Using Data Insights to Optimise Debt Collection Strategies
By Claire Ferguson, Product Specialist for Collections at TransUnion
It is well documented that South Africa (SA) has a spending culture with low savings levels, a trend which is evident in many segments of the population. Given the low growth rate and tough economic circumstances facing SA as well as the global economy today, consumers have turned to more accessible revolving and unsecured credit facilities to supplement their income.
While high debt levels remain a challenge for many South Africans throughout the year – as is evidenced in SA’s debt-to-income ratio which is approximately at 78%, - the added financial pressure attributed to the festive season further exacerbated the situation.
Consumer credit extension in SA is currently around R1.8 trillion, with roughly 9% of this debt 3 months, at least, in arrears. In addition, around 45% of the 22.5 million credit active consumers have impaired credit records. This phenomena hampers collections activities as it becomes increasingly difficult for credit providers to effect as the levels of debt rise, with many collectors across multiple industries trying to solicit payments from the same consumers.
The typical increase in year-end spending and the associated financial squeeze that consumers generally feel in January due to their overspending, results in lenders seeing a notable increase in their arrears portfolio in the first quarter of the New Year. It is therefore important for businesses to identify effective ways in which to optimise their debt recovery activities in preparation for this typical seasonal increase, so as to mitigate the consequences of bad debt to their bottom lines.
Given the costs involved, it is imperative that credit providers fully leverage the data (both internal and external), people and technology resources they have at their disposal and devise insight-driven collections strategies that maximise recovery rates while managing costs.
While effectively managing debit order payments may reduce the flow of accounts into collections, a book will always experience some level of defaults. Organisations must ensure that the accounts rolling into their collections queues are prioritised and actioned appropriately based on their evaluation of the risk and opportunities associated with overdue consumers. Credit providers will want to be first in line to collect against consumers who have multiple debt obligations through various service providers. Collectors should obtain comprehensive insights on the consumers by analysing both internal and external data and then use these insights to develop their collection strategies effectively. They should then be flexible enough to be able to adapt their strategies based on what these insights are telling them.
Best practice indicates that collectors should find the optimal balance between driving effectiveness and efficiencies. For example, it is costly to go after the ‘easy targets’ i.e. where the consumer is both willing and able to repay their debt as the consumer will often self-cure without the collector taking any action, resulting in cost savings instead of focusing energy and resources and on “difficult targets” and hence saving on unnecessary expenditure, which on its own does not make the debt collection process easier. It is also ineffective to utilise resource intensive collections strategies on accounts where consumers are unable to repay their debts such as consumers already in debt review. It would be better to set aside these accounts and monitor them until they exit debt review.
Optimal collections strategies should consider those consumers that may have insufficient funds to meet their full monthly debt obligations, but who have the ability to pay a portion of their commitments. Data analytics can be used to predict the best possible date to collect against a customer based on historical payment behaviour. Having this information readily available and aligning the collections strategy to this date allows a collector to increase the likelihood of a successful collection in the future.
When choosing an appropriate collections strategy, a collector needs to weigh the consumers’ likely reaction against the consumer’s value and potential. For example, alienating a first time defaulter who is only a few days behind in making a payment by using an aggressive collections approach may cause that consumer to take their business elsewhere.
It should also be kept in mind that a collections strategy that is effective today, may not be effective in the future due to changes in the environment and the strategies of competitors. Data must be analysed on an ongoing basis and a ‘test and learn’ (champion/challenger) approach must be adopted to optimise collections strategies. In other words, applying different strategies on a small portion of the book and proactively measuring the results can support the continuous improvement and evolution of collections practices.
A well-considered, insight-driven collections strategy will yield strong return on investment (ROI), driving higher recovery rates, reduced costs and increased profits.