Savings modelling series – How to determine core non-maturing deposit volume?
Low interest rates, decreasing margins and regulatory pressure: banks are faced with a variety of challenges regarding non-maturing deposits. Accurate and robust models for non-maturing deposits are more important than ever. These complex models depend largely on a number of modelling choices. In the savings modelling series, Zanders lays out the main modelling choices, based on our experience at a variety of Tier 1, 2 and 3 banks.
Identifying the core of non-maturing deposits has become increasingly important for European banking Risk and ALM managers. This is especially true for retail banks whose funding mostly comprises deposits. The last years, the concept of core deposits was formalized by the Basel Committee and included in various regulatory standards. European regulators consider a disclosure requirement of the core NMD portion to regulators and possibly to public stakeholders. Despite these developments, a lot of banks still wonder: What is core deposits and how do I identify them?
FINDING FUNDING STABILITY: CORE PORTION OF DEPOSITS
Behavioural risk profiles for client deposits can be quite different per bank and portfolio. A portion of deposits can be stable in volume and price where other portions are volatile and sensitive to market rate changes. Before banks determine the behavioural (investment) profile for these funds, it should be analysed which deposits are suitable for long-term investment. This portion is often labelled as core deposits.
Basel standards define core deposits as balances that are highly likely to remain stable in terms of volume and are unlikely to reprice after interest rate changes. Behaviour models can vary a lot between (or even within) banks and are hard to compare. A simple metric such as the proportion of core deposits should make a comparison easier. The core breakdown alone should be sufficient to substantiate differences in the investment and risk profiles of deposits.
"A good definition of core deposit volume is tailored to banks’ deposit behavioural risk model."
Regulatory guidelines do not define the exact confidence level and horizon used for core analysis. Therefore banks need to formulate an interpretation of the regulatory guidance and set the assumptions on which their analysis is based. A good definition of core deposit volume is tailored to banks’ deposit behavioural risk model. Ideally, the core percentage can be calculated directly from behavioural model parameters. ALM and Risk managers should start with the review of internal behavioural models: how are volume and pricing stability modelled and how are they translated into investment restrictions?
SAVINGS MODELLING SERIES
This short article is part of the Savings Modelling Series, a series of articles covering five hot topics in NMD for banking risk management. The other articles in this series are:
Savings modelling series – Calibrating models: historical data or scenario analysis?
Low interest rates, decreasing margins and regulatory pressure: banks are faced with a variety of challenges regarding non-maturing deposits. Accurate and robust models for non-maturing deposits are more important than ever. These complex models depend largely on a number of modelling choices. In the savings modelling series, Zanders lays out the main modelling choices, based on our experience at a variety of Tier 1, 2 and 3 banks.
One of the puzzles for Risk and ALM managers at banks the last years has been determining the interest rate risk profile of non-maturing deposits. Banks need to substantiate modelling choices and parametrization of the deposit models to both internal and external validation and regulatory bodies. Traditionally, banks used historically observed relationships between behavioural deposit components and their drivers for the parametrization. Because of the low interest rate environment and outlook, historic data has lost (part of) its forecasting power. Alternatives such as forward-looking scenario analysis are considered by ALM and Risk functions, but what are the important focus points using this approach?
THE PROBLEM WITH USING HISTORICAL OBSERVATIONS
In traditional deposit models, it is difficult to capture the complex nature of deposit client rate and volume dynamics. On the one hand Risk and ALM managers believe that historical observations are not necessarily representative for the coming years. On the other hand it is hard to ignore observed behaviour, especially when future interest rates return to historic levels. To overcome these issues, model forecasts should be challenged by proper logical reasoning.
In many European markets, the degree to which customer deposit rates track market rates (repricing) has decreased over the last decade. Repricing decreased because many banks hesitate to lower rates below zero. Risk and ALM managers should analyse to what extent the historically decreasing repricing pattern is representative for the coming years and align with the banks’ pricing strategy. This discussion often involves the approval of senior management given the strategic relevance of the topic.
"Common sense and understanding deposit model dynamics are an integral part of the modelling process."
IMPROVING MODELS THROUGH FORWARD LOOKING INFORMATION
Common sense and understanding deposit model dynamics are an integral part of the modelling process (read our interview with ING experts here). Best practice deposit modelling includes forming a comprehensive set of interest rate scenarios that can be translated to a business strategy. To capture all possible future market developments, both downward and upward scenarios should be included. The slope of the interest rate scenarios can be adjusted to reflect gradual changes over time, or sudden steepening or flattening of the curve. Pricing experts should be consulted to determine the expected deposit rate developments over time for each of the interest rate scenarios. Deposit model parameters should be chosen in such a way that its estimations on average provide a best fit for the scenario analysis.
When going through this process in your own organisation, be aware that the effects of consulting pricing experts go both ways. Risk and ALM managers will improve deposit models by using forward-looking business opinion and the business’ understanding of the market will improve through model forecasts.
SAVINGS MODELLING SERIES
This short article is part of the Savings Modelling Series, a series of articles covering five hot topics in NMD for banking risk management. The other articles in this series are:
