Machine learning and artificial intelligence are undoubtedly among the hottest topics in credit risk today.
As machine learning and artificial intelligence have become increasingly prevalent in finance, lenders look to their budding usage in decisioning and default prediction. Applying this technology to credit risk modelling has huge potential but also provides unique challenges which must be overcome to ensure success. However, despite much literature on the issue, articles and papers often fail to take into account the practical considerations of building and implementing such models in a credit risk setting.
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