In the previous article, we considered the client on-boarding process; in this second part, we will focus on the sales/advisory process. We will explain which machine learning (ML) models can be applied to which parts of the process. This is not an exhaustive view of the possible options and is meant as an opening to further discussion.
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There is a lot of buzz around artificial intelligence (AI) and machine learning (ML) and their application to financial services; specific examples include use cases applied to chatbots, robo advice, and credit risk scoring. Almost daily, articles are published focusing on specific functional areas, but do not address the potential of machine learning from an end to end perspective. This is the first of two lists whereby I document use cases by process area and potential use of ML algorithms and techniques. This initial list outlines AI and ML application to client on-boarding processes for new clients or for new products.
John Hucker outlines Switzerland’s credentials as a leading fintech hub, and its potential for further growth.
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