The rise of machine learning promises a new way of delivering successful outcomes and solutions across a plethora of industries, services and applications. Finextra brought this interesting topic to our attention in their article, “How Machine Learning is changing credit decisioning forever.”
In the finance world, machine learning has been widely used in areas such as fraud. However, now organizations are beginning to incorporate it into their credit-risk decisioning processes.
Machine learning is a method of data analysis that automates analytical model building. As a branch of artificial intelligence (AI), it is based on the idea that systems can learn from data, identify patterns and make decisions with minimal human intervention. So how does that work with credit assessments?
In credit scoring, traditional scorecards are developed using numerous variables. During the pandemic many of these variables have changed drastically resulting in less accurate predictability. There is a need to recalibrate scorecards post-pandemic and that is where machine learning steps up.
Most organizations have little visibility and knowledge on how AI systems make the decisions they do, and as a result, how the results are being applied in the various fields. Explainable AI allows users to comprehend and trust the results and output created by machine learning algorithms.
Melody K. Smith
Sponsored by Data Harmony, harmonizing knowledge for a better search experience.
