The Data Analytics Blog

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

All Posts

Collections Analytics: The Why and How

June 21, 2020 at 4:24 PM

As most of you may know by now, we are currently busy with a series of Q&A videos, so please feel free to send us your credit lifecycle related questions, or any questions relating to our products or services.

In today’s video, we look at a question from Justin May: “Hi Perry, what are the main advantages of investing in predictive modelling, especially preferred instalment models, and how would you operationalise these models to be used within a call centre?

In order to answer Justin’s question, we are going to answer the following questions:

  1. Is there a need for such an analytical model? And …
  2. How would I operationalise the outcome of such a model?

Contact Us to Discuss Your data analytics Business Requirements

Perry de Jager
Perry de Jager
Perry has been involved in Collections and Recoveries for the past 22 years, spending time in different market segments ranging from law firms to investment companies. At Principa, Perry has worked on extended projects within both South Africa and the Middle East with some of the largest financial organisation, providing on-site consulting within the collections and recoveries space covering strategy, process, people and technology.

Latest Posts

The Pros and Cons of a Multi-Bureau Strategy in Credit

Although not a new concept, very few lending organisations have deployed a true multi-bureau strategy (MBS). It is however talked about fairly regularly, but often dismissed as “too hard” or “not important enough”. So why should you consider a multi-bureau strategy? What are the key considerations? How do you go about deploying a MBS? This blog hopes to address all these questions.

PART 1: How to Cure the Post Pandemic “Collections” Symptoms

It has been a year and a half since the first case of the coronavirus (COVID-19) was reported from Wuhan, China. As we move into the third wave of the virus, there is an apparent dilution in both collection and recovery yields in the financial services sector, primarily because relief schemes and packages come to an end.

Predicting Customer Behaviour

Propensity modelling attempts to predict the likelihood that visitors, leads and customers will perform certain actions. It’s a statistical approach that accounts for all the independent and confounding variables that affects said behaviour. The propensity score, then, is the actual probability that the visitor, lead, or customer will perform a certain action.