personality types. Our platforms are also able to identify the best times and channels (SMS, email, social media) to reach customers, resulting in higher engagement and refund rates.

This level of smarter profiling and targeting of borrowers not only increases the likelihood of reaching the borrower, but also the collection rates for each targeted individual.

P2P lending platforms can benefit from technology-driven debt collection, but the platform can also find its place within various organizations, from collection agencies and digital lenders to banks and non-financial institutions. banking. A more human-centric and targeted approach to how we collect debt also reduces a company’s exposure to any form of reputational risk.

Maybe as an industry we had to go through these terrible growing pains to really understand the double-edged sword we let into the market. To answer the question posed above, yes, I believe these tragedies could have been avoided.

Industry players should consider a holistic application of P2P lending in new markets, considering all stages of a borrower’s life cycle.

Central to these efforts is a critical question: do we truly understand the underserved markets that require P2P lending?

I think once we’ve done that, the rest will follow naturally.

Guillermo Martin is Head of Global Sales and Country Manager for Indonesia at Asia Collect, a Singapore-based fintech company that aims to reform the collections industry using AI and machine learning.

Janet E. Fishburn