Stress Testing – Confluence of the Actuaries and Economists Viewpoints
How can actuaries and quantitative professionals involved with stress testing help their organisations derive more value from the practice? Sen Nagarajan and Michael Thomas give us an overview of their 2017 Actuaries Summit presentation on stress testing.
Stress testing is now accepted as a key tool for understanding capital requirements, selecting capital management tools and testing resiliency under extreme but plausible conditions. Regulators have also embraced stress testing as part of their supervisory processes, with regular industry wide stress tests run across banks and insurance companies.
Stress testing in many organisations is not well utilised in broader business management, other than in ICAAP. How can actuaries and quantitative professionals involved with stress testing help their organisations derive more value from stress testing?
Involving economists in the design of stresses and in the modelling of impacts can add significant value. Economists in particular can provide insights into how scenarios can propagate through the economy and how this then impacts the organisation through its business drivers. In our presentation, we recap how stress testing has evolved, and then provide examples on how an economist’s perspective can help to better understand macroeconomic stresses. Banks in particular use macro-economic stress testing extensively given the obvious link between economic conditions and credit defaults. Banks have developed models to translate economic scenarios into financial drivers such as defaults, net interest margins and market valuations that determine the capital requirements from a regulatory and economic capital perspective.
The relevance of macroeconomic stress testing for life and general insurers is mixed. Life insurers are diverse with a mix of conglomerates, specialised insurers and reinsurers. The relevance of macroeconomic stresses varies depending on the particular lines of business that a life insurer offers. Similarly macro-economic stress tests are relevant to general insurers with exposure to specific lines such as lenders mortgage insurance and trade credit.
While financial institutions have developed sophisticated models and have invested in stress testing infrastructure, there are some areas where stress testing is not as well utilised. This is due to a combination of the following factors:
- The use of national aggregate scenario does not provide insight into financial institution’s specific exposures both in regional, type of lending and industry. APRA for example considers a granular view of risk an important part of mortgage portfolio management “Good practice would be for an ADI to conduct stress testing at a sufficiently granular level to enable adequate sensitivity to the risk characteristics of different loan types. These characteristics would typically include product type, LVR, LMI coverage (including counterparty credit risk), serviceability, geography, vintage, origination channel and borrower characteristics.” APG 223, Residential Mortgage Lending.
- The models used may not directly look at outcomes across connected parts of the economy such as GDP, interest rates, currency rates, terms of trade etc. According to Wayne Byres “Some models still rely too heavily on a single economic driver or judgement alone, lacking a convincing link to the scenario or taking a high-level approach that misses the differences in risk across different types of asset.”
This is where economic thinking and modelling can be used in the stress testing process to augment the statistical and financial models developed by actuaries. In particular, economists have developed models that can flow a scenario through components parts of the economy to provide a richer picture of impacts across regions and industries. Previous downturns show that the impact of macro stresses can vary greatly between industries and regions. Further the impact is very sensitive to the source and nature of the macro economic shock.
In the recession of the 90s the house price impacts and unemployment increases were not distributed equally. The output by state differs during the period of the 1990s for example Victoria saw a marked dip in Gross State Produce relative to NSW.
This is also reflect in unemployment rates.Unemployment is a key driver of default in lending asset classes such as mortgages and personal loans.
The differences observed at a state level are driven by the exposure that each state has to industries. Industries in turn react differently in terms of timing and depth of downturn. The source of the stress also impacts the outcome. For example industries with an export focus can benefit from currency movements that improve their competitiveness despite a downturn across the broader economy. This is where the complex interplay between interest rates and currencies can play a significant role in how a macro economic stress plays out. The chart shows how output and employment in each industry changed over the period of the 1991 recession:
Economists’ models capture these interactions. Using these insights in stress testing can identify pockets of the lender’s portfolio that are exposed to particular shocks. Incorporating these into stress test can provide information that can be used in risk identification, risk limit setting, concentration risk measurement and pricing.
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