Giving credit credit in the board room, with Marlize Buys
Data analytics is no longer an isolated and arcane backroom activity to be understood by only a handful of geeks, it's at the core of every successful lending business.
For those of us that have grown up in data science, that's great news, but that rising prominence also means that a new audience must now come to terms with the implications of machine learning versus logistic regression scores, with gini coefficients and information values and bins and weights, etc. And that new audience is an important one: the Board.
Marlize Buys started her career getting hands-on with credit scorecards, then she helped to build a lending business of her own, and now she is advising the boards of major banks with that particular transition.
Marlize has been so busy optimising lending businesses that she hasn't quite got her website up and running, but Most Probably is on LinkedIn at https://www.linkedin.com/company/most-probably/
Or you can speak to her directly https://www.linkedin.com/in/marlizebuys/
I'm on LinkedIn, too, at https://www.linkedin.com/in/brendanlegrange/
As is the show, please follow its page at https://www.linkedin.com/company/how-to-lend-money-to-strangers/ (once you have followed, look for the circle with the three dots in the header section, click that and then 'invite connections' and invite any of your colleagues who you think might like the content
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Keep well, Brendan