Society, desperate to reverse the effects of global warming, finds a spare pound coin behind the couch cushions. This being an abstract thought exercise, we are allowed to consider only three possible options for the bounty.
Whether climate risk is actually a threat to financial stability has been a subject of ongoing debate. But a recent regulator-driven stress test has offered some clarity on this hot-button subject.
When narrative scenarios first became a standard tool for risk management, around the time of SCAP in 2009, I was frankly skeptical that the technique would last. Having emerged from academia, I was used to more rigorous methods and had spent years coding up very detailed and complex Monte Carlo experiments. I always thought that simulation methods, aided by advances in computing power, would eventually replace narrative scenarios for stress testing.
Sometimes you perceive something as a major risk, but the reality exposed by the data just doesn’t live up to your expectations. This is, in fact, what many modelers (myself included) experienced during the pandemic: expectations were constantly challenged by data.
Over the next 12 months, as COVID slowly wanes as an economic disruptor, a lot of industry credit risk models will be redeveloped. Historically, these methods have provided superior predictions to those based on gut feelings – but most of them were sidelined during the pandemic, because they were unable to explain the odd behavior that was unfolding. At some point, though, model owners will need to grapple with the unusual data and rehabilitate their quantitative models.
Consider a new pandemic scenario. In 2023, a pathogen will be discovered that, relative to COVID-19, is twice as deadly and five times as transmissible. It quickly becomes clear that vaccine development will be much more difficult than it was in 2020. Scientists estimate that 40% effectiveness is the best we can hope for, and that it will take at least three years to reach this level of development.
Honestly, this isn’t worthy of deep thought.
Last month, the European Central Bank published the results of its monumental TRIM project – a detailed five-year exercise to assess the internal models used by large banks to determine risk weights and regulatory capital charges.
As the world awakens, one of the vexed questions we face as model risk managers is when to redevelop. The simple fact is that the established procedure of designing and building a model, and then having it validated and implemented into various IT processes, is very cumbersome, time consuming and expensive.
In credit risk management, it is common to distinguish between point-in-time (PIT) and through-the-cycle (TTC) estimates of default probability or expected loss. But amid a unique pandemic, TTC loss forecasts may have been too bullish, and there is now talk about whether this credit risk estimation tool needs to be fine-tuned to reflect financial institutions’ new reality.
With COVID-19 vaccines now available, attention will soon revert to some of the other existential risks facing humankind. Top of the 2021 list for bank risk modelers, in the absence of new black swans, will undoubtedly be climate change. A number of key regulators have scheduled pilot stress testing projects in the coming year and the Bank of England has taken the bolder step of initiating a fully fledged regulatory stress test, known as the Climate Biennial Exploratory Scenario (CBES).