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:

Account Management Credit Strategies: A profitable Pursuit (Part 2)

In our previous blog we introduced the value of effective account management strategies.  In this blog we continue to run through different account management decision areas. In our next blog we will discuss what is needed for an effective account management strategy.

Account Management Credit Strategies - A Profitable Pursuit: Part 1

Onboarding good new customers in a very competitive market is difficult and not always that profitable. That is why prudent credit managers often look to account management strategies to reap the greater rewards. Once a customer is on-boarded and has proved herself to be an exemplary re-payer, offering her money is more of a sure-thing for repayment.Behavioural scorecards offer far better Ginis than application scorecard. This means you can afford to be more aggressive in account management.

10 ways of combating application fraud Part-2

In our previous blog, we covered five steps to help lenders avoid application fraud. Application fraud has been an increasing blight on credit books particularly with the growth in digital channels. In this blog we explore another five fraud-mitigation steps.

10 ways of combating application fraud (part 1)

New technology gives the promise of greater enablement. But some of the shrewdest entrepreneurs understand that opportunity comes from the unintended consequences of new technology. So, let us take digitalisation of the loan application process: the opening of digital channels has enabled lenders to service their customers 24/7 and through APIs integrate with a host of sophisticated services. However, the advent of the digital channel has meant more opportunity for fraud.  The question to ask is:

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

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