A lot has been happening in the world lately, well, certainly in my world. I decided to write a book. It's about Retail Consumer Credit Risk Analytics. I would love to have it published by Christmas.
I've also been reading up on things. And doing research - by research, I mean I have been reading about what other people have been doing.
One of the challenges with being a deeply curious person is that I can get quite easily distracted by topics. Then I read up on them. Some of these topics only hold my attention fleetingly. Other topics stir a deep fascination, and can hold my attention for a while longer.
Credit Risk Analytics is one such topic. It has held my attention for years.
I was recently speaking to a mentor of mine, we were chatting about how I'm stepping out of the analytics role itself, and more into a mentor/coach role for analysts as they step up in their journey. He asked me whether I missed the detail of the analytics.
That's an interesting question.
Whilst a part of me misses the analytics, a bigger part of me is truly excited about helping, coaching and mentoring the next generation of Credit Risk Analysts. Credit isn't going anywhere. We have the usual suspects: Banks, Retail Finance etc.
We also have FinTechs, and niches popping up, the same skills are required. I, and everyone I have spoken to - many of whom are seasoned analysts who are now Head of various Departments, (Card, Loans, Risk etc) we all learned the skills from those who went before us. It's not like you can come out of university with a degree in retail consumer credit risk. Yes, some people have degrees in maths, or stats, perhaps operational research. I know a couple of physicists. Key commonality - numerate and pretty bright.
Many of the "go to" analytical tools haven't changed, and are unlikely to change. As a rule of thumb, Credit Risk Analysts need to have a decent grasp on basic analytics - importing data, making sure that it has been imported correctly. Exploratory Data Analysis (EDA), data validations and descriptive analytics. This is not new (although some of the naming conventions are). It's as important now as it was back in the "olden" days, when we worked on PCs and 256MB of RAM was a LOT!!!
It is arguable that there was this one brief moment in time when some of these skills were less essential - that brief period where data was sitting all beautifully scrubbed and sorted in a data warehouse, before the advent and seemingly ubiquitous adoption of data lakes...
During that window, as an analyst, you could be confident that the data was what it said it was, that it was accurately updated and populated. Should something 'odd' happen, there would be a notification and, usually, data would be 'fixed' or it would be well known and documented that the data in question should not be used.
Credit Risk Analysts need to have a good understanding of the lingua franca of Credit Risk Analytics. It can seem like a bit of a secret club to those who have not been initiated. With a solid grasp on the language and concepts of Credit Risk Analytics, you need to understand how the different 'bits' fit together, you need to know how to work out whether something is a good idea or a bad idea, you need to be able to unpack which parts of a 'thing' might be worth saving, what should change and the impact that would likely have. That impact is not reserved for on the impact on the Good/Bad Odds or Bad Rate. There will likely be an impact on losses, perhaps on approval rates, perhaps on provisions. Often disregarded, is the likely impact on the Operations Teams.
The Credit Risk Analyst who disregards the impact of change on the Operations Team does so at their peril.
Back to the question: do I miss doing the analytics? In short, no, not really. I've always done the analytics to understand why I see what I see. To understand what we could, or should, do differently. For me, the analytics are a means to the ends. Over the past decade or so, I've worked with analysts, helping them ask the right questions. And then unpack what the answers are actually telling them. Fortunately, coaching and mentoring analysts as they step up on their journey means that I still get to do that.
My mission is to help more aspiring credit risk analysts learn the key skills needed to effectively analyse and unpack what's happening, and then figure out what a 'do nothing' approach would mean. And if the impact of the 'do nothing' approach is unpalatable, what should we do instead.
Comments