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FRTB Roundtable: what you may have missed in our virtual roadshows
29 April 2021
We recently hosted a series of virtual roadshow meetings in
EMEA, North America and Asia to discuss the most recent
developments in the implementation of the Fundamental Review of the
Trading Book (FRTB).
We focused both on FRTB Standardized Approach (SA) as European
banks are finalizing their programme deliveries for a September
2021 reporting date and on FRTB Internal Model Approach (IMA) as
many banks are now looking to ramp up development after a hiatus
due to regulatory delays and uncertainty.
FRTB SA
For FRTB SA, the focus revolved around two main areas:
Reducing cost and increasing operational efficiency by
mutualising data and calculation infrastructure to maximise
synergies between risk measures e.g. FRTB-SA and ISDA-SIMM
Maximizing datasets and managing costs for FRTB-SA look-through
requirements across indices, ETFs and fund
With a growing shift towards cloud-native or at least
cloud-based risk architecture, now is the time to start looking at
the overlap between risk calculations and how to mutualise
infrastructure and development work for higher operational
efficiency.
We have indeed been discussing more and more projects straddling
teams and risk use cases with a view to maximise reusability and
switch from a siloed, segregated programme view to adding use cases
like add-on applications on a common platform - see a simplified
infrastructure example below:
With most of the input data originating from similar sources in
similar formats (even with varying coverage or depth), it makes
sense to centralise feed management and orchestration.
FRTB-SA and ISDA-SIMM for instance are both sensitivity-based
calculations using similar valuation components albeit with
slightly different configurations.
Similarly, the corresponding risk measures can be aggregated
using the same components with a different set of formulas.
And more importantly, such mutualised infrastructure allows for
all users to benefit from the same overarching features: resilient,
scalable production calculations with flexible what-ifs based on
consistent datasets, full drill-down capability into capital
measures but also intermediate results for reconciliation and
analysis and consistent end-user interactions in the reporting
layer or dedicated UIs.
FRTB IMA
As for FRTB IMA, two trends we have been seeing for a few years
now have firmly established themselves as high priority for both
banks and regulators:
What is the impact of recent market volatility on the Risk
Factor Eligibility Test?
How can IMA calibration be finalised in time for go-live while
understanding the interaction between all the moving parts (RFET,
NMRF proxying, PLA, Backtesting etc)?
On the former, we have regularly been publishing RFET
seasonality studies so we were used to seeing some volatility in
counts of modellable and non-modellable risk factors but even we
were surprised by the results of comparing 31-Dec-19 to
31-Dec-20.
Let's start with the clear winners of the period: the new
risk-free rates. We started monitoring SOFR and EuroSTR as the
first instruments started trading and we are happy to report that
all but one bucket are modellable:
When looking at asset classes in aggregate the trend is net
positive with a few nuances (and bear in mind that individual
banks' views of this will be filtered on their respective
exposures):
But the most interesting development we wanted to share with a
wider audience of banks were the findings of our most recent
studies, confirming a lot of the principles we have used to build
our solution: calibrating IMA properly potentially requires
numerous iterations between its moving parts:
From collecting the largest set of Real Price Observations
(RPOs) to maximise observability for existing risk factors but also
have a larger pool of modellability proxy candidates to select
from
To refining risk factor taxonomies to capture a realistic set
of RPOs
To maximising historical data to not only calibrate existing
risk factors but also increase the universe of suitable NMRF
proxies
To refining the proxy selection criteria themselves between
stable but sometimes inadequate rule-based methods to more dynamic
methods requiring regular recalibration
All of which while passing the P&L Attribution Test and the
backtesting requirements
Did you miss our roadshows? If you would like to discuss
recent FRTB developments
please reach out to us.
S&P Global KY3P® is proud to co-sponsor Vendor & Third Party Risk USA with our own Peter Pernebo speaking on 1 June… https://t.co/x9Sj4WxoBJ
May 12
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