Of Broker Dealers, Machine Learning, Capital Utilization, and Profitability

Over the past couple of years I have had the good fortune to discuss the need for improved understand of profitability and capital utilization in broker dealers. Frustrations abound. Discussions on the need to find the right clients to meet the balance sheet utilization mix meander with no clear end in sight.

Investment managers are moving their books of business, not based upon desire, but based upon the BD needing to achieve the correct balance sheet mix.

BDs are looking at return on capital as much as profitability of clients.

Machine learning is a field of artificial intelligence that involves developing self-learning algorithms. Not trading algorithms as we all know, but rather algorithms that provide insight and suggestions. Our goal is that these self learning algorithms and visualizations help highlight and suggest real actions that can be taken.

Moving from suggestions to a substantive, informed discussions clients is the real goal. Discussion topics now need to cover such broad topics as:

• Asset class mix,

• Security on deposit,

• All in or “a la carte” pricing,

• Mix of execution only, clearing only and full service accounts,

• Technology utilization,

• Market data,

• Risk profiles,

• And more

In the end, all broker dealers, their banks, and their clients need to examine not just their activity, but how they are going to react.