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ReserarchID
KO5B8
Crossref Journal DOI 10.17406/gjcst
Print ISSN 0975-4350
e-ISSN 0975-4172
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Machine learning is one of the most exciting and powerful cognitive levers out there in the Industry and today Risk managers are grappling to make sense of whether it is just a hype or does it really have a value to add in Banking Risk Management. The article attempts to give a brief introduction into foundational concepts of machine learning and highlights some of the problems with the current predictive models and also some of the most popular pilot or candidate Use cases for Machine learning adoption. It also highlights the critical success factor which one needs to consider or be aware of in in adoption of Machine leaning to solve business problems. The paper intends to demystify the conundrum called as Machine learning and elucidate it to an extent which will enable the new age Risk & Regulatory managers to carefully evaluate and decide on an adoption of Machine learning techniques and solutions to solve specific Business problems.
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