Detecting Consumers' Financial Vulnerability using Open Banking Data: Evidence from UK Payday Loans
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Behind the debt trap concept is the rationale that payday loans exacerbate consumers' financial vulnerability. To investigate this relationship, we propose a Mixed Poisson Hidden Markov approach to model the number of payday loans a borrower obtains in each period. Given the lack of agreement in the literature on financial vulnerability, we introduce financial distress as an unobserved binary variable using a hidden Markov process (vulnerable and non-vulnerable). Using data from 90,523 anonymised transactions for 1,817 UK consumers, we find that the effect of certain time-varying covariates depends greatly on the borrower's hidden state. For instance, luxury expenses and non-recurring income increase the need for payday loans when financially vulnerable, but the opposite is true when not vulnerable. Additionally, we demonstrate that almost 60% of payday loan borrowers remain vulnerable for 12 or more consecutive weeks, with two-thirds experiencing consistent financial difficulties. Finally, our analysis underscores the need for a nuanced approach to payday lending that recognises the varying levels of vulnerability among borrowers, which can prove helpful for policymakers and lenders to enhance responsible lending practices.
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