New regulations drive changes to
behavioral modeling for IRRBB
The focus regulators put on the behavioral modeling of non-maturing deposits and embedded options in
the recent EBA and BCBS regulation for Interest Rate Risk in the Banking Book (IRRBB)1 demonstrate the
key role it plays for IRRBB. Both the EBA and BCBS papers cover the same types of positions and
customer behavior risk (prepayment, early redemption, loan commitments and non-maturing deposits)
and set new requirements within a Pillar II treatment of customer behavior. Within this framework,
banks have a relative large freedom to develop models that suit their structure and risk strategy. In
addition, the BCBS consultation paper suggests a standardized Pillar I approach to calculate regulatory
capital, which includes a model for non-maturing deposits and loans and deposits with embedded
options. This is a hybrid approach where each bank is allowed to parameterize the predefined model as
an alternative to using the parameterization given by the regulator.
Non-maturing deposits are characterized by the fact that their realistic repricing differ substantially from
the contractual agreed. Under both the BCBS Pillar I hybrid approach and the new Pillar II regulation,
banks are expected to divide these deposits into a core part and a non-core part. The core part has
stable volume and is insensitive (non-pass-through) to market interest rate changes and therefore has a
much longer average repricing profile than the non-core part, which has a transient character and a
short repricing date. An expression of the higher degree of freedom under Pillar II is, that banks can
define their own deposit parameterization clusters while under Pillar I there are regulatory pre-defined
clusters.
The current low interest
rates and the expected
future renormalization of
interest rates, lead to changes
in the customer behavior.
A large percentage of most
bank’s assets and liabilities are
sensitive to these behavioral
changes as they do not have a
contractual maturity or
repri-cing (e.g. customer sight
deposits) or contain embedded
options. To be able to measure
and hedge the interest rate risk
of such positions effectively
and thereby stabilize their
value and earnings, banks
implement models to estimate
the customer behavior.
FIGURE 1: THE IDENTIFICATION OF CORE DEPOSITS IS THE CORNERSTONE OF THE REGULATORY
APPROACH TO NON-MATURING DEPOSIT MODELING
Non-maturing deposits
Stable volume
Interest insensitive
Core (to be modeled)
Fluctuating volume
Interest sensitive
Non-core
Embedded options lead to interest rate sensitive uncertainties in the repricing profile. Under the BCBS
Pillar I hybrid model, the way the options are parameterized is predefined. Banks should estimate option
exercise rates for three types of embedded options per predefined interest rate scenario and per
homogeneous portfolio. These are prepayment of fixed rate loans (expressed as Conditional Prepayment
Rate), draw down of fixed rate loan commitments and early redemption of term deposits. Under Pillar II,
the regulators expects banks to model all material embedded option types and, depending of the
complexity of their business model, design behavioral scenarios that can be integrated with advanced
IRRBB stress testing (e.g. modeling of second round effects).
(2015) EBA, “Guidelines on the management of interest rate risk arising from non-trading activities” & BCBS “Consultative Document ‘Interest rate risk in the banking book’”
1
To assist banks to leverage behavioral modeling in the IRRBB framework, BearingPoint has developed an
approach that provides financial institutions with a potent input for interest rate risk calculations. It is a
structured approach to generate cash flow and repricing profiles consistent with regulatory requirements
and can serve as a basis for risk management, stress testing and planning. The modeling is based on
statistical analysis of historic interest rate and behavioral time series data. It identifies trends (periodic
and non-periodic), the sensitivity of those trends to changes in the interest rate and potential fluctuations around the trends. The result of the statistical analysis is then used to create behavioral scenarios
consistent with the relevant interest rate scenarios.
Governance
Conception
BearingPoint’s approach to behavioral modeling helps
to create value
FIGURE 3: A STRUCTURAL
APPROACH TO BEHAVIORAL
MODELING HELPS TO ACHIEVE
FULL COVERAGE AND REGULATORY COMPLIANCE
Implementation
The behavioral modeling is one of the core elements of the new IRRBB framework where the banks can
take advantage of the given degrees of freedom. Particular in the proposed BCBS Pillar I hybrid
approach, the freedom to make internal estimates of behavioral parameters is one of the few available
optimization levers and can ultimately lead to reduced capital requirment.
Process
Methods
IT-Architecture
(Data, Systems)
FIGURE 2: TREND ANALYSIS, RISK MEASUREMENT AND SCENARIO GENERATION ARE THREE
MAIN STEPS TO MODEL CUSTOMER BEHAVIOR
Statistical analysis
of historic data
Trend
analysis
Risk
measurement
Forecasting
Behavioral
scenarios
The starting point for all behavioral models is the identification of homogenous portfolios based on
static product and customer type properties. To validate the potential clusters and to perform the
statistical analysis of the behavior modeling, long historical time series of high quality, segmented
customer behavior data, with a sufficiently high frequency, are needed. In addition, historic as well as
current interest rates curves are needed for the analysis and scenario generation.
To set up regulatory compliant behavioral models an initial analysis highlights the gaps between current
policies, processes and modeling methodology and the new regulatory requirements. In addition, the
gap analysis identifies areas where further development can optimize the use of risk capital, improve
hedging of interest rate risk and achieve better integration with related processes (e.g. business
planning). An impact study is used to evaluate how changes due to the new regulatory requirement and
identified additional improvement will affect the interest rate risk and balance sheet management. It
will quantify the impact of an improved modeling methodology and parameterization on both economic
value and earnings based interest rate risk measures. The results of the impact study is used as the
business case for to the design and implementation of the new behavioral models and their parametrization logic.
Contact
About BearingPoint
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resulting complexities demand intelligent and adaptive solutions. Our clients, whether in commercial or
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and engage with them for measurable results and long-lasting success.
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© 2015 BearingPoint GmbH. FC 1035 DE
Thomas Steiner
Partner
[email protected]