If you look at the current consumer debt picture as painted by the media, analysts and even some financial service providers, the situation appears to be dire. Consumers are battling already high debt levels, which are expected to be compounded now in the face of the latest interest rate hike, potential power increases and spiraling food costs off the back of the drought.
Yes, the situation is critical, but no, I don’t believe we are plunging into the abyss. South African consumers are not as reckless as many observers would have us believe (just look at the UK where consumer borrowing is at an all-time high), and under financial pressure they’re capable of paying their monthly bills and, if carefully managed, servicing their debt.
The challenge is for credit providers to be innovative in their approach in reaching debtors, and flexible in their strategies in undertaking collections.
Probably the most powerful tool in credit providers’ arsenal right now is data and predictive analytics. While this solution has been informing financial institutions’ modelling and product development strategies for a few years, it has only recently been applied to collections. And with outstanding results.
One of the areas where credit providers continually fall down is painting all debtors with the same brush. We assume all debtors can’t service their debt, don’t want to service their debt or deliberately dodge our attempts to reclaim outstanding debts.
But harvesting the wealth of data a provider has collected over the years and drilling down into this information reveals the differences in the types of consumers on their debtors’ book, the unique obstacles they face in servicing their debt, and the best strategies for successful collections.
For example, geographically, certain consumers could exhibit similar behaviour purely as a result of where they live. Perhaps they’re farm workers and during peak seasons are not able to make it into their nearest town to make the relevant payments for weeks on end. That would be true for multiple customers in that specific area as well as other farmworker customers in other rural areas across the country.
Further analysis would reveal the different seasons in the different parts of the country (i.e. winter versus summer crops) that drive consumer behaviour in these respective regions.
And then there are specific types of occupations that when grouped together, present a different set of challenges for collections. Night workers, for example, are often unreachable during the day as they catch up on sleep after their late shift. Does this mean they make deliberate attempts to miss debt-related phone calls? No, it simply means the collector is phoning at the wrong time.
Understanding these subtle nuances between customers and the particular challenges they face, helps ensure a more effective collections strategy.
The July 2015 www.forbes.com article Bank reduces debt collection costs through big data analytics, says data analytics can save companies significant amounts of money by showing that the obvious process isn’t always the most cost-effective.
It cites the example of a US regional bank that, using data analytics, managed to reduce collection costs by $1 million, during the recession, without dropping below its 98% collection rate for early stage delinquents.
Over and above using big data to redefine collections strategies, collectors must maintain regular contact with debtors (a surprising number of debtors can pay, but simply forget); incentivise good payment behaviour (i.e. moms and dads, pay your account and get a back to school voucher); be proactive and establish payment plans after the first debit order has bounced (don’t wait for the debt to mount); be creative with debtor communications (use social media and sms reminders); and most importantly, implement flexible strategies capable of adapting to changing market conditions.
Ultimately, credit providers should look beyond mere collections to positive rehabilitation that transforms debtors into long-term clients, because when the economic downturn eases, this is where future growth will lie.
Mark Essey is director of Debt-IN, experts in debt recovery and specialist advisors on credit and distressed debt.