everis was Gold Sponsor of the Marcus Evans Conference ‘4th Edition: Impact of the Fundamental Review of the Trading Book’ at Canary Wharf, London on 23-24th February 2017. This was a timely opportunity to catch up with banks and solution partners as we move into the implementation phase of Fundamental Review of the Trading Book (FRTB) programmes. We heard views and case studies across a range of topics including market risk methodology, operating model definition and data and systems architecture design. Our presentation at the conference focused on the architectural challenges posed by FRTB.

1. Fundamental Review of the Trading Book
Business model and IT architecture evolution
London, February 2017

2. everis 2
Fundamental Review of the Trading Book (FRTB)
FRTB impacts expand far beyond new risk metrics and Internal Model Approach approval
requirements. Efficient controls, analytical tools and capital-driven decision-making will be
essential for success in the post-FRTB business environment.
FRTB compliance
•New Standardised
Approach (SA)
framework
•New Internal Model
Approach (IMA)
framework
•IMA approval
constraints
•Open issues still under
discussion
Constraints, controls
and analytical tools
•P&L attribution
process
•Unexplained P&L, ES,
DRC decomposition
•Modelling SA/IMA
transitions
•High-performance
computational
capabilities
Capital-driven
decision-making
•Modelling trading
desk allocations
•Alignment with wider
capital framework
•Risk-adjusted ROC
optimisation
•Back-testing, What-If
simulation and
portfolio reallocation
 FRTB prescribes an increased alignment between Front Office and Risk Management in terms of risk
metrics, models and conventions leading entities to rethink entirely their existing IT architectures.
 New metrics such as Unexplained P&L and Expected Shortfall demand increased transparency from the
risk aggregation processes to enable analysis. In-memory analytics explored as the only way to achieve
performance required for intraday capital-driven decision-making.
 Effective cross-functional governance is critical for the successful delivery of an FRTB programme’s
objectives, and to ensure that the architecture choices made are appropriate.
Key challenges

3. everis 3
Front Office and Risk Alignment
“Internal models used to calculate market risk charges are
likely to differ from those used by banks in their day-to-day
internal management functions. Nevertheless, the starting
point for the design of both the regulatory and the internal
risk models should be the same. In particular, the valuation
models that are embedded in both should be similar.”
[BIS d352, paragraph 180, IMA Qualitative Standards].
FRTB requires stronger alignment between Front Office and Risk in terms of risk metrics,
revaluation models and conventions.
The regulatory risk associated with a failure to meet IMA P&L test can be mitigated by the
architecture of the selected solution:
“The P&L attribution assessment is designed to identify whether a
bank’s trading desk risk management model includes a sufficient
number of the risk factors that drive the trading desk’s daily P&L.
[..] This “risk-theoretical” P&L is the P&L that would be produced
by the bank’s pricing models for the desk if they only included
the risk factors used in the risk management model.”
[BIS d352, Appendix B, P&L Attribution and Backtesting frameworks].
everis recommends re-use of Front Office engines for Risk where practicable to reduce risks
associated with IMA P&L test failure and consequent capital impact.
FO 1
FO 2
FO n
Risk
FO 1
FO 2
FO n
Risk
…
…
Positions and
transactions
P&L vectors,
sensitivities
Different
engines
for Front
Office and
Risk
Single
engine for
Front
Office and
Risk
Positions and
transactions are
delivered to the risk
system for
calculation of risk
metrics.
P&L vectors and
sensitivities are
delivered to the risk
system for
aggregation.
↗ Application of more
efficient models adapted
to the particular needs of
each product
↘ Higher engine
synchonization effort and
risk of IMA failure
↗ Mitigates risk of IMA failure
↘ Front Office engines may
need to be adapted to
meet new requirements

4. everis 4
FRTB Reference Architecture
The re-use of Front Office engines for Market Risk and the segregation of the aggregation layer
for Risk offers a simple solution, segregated from a business and geographical point of view
and with low regulatory risk.

5. everis 5
Big Data Reference Architecture
The Big Data logical
architecture is based on a
modular structure with well-
defined and uncoupled
components to provide the
technical capabilities to build
any functional use case.
It can be easily extended to
provide new capabilities (e.g.
new data sources, real time
processing, etc.) and can be
implemented with different
technical solutions.
An interactive aggregation
tool with rich visualisation
capabilities permits the
flexible and detailed analysis
of variations in results.

