Introduction & Background Access to affordable credit is essential for individuals living on low incomes to participate in society fully. However, due to their limited credit history and volatile incomes, many cannot access mainstream sources of credit, such as credit cards and personal loans. As a result, they often must rely on more expensive sources of credit such as payday loans, doorstep loans or rent-to-own loans. This leads to them paying more for credit, also referred to as the poverty premium. Incurring the poverty premium exacerbates the financial challenges faced by already vulnerable individuals and can lead to a cycle of financial distress. Identifying the behaviours and factors that lead to a need for high-cost credit can help in identifying individuals who are most vulnerable to incurring the poverty premium. Objectives & Approach To achieve this, we rely on anonymized Open Banking transaction data from 100,000 individuals provided by a UK-based social lender.Given the latent nature of vulnerability, we identify indicators of vulnerability to poverty premium which include frequency of overdraft use, previous debt problems, low financial resilience, and indebtedness. We use a copula-based approach to create an index of vulnerability to poverty premium. This is based on weighting the individual indicators using their Spearman rank correlation coefficient. We use a fixed effects model to identify the factors that contribute to this vulnerability, where the index of vulnerability is the dependent variable. Relevance to Digital Footprints We use a rich and granular dataset on individual financial transactions to address a key social issue. The findings from this study can inform policy and industry efforts to promote greater credit affordability for these vulnerable individuals. This is particularly important due to the renewed concerns regarding the increased use of high-cost credit by individuals living on low incomes due to COVID-19 and the increased cost of living. Results Our findings show that variables related to the financial profile of an individual are important driving factors of the vulnerability to poverty premium. These include the number of salary sources, frequency of salary receipt, benefit receipt and savings frequency. Other variables related to spending behaviour such as gambling, volatility in fixed expenses and high transaction counts all have positive relationships with this vulnerability. Conclusions & Implications This study is a first step towards examining the determinants of vulnerability to poverty premium by analyzing an Open Banking transaction data set. The innovative feature of this work is the creation of an index of vulnerability to poverty premiums based on various indicators of financial distress and high-cost credit use. Our findings on the relationships between the individual's financial profile and the vulnerability to poverty premium suggest that policymakers should consider targeting interventions for individuals with specific profiles to alleviate the need for high-cost credit. For example, programs to promote regular savings or financial education for gamblers and people with volatile spending behaviour can help assist these individuals manage their finances better.
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