Collections Predictions 2019: SOP Won’t Cut It

Here’s my advice for 2019 in a nutshell: With IFRS 9 impacts and €780 billion of NPL in Europe alone, stop reading about AI and start thinking about optimization.

by Bruce Curry

December 18, 2018

Here’s my advice for 2019 in a nutshell: With IFRS 9 impacts and €780 billion of NPL in Europe alone, stop reading about AI and start thinking about optimization.

OK, let me unpack that. I’ll break it down to four focus areas.

Accounting Rules & Regulation Overload

You don’t have to be Nostradamus to predict that regulation will continue to drive change in the collections industry. In fact, the regulatory pressure may be compounded by a rush of interpretation of recent regulation. And it’s not just regulation around GDPR and the now-imbedded KYC, TCF and effective management of the vulnerable — in the EMEA region, we are also seeing levels of prescription we have never seen before, whether that be the management of persistent indebtedness in the UK or the need for customer authorization under DebitCheck in South Africa. So there is not only an increase in what should be done but evidence of regulators deciding they will prescribe how things will be done and to whom.

The first round of audits for IFRS 9 are already causing some challenges in both the appropriateness of the modelling and certainly the credit loss and capital coverage implications. On top of this, organizations are also starting to identify complexities created by accounts oscillating between Stage 1 and 2, how this impacts the necessary cost of “probation”, and how that will be catered for in any originations pricing.

IFRS 9 and CECL may make risk-based pricing difficult, as will the focus on fair pricing by the FCA in the UK. But if you can’t confidently price for risk, you have to find other ways to increase shareholder value and make margins. If you can’t increase sales, you’ll have to bring down the cost to operate. That will push more organisations to explore automation and cloud-based collections — although most in the industry still have to get their heads around what a move to (or provision of) cloud services truly means.

The shape and price of credit is likely to change significantly in those markets where the financially vulnerable are well-protected. As regulators look to force remedial action that evidences more customer tolerance, the cost of that tolerance will be passed on to non-vulnerable customers.

Another interesting trend that will affect collections is the rise in telecommunications firms being the channel of credit facilities in many markets. People who are unbanked will no longer need a bank to be banked. This is already true in some emerging economies, but it’s expanding to other regions as well. This could cause some chaos if the regulations aren’t as tight as they are in banking, followed by new regulations to address the impacts that result.

An upside of the regulation and accounting changes that are hitting many markets is that lenders will need to move from talking about “the back end informing the front end” and actually leverage the analytic tools and technologies that enable rapid learning. If need ‘truly is the mother of innovation, then the needs that are being driven by the regulatory and accounting changes are forcing an ever-increasing need to invest in enterprise-wide, agile and high-benefit decision science solutions

And with all of this, we are yet to see where open banking comes into play for those managing the in-arrears portfolios. Should be interesting.

The Debt Wave

Many markets are already experiencing an economic slowdown, and some are on a clear path towards economic downturn. This is driven in large part by political issues such as Brexit, and stock market volatility.

(I don’t see Brexit having a huge impact on collections in 2019, but certainly by 2020 if estimates of a 3% shrinkage in the British economy come true, along with a per-household cost of £2K, at some point that’s going to mean a lot of people already in persistent debt will miss bill payments.)

EMEA is a very diverse region: we have organizations with 40%+ NPLs in mature Southern Europe markets and organizations with only 0.04% NPL in the emerging east Africa micro credit markets. In fact, a country with NPL well below the highest in the region holds the highest absolute value of NPLs. So nothing is crystal-clear other than the fact that we have too much debt —whilst regulators and accounting rules are looking to strengthen how risk is managed, we can’t seem to stop the need to consume more credit at a household level.

The Transformation of the Debt Servicing Industry

All of the challenges of reducing NPL (non-performing loans), understanding the portfolio impact of NPEs (non-performing exposures), having to report on the UTPs (unlikely to pay) will continue to drive a reshaping of the third-party debt purchase and servicing infrastructures, no matter the maturity in that area of the market. It presents many opportunities for debt collection agencies, and it will be interesting to see where the investment goes into that sector. Mature markets may find they are left short, as margin rewards from maturing C&R markets hold lower-hanging fruit for those in the 3^rd party space.

The mergers and acquisitions of DCAs are likely to continue apace, likewise the uplift in technology investment made by the larger servicing organizations looking to increase competitiveness through improved standardization and a lower TCO

Analytics at Last!

As regulations and NPLs make originating non-profitable business ever more costly, collections analytics are finally going to get the attention they’ve deserved for decades. Squeezes on margins will drive organizations to find a route to stronger margin, and the best way to balance regulations, costs, demand and capacity is analytics, in particular mathematical optimization.

