Abstract
Digital credit has exploded in popularity over the last decade with the number of digital lenders growing nearly tenfold globally (Venkatesan, 2023). Although digital credit offers significant potential to advance financial inclusion by allowing previously unbanked and underbanked consumers access credit (Bharadwaj and Suri, 2020), the speed and ease of access to digital credit has raised several consumer protection concerns particularly in low- and middle-income countries (LMICs).
Digital loans are disbursed and repaid electronically, and they differ from traditional credit in several aspects: approval is nearly instantaneous, evaluation of loan application is automated, loans are processed remotely without requiring in-person interaction, and loan decisions are typically determined using “non-traditional data” such as mobile phone data (Francis et al., 2017). The most popular form of digital credit offered in the Philippines is short-term, high-interest, small amount consumer loans disbursed via mobile money platforms (e.g., FMA, 2021; Francis et al., 2017). Despite being costly, the popularity of digital credit in the Philippines suggests unmet demand for credit. However, the surge in customer complaints concerning inadequate disclosures, misrepresentations, high interest rates, and unreasonable collection practices (e.g., FMA, 2021; Tamayo, 2021), also indicates the need to build a stronger evidence base to improve consumer protection in digital lending.
The target client base, typically low-income consumers with low levels of financial literacy, and influenced by typical human behavioral biases such as weak self-control, present bias, overconfidence and limited attention, are susceptible to exploitation due to poor transparency of fees and loan terms and costly roll-over refinancing (Garz et al., 2021). Furthermore, most digital credit borrowers live precarious financial existences that allow little room for financial error and poor consumer decisions can have debilitating immediate and long-term consequences. In the short term, poor consumer decisions can worsen the borrowers’ cash flow position and induce over-indebtedness that could ultimately result in them being shut out of credit markets (Skiba and Tobacman, 2019; Melzer, 2011). In the long- term, over-indebtedness can cause asset erosion and poor psychological health (Gathergood, 2012).
In partnership with the Philippine Competition Commission, we will conduct an online survey and embed a discrete choice experiment (DCE) to provide evidence on how loan choice is affected by behaviourally-informed disclosures and alterations to the choice architecture. After passing the screening questions and answering socio-demographic questions, we will randomly assign respondents to one of the eight treatment arms or the control group. The core task involves choosing the most preferred option from six hypothetical digital credit products which vary across a number of product attributes. The control group will be presented with a set of digital loan choices, inspired by real products, and presented similarly to how they are marketed to consumers in the Philippines (with partial information and informed by specific marketing strategies), requiring potential customers to hover the mouse around to access information on nominal interest rates, processing fees, etc. The first two treatment arms involve provision of additional product information, specifically product attributes a regulator might request be presented in the fine print, These two treatment arms present the six products in random order and involve the clarification of product attributes with and without the total cost of credit (effective interest rate). The remaining six treatment arms involve a ranking one of five product attributes, followed by the final treatment which allows the participant to choose the attribute of ranking.
Our experiment allows us to explore a number of important debates in the literature. First, explored in other credit markets, is how awareness or naivete about one's own abilities and preferences affect product choice (Alcott et.al. 2022; Ausubel 1991; Campbell 2016). We measure borrowers' overconfidence and perceived time inconsistency, and examine their relationship with individual choice of digital loan products. We are specifically interested in testing how generalized overconfidence and perceived time inconsistency affect the weights that consumers place on contingent costs, such as late payment fees or the cost of repeated borrowing, which are only relevant for individuals who believe they will miss a payment or borrow repeatedly.
We anticipate that findings from this study will help improve understanding of consumer protection issues in the digital credit market globally. Across the regulators in the Philippines there is a shared sense that more needs to be done to equip consumers with tools to identify “appropriate” financial products as continued exploitation of consumers will lower willingness to access digital financial services (DFS) and erode trust in the broader financial system (e.g., Garz et al., 2021; McKee et al., 2015).