6. everis 6
The Goal: Dynamic Capital Management
Capital Framework
Counterparty
Credit Risk
Securitisation
Framework
Market Risk Operational Risk
Pre-trade Post-trade Risk management Capital charge
Capital estimate
DataManagement
Data tools manage
the ingestion and
cleaning of data
from multiple sources
and make them
available for analysis,
flexibly integrating
new data sources to
support incremental
use cases
Aggregation
Aggregation solution
compliant with BCBS
239 principles should
deliver accuracy,
integrity,
completeness and
timeliness whilst
retaining flexibility to
meet additional
requirements
Monitoringand
Analysis
Advanced analytics
and visualisations
implemented using
high-performance
technologies
support the
monitoring and
decomposition of risk
outputs to reduce
the risk of P&L test
breaches.
DynamicCapital
Management
What-if and back-
testing tools assess
the capital cost of
new trading
strategies and
support portfolio
reclassification
across trading desks
to maximise the
efficient deployment
of capital.
Stress-testing

7. everis 7
FRTB Cross-functional Governance
The cross-functional nature of FRTB demands robust governance with adequate stakeholder
representation. Revaluation models, calibration procedures, market data Sets, cut-off times
and many more conventions must be aligned to meet qualitative and quantitative
requirements.
Front Office
conventions
Risk Management
conventions
 Revaluation
models
 Calibration
 Market data set
 Cut-off time
 P&L definition
 Support teams
 Revaluation
models
 Calibration
 Market data set
 Cut-off time
 P&L definition
 Support teams
Close collaboration between front office, risk, finance and IT stakeholders is essential to ensure
that the to-be architecture strikes an appropriate balance where trade-offs are necessary and
meets the full range of requirements as comprehensively as possible.
The complexity of change management related to FRTB implementation should not be
underestimated.

8. everis 8
Flexible Approach to FRTB Implementation
The approach to the definition of business model, operating model and technology
architecture must reflect the need to maintain flexibility to respond to regulatory obligations
and market developments in an agile way.
Global governance needed Local governance permitted
BusinessModel
Risk appetite
Capital allocation
Diversification strategy
Internal Model
Approach Authorisation
Trading desk structure
Revaluation models
P&L and Risk
representation
OperatingModel
Market data sourcing
Model calibration
Trading conventions
Limits and controls
Trading workflows
Scenario generation
Risk calculation and
aggregation
P&L testing
Reporting
Technology
Market data feeds
Data quality checks
Real-time vs batch
integration
Computational
performance
Vendor vs in-house
solutions
Global vs Local Project
delivery

9. everis 9
Summary
The specific challenges of FRTB may be addressed by the establishment of a cross-functional
governance framework and by evolving or replacing functional components within a bank’s
front office and risk architecture.
We can consider consolidation on a ‘front-to-risk’ solution, but bear in mind the trade-off
between the benefits of consolidation and flexibility.
Where Front-to-Risk consolidation is not practicable, we can define an aggregation solution
that enables the re-use of components and delivers the required analytical capabilities to
calculate and monitor FRTB outputs at a sufficient level of performance.
A Big Data approach can address the computational intensity and complexity associated with
FRTB and can be readily extended to accommodate new data sources and analytical tasks.
Such an architecture can be defined to meet specific FRTB requirements and then extended
to be the foundation of a true dynamic capital management process.
Effective cross-functional governance is critical for the successful delivery of an FRTB
programme’s objectives, and to ensure that the architecture choices made are appropriate.

10. everis.com
Thanks, we are
delighted to
have the
opportunity to
share our vision
with you JONATHAN PHILP
Director, Treasury & Capital Markets
jonathan.philp@everis.com
Gilmoora House. 57-61 Mortimer Street
London W1W 8HS
Tel: +44 74 6293 1415
ENRIC OLLE
Director, Head of Murex Services
enric.olle.soteras@everis.com
Avenida Diagonal 561, Planta 5
08028 Barcelona
Tel: +34 936 007 744

11. everis 11
Annex: Risk appetite and limits monitoring
Beyond the regulatory limits established to preserve FRTB/IMA authorization, pre-trade and
post-trade market risk limits and controls should be reviewed at the level of each trading desk
in order adapt the whole risk appetite framework to the new risk metrics introduced by FRTB.
New risk limits, controls and analysis tools
 The new Target Operating Model will leverage on
new risk limits and controls to ensure a closer
monitoring of trading desk activities by the risk
management unit.
 In addition, proper analysis tools will be required
to explain any sudden shift in a complex risk
metric and to capture the root cause and
expected development in the future.
New risk metrics introduced by FRTB
 Curvature risk which expands existing delta and
vega risks capturing the worst loss of two stress
scenarios.
 Jump to Default (JTD) risk based on notional
amounts and market values intended to capture
stress events in the tail of the default distribution.
 Residual Risk Add-on applied to notional amounts
of instruments with non-linear payoffs.
 Expected Shortfall (ES) adjusted to include stressed
period and liquidity horizon effects which should
be confronted to the VaR risk metric currently in
use.
 Default Risk Charge (DRC) which should be
measured using a VaR model and must recognize
the impact of correlations between defaults
among obligors including the effect of periods of
stress.
 Stressed Capital Add-on (SES) which will capture
non-modellable risk factors in model-eligible desks
and will be based on a stress scenario calibrated
to be at least as prudent as the ES calibration.
SA
IMA