AI is here for a few and coming for many, but there will be many failures and many areas of wasted investment before appropriate AI is an off–the-shelf purchase. In the C&R space, a huge proportion of the industry still needs to develop a reasonable standard of analytic insight. My advice: Don’t get distracted by the word AI, unless you’re already pretty far along the analytics spectrum. You’ll see faster results from focusing on a good set of collection models and strategy optimization. (And for those that are close enough to it you’ll recognize that mathematical optimization in an adaptive control environment, and so actually is AI and ML!).

Not every organization will realize this off the bat, but those interested in achieving a true competitive collections competence will look to analytic models, decision engines and automated, omnichannel communications. Early adopters of highly sophisticated omnichannel systems will gain an advantage from their ability to serve pre-delinquent and disorganized payers at an extremely low cost, whilst achieving a better customer experience. (For many, many customers, collections is their experience of a lender.)

These omnichannel solutions are the target investment of many organizations that recognize the competitive disadvantage if they’re not in place. However, these platforms that provide the biggest change in customer treatment and performance for huge cohorts of customers only start to truly ”buzz” when they are deployed on a foundation of analytic optimization.

Collections and recovery is increasingly being recognized as an area of business performance differentiation. 2019 and 2020 will see a steepening of that incline. This might mean higher budgets; it certainly means transformation. As our industry gets the full attention of the CFO, the CRO, the CTO and the CEO, the old ways are just not going to cut it anymore.

For more collections predictions, see this post from my U.S. colleague Ed Wallen.

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While you’re here, why not check out our other prediction pieces for 2019

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I further broke this down by looking at the characteristics of the youngest 15% in each group, which occurs at age 29 for the 750-799 group and 43 for the 800-850. We used FICO® Score 9 for our analysis, and examined typical variables of the categories that go into the make-up of the score. <a href="http://www.fico.com/en/blogs/wp-content/uploads/2016/10/FICO-Score-High-Achiever-table.png"><img class="alignnone size-full wp-image-29367" src="http://www.fico.com/en/blogs/wp-content/uploads/2016/10/FICO-Score-High-Achiever-table.png" alt="fico-score-high-achiever-table" width="715" height="747" /></a> Since there’s a lot to dissect in this chart, I’ll highlight a few findings that struck me: <ul> <li>Credit history. Higher scores are undoubtedly associated with a longer time on file. What’s striking is the higher average time on file for the 800+ group, both overall and for revolving accounts (the most common trade line). Clearly, it helps to start credit use early in life – but that’s not the sole determining factor for high scoring. The younger cohorts in both the 800+ and 750-799 groups have time on file medians significantly less than their older counterparts.</li> <li>New credit. High credit scorers do, in fact, pursue new credit. We see little variation in months since last trade line opening and last inquiry among all groups observed.</li> <li>Pay on time. As you might expect, the further in the past the delinquency, the higher the score – and that’s if a delinquency ever happened. 95% of the 800+ people and 72% of the 750-799 group have never been delinquent, which is a striking contrast to the 57% for the total population. The percentages for the younger groups are even higher, especially so for the 750-799ers. Collection items are also scarce for these high scorers. 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The 800+ group is roughly 1/4 of the national median, both in total and on their highest utilized card; they also have lower balances and more cards. The 750-799 group is more active and higher utilized, but still only at 2/3 of the national figures. The young 750-799 group compensate with lower revolving balances and, as a result, lower utilization, which is in line with what we see for the 800+ group.</li> <li>Benchmarks. I’d like to point out that while this study provides good benchmarks of the typical credit traits of the FICO® Score high achiever, individual credit profiles will vary widely. And keep in mind that when we sort groups of consumers as a whole by different behaviours, some results may look superficially odd. For example, the 800+ band has a longer median average open account time (128 months) than average revolving months on file (140 months).</li> </ul> So, what do we conclude? A huge takeaway is that high scorers don’t have too much in the way of serious delinquencies and negative public record data. In most respects, the young 800+ people are like their peer group. They really only differ markedly in their shorter credit history and higher non-mortgage balance, both of which are a function of life stage. Our results show that you don’t have to be a credit product hermit; these high scorers have more credit cards. The takeaway is to start credit activity early and maintain well-managed and moderate usage. In many ways, the young 750-799 people are more interesting because their age profile is much younger. Their credit characteristics differ more from their peer group, particularly in terms of length of credit history. They compensate by having almost pristine credit records and lower balances. Ultimately, 39% of US consumers are FICO® Score high achievers, which they accomplish by following common-sense credit practices. It ain’t rocket science!

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