In this 2-day workshop (live and webcast), we review lessons learned from the last several business cycles, including what banks missed and why they missed it – we will been keenly focused on the 2004-6 rate cycle, which was the last time in the US that we experience a material increase in interest rates. Drawing on these lessons, I describe how risk and profitability management are one in the same problem; they cannot be treated as separate and distinct, else the result will be conflicting stories of how the financial institution (FI) makes money.
Following a brief discussion on the sources of interest rate risk (IRR) and liquidity risk (LR), I show how a well-functioning funds transfer pricing (FTP) process immunizes lenders and deposit gatherers against these risks. This is a key motivation for lenders and deposit gatherers to embrace FTP. Without it, they are exposed to risks over which they have no control.
I provide a detailed description of the mismatch center and explain how it should contain all IRR- and LR-related earnings and earnings volatility. In a well-functioning FTP framework, the earnings risk profile of the FI and the earnings risk profile of the mismatch center should be identical regardless of the risk profile of the FI.
The feedback from the FTP Conference participants was nothing short of excellent. Several product managers have reported that the workshop has positively influenced their decisions around which deposit products to promote and how they will price and manage them to maximize their value to their business units AND to the bank. – Director, Funds Transfer Pricing, Royal Bank of Canada
Given that non-maturity deposits (NMDs) make up a material source of funding at most FIs, I describe a method of calculating the FTP rates on NMDs that follows logically from their IRR and LR cashflow attributes. This approach compels deposit gatherers to consider how product behaviors (over which they have some control) drive the crediting rate they receive, i.e. the FTP rate is not arbitrarily imposed on them. This understanding produces significantly more accurate measures of IRR and LR for the FI. This discussion is particularly germane given the excess deposits that currently plague the system – how sticky are they and how rate sensitive are they? Past behaviors may not be entirely helpful, so having a behavioral model that provides real time feedback is essential to detecting behavioral changes which may have material implications for risk and profitability.