Banking Analytics by Ms. Anna Michael, CFA

Contributed By :Sri Siva Shankar R., CFA

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On 22nd February, the Bangalore chapter of CFA Society India hosted Ms. Anna Michael to conduct a session on Banking Analytics. Anna Michael is a CFA charter holder and the Head of Trade and Treasury Solutions Analytics in Citi. She has over 20+ years’ experience in banking and has taken up roles in Institutional Banking, Consumer Banking and Investment Banking.

Anna started the session with an introduction to the importance of visualizing a data set and explaining the tools and techniques used to visualize a data set viz. dashboards, Tableau, Qlikview, PowerBI. These data sets can help us to understand consumer behaviour. Harnessing the power of data science, prescription analytics can be employed to understand which RMs are more effective than others for instance, or predictive analytics could be used to forecast cash flow for a customer. Recommendation systems can help us understand what to recommend to a customer, when to recommend and whom to recommend a product to.

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In the last decade, the volume of data and the velocity at which it comes to companies has been only growing. Also, computational power and the network bandwidth available to process this data has grown exponentially. With the advent of open banking, not using these new age technologies could potentially lead to loss in revenue.

Banks have a fiduciary responsibility to protect their client’s data. This acts a primary constraint for the banks when they try to employ new age technologies. They constantly work on solutions like setting up control systems to ensure there is no breach when using a third-party technology or replicate the algorithms in-house to remove threats and stay competitive. While this does take significant time and effort, the banks have now realized the power data holds. Anna rightly quoted that earlier, “Rivers defined where cities are, then money defined where cities are, (but) today, money is where data is”.

Anna then walked us through the life cycle of a data science project explaining the steps taken from conceptualizing the business requirement to deployment, and the roles people take on in a data science project. This was followed by an intense Q&A session by the audience. Questions ranged across how regulatory challenges is an integral part of the banking process, how it makes sense for traditional banks to collaborate with startups, and what new skillsets in Data Science CFAs need to develop to upgrade themselves on a continual basis.

 



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