Identification of analytics use cases in Business Banking - a step by step approach

Use of advanced analytics and data science has gained traction in corporate and SME banking only recently. One struggle which the analytics teams have in these business segments have been having is that of use case identification. I had this struggle for long and I did a lot of research of solutions by consulting companies, foreign banks, Bank of International Settlement (BIS) etc.

I have tried to present my learnings in a simple and easy to understand format below. The description begins with the premise that all the businesses want to maximize profit. That is the left most column (not shown in the table). Then you start moving to the right and create a decomposition tree. Profit is split in two parts – revenue and cost. Then the revenue is further split in acquisition of new customers, increasing the price etc.

The guide below also gives an indication of the possible data sources and data science algorithms which can be used. Please note that the internal data sources have not been disclosed because these are confidential for every bank and can vary from bank to bank. The data science algorithms are one of the many possible. The list is not exhaustive and is supposed to act as a guide for identification of more use cases.?

Note - views expressed are personal