Savings modelling series: The impact of savings rate floors on balance sheet management
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.
The low or even negative market rates in many Western European countries significantly affect banks’ pricing and funding strategy. Many banks hesitate to offer negative rates on non-maturing deposits (NMD) to retail customers. In some markets, like in Belgium, regulatory restrictions impose a lower limit on the savings rate that a bank can offer. The adverse impact of these developments is that current funding margins for many banks are under pressure.
The flooring effect on variable rate deposits is a hot topic for banks’ Risk Management functions due to its impact on the pricing dynamics and customer behaviour. Although it is possible that banks offer negative deposit rates when interest rates continue to decrease (“soft flooring”), banks depend on the pricing strategy of competing banks. Next to that, offering negative rates can cause serious reputational damage, leading to deposit volume outflows. The next paragraphs outline the key focus regarding risk reporting, economic hedges, and risk models for Risk and ALM managers.
BREACHING THE SUPERVISORY OUTLIER TEST
Banks are likely to hit the Supervisory Outlier Test (SOT) because of the asymmetric sensitivity of the economic value to interest rate shocks. Banks must inform their supervisor when the Economic Value of Equity change resulting from specific interest rate scenarios exceeds certain thresholds. Asymmetric pricing effects on NMD can have substantial impact on economic value and earnings. This is because when NMD rates are close to the floor, the interest rate sensitivity decreases. This effectively makes NMD similar to fixed-rate instruments like bonds.
"Banks are likely to hit the Supervisory Outlier Test (SOT) because of the asymmetric sensitivity of the economic value to interest rate shocks."
Risk Management functions need to adjust the Economic hedge to mitigate the interest rate typical gap between assets and liabilities. While NMD are traditionally variable-rate products, these behave more like interest rate insensitive instruments in a low interest environment. Risk managers need to reflect this impact in the economic hedge. It is important to realize that it is difficult to capture the non-linearity of NMD, resulting from the floor, with linear financial instruments such as interest rate swaps. Although some banks are adjusting the hedge on a best-estimate (duration or DV01) basis, the asymmetric pricing effects will largely be left unhedged. Banks can choose to accept and monitor this risk, or capitalize for it.
Risk models need to be adjusted to reflect flooring effects on NMD. For most Western European markets, historical data is dominated by higher interest rate levels and does not yield representative behavioural risk estimations.
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: Non-maturing deposits model concepts
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.
Are you interested in a more in-depth comparison of deposit modeling concepts? Click here.
For banks with significant non-maturing deposits portfolios, Risk Management functions need to have a robust behavioural risk model. This model is required for Interest Rate Risk in the Banking Book reporting, hedge, stress testing, risk transfer, and ad-hoc analyses. Although specific modelling assumptions vary per bank, cashflow-based models, a replicating portfolio model, or a hybrid model are market practice model concepts. The choice for one of these models is strongly linked to model purpose and use. Each concept has its benefits and drawbacks for different purposes and uses.
CASHFLOW-BASED MODELS
Cashflow-based models consist of two sub-models for the deposit rate and volume that forecast coupon and notional cashflows, respectively. Both sub-models measure the relationship between behavioural risk and underlying explanatory factors. Cashflow-based models are suited to include asymmetric pricing effects (such as flooring of rates) in resulting risk metrics. Since the approach captures rate and volume dynamics well, it is also often used for ad-hoc behavioural risk analysis and stress testing.
"The choice for one of these models is strongly linked to model purpose and use."
REPLICATING PORTFOLIO MODELS
Replicating Portfolio models replicate a deposit portfolio into simple financial instruments (e.g., bonds) such that its risk profile matches the risk profile of the underlying deposits. The advantage is that it converts a complex product into tangible financial instruments with a coupon and maturity. This simplified portfolio is well-suited to transfer risk from business units to treasury departments. A disadvantage of the model is that it does not fully capture non-linear deposit behaviour, for example the asymmetric pricing effects resulting from the floor. This makes the approach less suited for stress testing or ad-hoc behavioural risk analysis for senior management.
Read our extensive analysis of replicating portfolio models here.
HYBRID MODELS
Hybrid models, consisting of both a cash flow model and replicating portfolio model, combine the benefits of the other approaches, but at the cost of increased complexity. These models are often used by banks that want to use the model for a wide range of purposes: risk transfer to treasury departments, risk reporting, ad-hoc behavioural risk analysis, and stress testing. To prevent a larger mismatch between the models, most banks ensure that the risk profiles (duration or DV01) of both models align.
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 – 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: