This paper examines whether repeated payday loan use, commonly known as the debt trap, harms borrowers' financial wellbeing. Using Open Banking data from 1,815 UK borrowers observed between 2017 and 2018, we model borrowing intensity using a two-state hidden Markov model (HMM). The HMM outperforms single-regime alternatives and identifies two distinct borrowing patterns: occasional (low-intensity) and persistent (high-intensity) use. Each regime exhibits a characteristic relationship between borrowing intensity and wider transaction behaviour. We translate the decoded state sequence into a practical monitoring rule based on sustained high-intensity exposure. Defining a trigger event as 12 consecutive weeks in the high-intensity regime, we find that 36.4% of borrowers experience at least one such event. Among those who do, high-intensity weeks represent 17.8% of all borrower-week observations on average. Together, these results provide evidence for a persistent high-intensity borrowing pattern and demonstrate that it can serve as a simple, interpretable rule for monitoring prolonged reliance on payday loans.

翻译：本文探讨了反复使用发薪日贷款（通常称为债务陷阱）是否损害借款人的财务福祉。利用2017年至2018年间观察到的1,815名英国借款人的开放银行数据，我们采用双状态隐马尔可夫模型（HMM）对借款强度进行建模。HMM优于单机制替代模型，并识别出两种截然不同的借款模式：偶发性（低强度）和持续性（高强度）使用。每种机制均展现出借款强度与更广泛交易行为之间的特征关系。我们将解码后的状态序列转化为基于持续高强度暴露的实用监控规则。将触发事件定义为连续12周处于高强度机制，我们发现36.4%的借款人至少经历一次此类事件。在这些借款人中，高强度周数平均占所有借款人-周观测值的17.8%。综上所述，这些结果证明了持续性高强度借款模式的存在，并表明其可作为监控发薪日贷款长期依赖的简单、可解释规则。