In Focus Consumer Credit
Left-right: Andrew Jackson; Bruce Curry; Clive Moore; David Sheridan; Dawn Stobart
Where along your analytics roadmap are mathematical optimisation and artificial intelligence? BC: I would put it into the context of what we see in the UK, and also what we see in other global markets. We talk about our traditional originations
and underwriting: operational efficiencies aside from when underwriting was purely manual, customers demand that they want the decision pretty quickly and no human can do an algorithm in their head! If someone has got their defaults rates
wrong, then they either do not have enough data to predict effectively, or they are using the data wrong. If I look at some of the work that we are
doing in East Africa, where the average size of a loan is $6 – and you do not have a lot of resource that you can put to a $6 loan before you are over margin – it is all highly automated and less than 20% of the data used in the decisioning is financial, because it is mainly the unbanked. Analytics and data, and social data, is
proving that it can be used effectively. I get worried when we talk in a rather binary way – there is a lot of good practice in the UK at the originating end. Yes, we are highly geared, but our NPLs are not the highest by a long way. The regulator’s push on affordability is
forcing people to have to use data and to do the right kind of assessments to drive the right outcomes. It is interesting that, in most of the big institutions over the past three years, there have been major shifts in focus on getting their act together to drive the right outcome.
FH: Surely this is the way that it should be; it is a function of the credit cycle. If I had
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been working in 2008, but I lost my job because my employer went bust, then I should not be denied a loan today, if I had subsequently gotten myself out of that debt situation.
BC: To consider some statistics: two years before 2008, the average return to financial good that debt purchasers bought in the USA and UK was 2.5 years. Two years post-2008 it shrank to nine months.
Where we fail is that we do not go looking
for them as a particular cohort, we do not adjust our tolerance policies for them, and we do not adjust our strategies and we charge them off at 180 days and they get swept through with the rest of the portfolio. Those people should not be penalised today, because it was totally outside of their control, and they may have a default, but they may still have serviced their debt!
Analytics and data, and social data, is proving that it can be used effectively. I get worried when we talk in a rather binary way – there is a lot of good practice in the UK at the originating end. Yes, we are highly geared, but our NPLs are not the highest by a long way
The reason was that economic victims
behave in a totally different way to steady- state victims. They have very high financial morality
and they do not want to compromise on things, so they will take the third job and they will pull in their belts to service their debts to meet what they said they were going to commit to for their families. So, while the executives from Lehman
Brothers might have had a problem getting a job, most of the employees were back in work within three to six months.
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DST: From our debt-advice point of view, one of the main reasons that we are seeing people get into financial difficulty is because of relationship breakdowns. This kind of issue is impossible to predict when completing an affordability assessment, income shocks can strike anyone at anytime. We have done a survey with our clients,
once they become debt-free, between one and five years on, and 93% remain debt free. We need to be careful that we do not judge people too harshly and make them victims of their past. We need to recognise that many people learn for this experience and become more financially capable.
DS: From an underwriting point of view, every lender is different and each has their own requirements of risk and return, and this is heavily influenced by deep analytical insight. From a collections perspective, and in
particular, a debt-purchase perspective, I would say that the use of analytics has risen dramatically over recent years, particularly given the debt-purchase boom that has happened since 2009-2010. This is not so widespread amongst DCAs
however. There are other factors that can influence activities outside of a company’s resource capabilities and willingness to use
May 2018
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