The Data Analytics Blog

Our news and views relating to Data Analytics, Big Data, Machine Learning, and the world of Credit.

Thomas Maydon

Thomas Maydon

Thomas Maydon is the Head of Credit Solutions at Principa. With over 17 years of experience in the Southern African, West African and Middle Eastern retail credit markets, Tom has primarily been involved in consulting, analytics, credit bureau and predictive modelling services. He has experience in all aspects of the credit life cycle (in multiple industries) including intelligent prospecting, originations, strategy simulation, affordability analysis, behavioural modelling, pricing analysis, collections processes, and provisions (including Basel II) and profitability calculations.

Recent Posts:

Model validation and adjustment

The time is NOW for model validation and adjustment. One of the major premises used in credit scoring is that “the future is like the past”. It’s usually a rational assumption and gives us a reasonable platform on which to build scorecards whether they be application scorecards, behavioural scores, collection scores or financial models. That is reasonable until something unprecedented comes along. You can read about this black swan event in our previous two blogs here and here.

Payment holidays – what did everyone do?

Payment holidays have been used throughout South Africa and around the world to help alleviate the economic stress during the COVID-19 lockdown. In this blog we look at some of the steps taken internationally and by some of South Africa’s major lenders (specifically in the consumer space).

Psychometrics in credit originations

If 2020 was not hit by the COVID-19 global pandemic, many were touting 2020 as the year of alternative data. In the credit assessment world, data has typically incorporated demographic data and credit bureau data (where available), but now we are seeing alternative data playing more of a role namely in cellular behavioural data and psychometrics.

Shift happens: Top tips on Scorecard re-alignments

Principa employs a variety of best-practice credit scorecard building techniques including mathematical programming, regression modelling, optimal segmentation-seek genetic algorithms and reject inference parceling, amongst others. Through our credit risk scorecards businesses can look to improving their credit risk decisioning by 5-30%.

How Quick-Step Machine-Learning Models will help you through COVID-19

In a previous blog, we looked at assessing your credit models and the challenge of building and deploying models representative of the COVID-19 crisis. At the crux of the challenge was the fact that:

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