The banking industry is rapidly changing as leading financial institutions have begun using predictive modelling and price optimization to improve deposit pricing, improve balance sheet management, and optimize profit in a changing market environment. Banks require an understanding of their customers’ deposit price elasticity — how sensitive are they to pricing changes, and what is the relationship between price and demand at the customer, segment and portfolio level?
I’m going to explore this topic in a series of posts, which should be useful both to deposit portfolio managers and analytics teams. To start with, let’s look at the basics.
Price elasticity is the study of responsiveness, and how the demand of a product, in this case balance inflows and outflows, changes with respect to the applied interest rates and/or the market price derived from competitor bank interest rates). Understanding deposit price elasticity, or having models that predict this, means you can quantify:
- Impact of a product’s price change on expected balance
- How product balances react to the market, e.g., what impact does a competitor bank price increase have on the deposit portfolio
- Impact of changing macro-economic conditions, such as an increase in a central bank lending rate
- How a product’s price change will impact the overall deposit portfolio balance, taking account of product cannibalization and source of funds
A suite of deposit price elasticity models not only enables accurate forecasting of monthly balances for a new pricing strategy and ‘what-if’ analysis for events such as an increase in the central bank's interest rate. It also lends itself to price optimization, which leverages variations in elasticity to calculate optimal prices that maximize profit, where a simple forecasting tool cannot.
Deposit Pricing and Customer Behavior
Using analytics to understand customer behavior and elasticity is critical in establishing the deposit pricing strategy. A large number of potential characteristics can be considered in the modeling process, such as:
- Product details relative to the whole banking market, or different competitor peer groups
- Deposit product details relative to neighboring deposit products
- Existing customer product holdings with the bank, including those reaching product maturity, or the end of an introductory / bonus interest rate
- Macro-economic data including benchmark interest rates
- Brand & market awareness
- Monthly & seasonality trends, which impact might demand
- Indicator information (to take account of exceptional events)
The final model structure and characteristics are considered carefully to ensure robust relationships, across the suite of price elasticity models. It is also critical to understand how the models interact and perform on data more recent than what was considered for the model development, as well as outside of historical price points. This helps gain buy-in from the product teams who are going to be using the models to set pricing.
Benefits seen by banks from using price elasticity data driven models are:
- Deposit Portfolio Impact: To understand the impact of a pricing strategy on account applications, sales, and balance flows, taking account of monthly changes to competitor pricing, central bank interest rates, yield curves, and how the pricing strategy impacts other products.
- Source of Funds: To predict the source of funds, which help determine if a pricing strategy is resulting in net new balances or if the same balances are being cannibalized from older low-interest rate accounts to a new higher-rate account.
- Regulation: Not having statistically built models to make pricing decisions will be viewed as guesswork from subject matter experts. You need to be able to point internal auditors / regulators to a price elasticity model that has gone through the bank’s governance process.
A further benefit of price elasticity modeling is to make yourself more price-elastic, and review the deposit products you hold!
In my next post, you’ll learn about some of the challenges and requirements when building effective price elasticity models.
How FICO Can Help You Improve Deposit Pricing
- Explore our solutions for deposit price elasticity modeling and optimization
- Watch the webinar on Five Strategies for Driving Always-on, Intelligent Deposit Pricing Decisions
- Read the next post in this series: Modelling Deposit Price Elasticity: What Data Do You Need?
