Lender abuses

Experience demonstrates that for digital credit, reaching scale in a developing economy involves a high risk of customer over-indebtedness leading to default, heavy-handed collection attempts, cutoff of credit access, and reduced welfare. These risks are inherent in many digital consumer credit models, which combine unsuitable offerings with:

  • Mass marketing to consumers with little assessment of individual consumer circumstances or ability to repay (“lend-to-learn” model)
  • Business models based on high loss rates (for example, large late fees relative to size of loan)
  • Poor practices such as rolling over loans or encouraging multiple borrowing
  • Abusive debt collection practices utilizing mobile phone and social media data to contact relatives, friends, and coworkers.1

High incidence of over-indebtedness and default may indicate a pattern of reckless or predatory lending. A failure to lend responsibly as defined above could be considered reckless and subject to administrative penalties. A more serious form of market misconduct, involving harmful intent or at least a pattern of harm, predatory lending is a criminal violation of financial laws in several countries.

Loans offered with limited or no assessment of consumer circumstances, or without adequate consideration of the target market, may be unaffordable and so unsuitable for particular consumers. While this is a longstanding problem in the traditional credit market, the risk is exacerbated in the digital context. For example, digital credit providers may use blind “lend-to-learn” models that fail to consider repayment capacity. As a result, borrowers may become over-indebted and individual lender/investors may suffer losses that they could not have anticipated.2

Debt collection is also subject to a variety of abuses. Digital lending has seen an upswing in harassment tactics by providers and their agents. Lenders have been known to harass a borrower by repeated calls, constant reminders sent to the borrower’s mobile phone, using data obtained from the borrower’s contact list to call or text friends and family to shame borrowers into repayment, and creating further stress through social media posts.3These tactics are, in a sense, a natural complement to predatory lending.

Recommendation: A number of regulatory responses to predatory lending and abusive collections are possible, such as to:

  • Require responsible lending, including the duty of providers to assess the ability of prospective customers to repay loans and grant loans only where they are affordable to potential borrowers
  • Limit rollovers and multiple borrowing to decrease risk of over-indebtedness
  • Require enhanced monitoring of loan portfolios, particularly where automated credit scoring is utilized
  • Apply product design and governance rules to digital consumer credit, including designing processes and customer acquisition plans to ensure that potential harms and risks to consumers are considered and mitigated
  • Adapt debt collection rules to prohibit the kinds of abuses that have become prevalent among digital lenders
  • Define predatory lending as a more serious offense than irresponsible lending, with stricter penalties.

When dealing with digital personal credit, regulators must also be vigilant about abusive provisions in the loan agreements such as short-term interest rates and rollover provisions that lead to extortionate charges, and other tactics such as “tying.”

Predatory digital lending and abusive debt collection are enabled by improper handling of customer data. Digital lenders have developed methods to manage risk and ensure repayment when faced with inadequate information or collection mechanisms. These are likely to be used even more often when lenders have predominant market power and can make unreasonable demands. In such cases, lenders may either increase the risk premium via higher interest or fees, or alternatively demand access to a customer’s entire data trail, or both. In India and China, for example, providers with comprehensive access to customers’ data trails are known to have used the data to exert social pressure on debtors, through “debt shaming” and similar tactics.4(See the next section for further detail.)

Abusive provisions in the loan agreements must also be monitored. Interest rates and fees, for example, often reach levels considered exploitative, particularly for vulnerable borrowers. As with conventional credit products such as payday loans, digital credit serves as a kind of financial “taxi” in that the loans are typically very short term and interest rates are quoted on a monthly, weekly, or even daily basis. This need not be a serious problem unless loans are repeatedly rolled over. When that happens, it may become more meaningful to talk about those loans with quoted rates of, e.g., 1% per day or 4% per month resulting in APRs in the range of 350% to over 500% -- unless strict limits are placed on maximum APRs, repayment terms, and/or rollovers. To evade interest rate caps, digital lenders often charge fees as either a substitute or a supplement to interest charges. These are typically a fixed percentage of the principal amount (or in a few cases a fixed sum) ranging from 1% to 30%, often on top of the interest charge.5

Another example of exploitative contract terms is “tying.” This is where the lender markets other products (e.g., insurance) by bundling them into a package with the loan, conditioning the loan on the customer’s acceptance of the full package. The risks of tying are greatest where remuneration (for partners, agents, or staff) is based on sales volumes. The bundling requirement may be disguised or only implied in the loan agreement, and so regulations must be carefully worded. For example, in British Columbia (Canada), tied selling is prohibited for payday loans. A payday loan agreement must not include a term or condition relating to the supply of other goods or services and must include a statement that the supply of ancillary goods or services is separate and optional.6

Country Examples

Link to South Africa case studies
South Africa
Link to Uganda case studies
Uganda