12. everis 12
Annex: Initial assessment and critical path management
An early assessment of capital impact at the level of every desk and strategy both under FRTB-
SA and FRTB-IMA is recommended to establish business priorities and identify the critical path of
the whole transformation project. The resulting management framework should be ready to
dynamically accommodate new business requirements and/or regulatory amendments.
Diameter linked to projected Business P&L Diameter linked to projected Business P&L
Capital charge vs Project delivery risk
S01 S02 S03 S04 S05 S06 S07 S08 S09 S10 S11 S12 S13 S14 S15 S16 S17 S18 S19 S20 S21 S22 S23 S24 S25 S26 S27 S28 S29 S30 S31 S32
Spain Trading Room
Trading Desk 1
Strategy 101 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1
Strategy 102 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1
Strategy 103 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1
Trading Desk 2
Strategy 201 0 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1
Strategy 202 0 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1
Trading Desk 3
Strategy 301 0 0 0 0 1 1 1 1 0 0 0 0 1 1 1 1 0 0 0 0 1 1 1 1 0 0 0 0 1 1 1 1
Strategy 302 0 0 0 0 1 1 1 1 0 0 0 0 1 1 1 1 0 0 0 0 1 1 1 1 0 0 0 0 1 1 1 1
Strategy 303 0 0 0 0 1 1 1 1 0 0 0 0 1 1 1 1 0 0 0 0 1 1 1 1 0 0 0 0 1 1 1 1
Strategy 304 0 0 0 0 1 1 1 1 0 0 0 0 1 1 1 1 0 0 0 0 1 1 1 1 0 0 0 0 1 1 1 1
Trading Desk 4
Strategy 401 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1
Strategy 402 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1
Strategy 403 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1
Trading Desk 5
Strategy 501 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
Strategy 502 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
S01 S02 S03 S04 S05 S06 S07 S08 S09 S10 S11 S12 S13 S14 S15 S16 S17 S18 S19 S20 S21 S22 S23 S24 S25 S26 S27 S28 S29 S30 S31 S32
Business Value 16.0 17.4 16.0 17.4 20.8 22.3 20.8 22.3 21.1 22.6 21.1 22.6 26.0 27.4 26.0 27.4 16.5 18.0 16.5 18.0 21.4 22.8 21.4 22.8 21.7 23.1 21.7 23.1 26.5 28.0 26.5 28.0
Capital Cost (mEUR) 886 864 720 695 633 607 461 433 807 783 638 611 550 523 375 345 699 673 529 500 439 411 264 233 616 589 443 413 353 323 174 142
Project Cost (mEUR) 8.2 10.6 17.7 17.7 14.9 14.9 20.0 20.0 13.4 14.0 19.3 19.3 16.5 16.5 21.6 21.6 21.0 23.4 24.8 24.8 25.9 25.9 27.1 27.1 24.4 25.0 26.4 26.4 27.5 27.5 28.7 28.7
% Project Risk 0.6 3.2 20.5 20.5 17.7 17.7 31.3 31.3 4.6 4.8 21.0 21.0 18.1 18.1 31.7 31.7 59.0 60.0 63.4 63.4 65.6 65.6 68.4 68.4 60.2 60.3 63.6 63.6 65.8 65.8 68.6 68.6
Migration Scenarios
S16 S16
Capital charge vs Project delivery costs

13. everis 13
Annex: P&L Attribution governance framework
FRTB establishes a stringent model validation framework at the trading desk level based on
backtesting and P&L attribution to preserve IMA approval. A strong P&L attribution governance
framework should be put in place to closely monitor P&L attribution backtesting performance
and to react promptly in case IMA approval is jeopardized.
P&L attribution requirements
 Based on two metrics:
 Mean unexplained daily P&L (i.e. risk-theoretical P&L minus
hypothetical P&L) over the standard deviation of actual
daily P&L.
 Ratio of variances of unexplained daily P&L and
hypothetical daily P&L.
 If the first ratio is outside of the range of -10% to 10% or if the
second ratio were in excess of 20% then the desk experiences a
breach. If the desk experience four or more breaches within the
prior 12 months then it must be capitalized under SA.
 The desk must remain on SA until it can pass the monthly P&L
attribution requirement and provided it has satisfied its
backtesting exceptions requirements over the prior 12 months.
Backtesting requirements based on VaR
 Based on comparing each desk’s 1-day static
value-at-risk measure (calibrated at the most
recent 12 month’s data, equally weighted) at
both 97.5th percentile and 99th percentile, using at
least one year of current observations of the desk
one-day P&L.
 If any given desk experiences either more than 12
exceptions at the 99th percentile or 30 exceptions
at the 97.5th percentile in the most recent 12-
month period, all of its positions must be
capitalized using SA.
 Positions must continue to be capitalized using SA
until the desk no longer exceeds the above
threshold over the prior 12 months.
A proper solution is required to drill down risk exposures from risk factors and to identify
conflicting positions which should be hedged or removed from the portfolio. The solution
should not only focus on exceptions but on how closely the desk if operating from the
threshold.

14. everis 14
Annex: Cross-regulation impact assessment
FRTB impacts and actions should be aligned with those of other on going regulations in order to
ensure full compliance while preserving data integrity and process automation which will in the
root of a competitive operating model moving forward.
FRTB
EMIR
SA-CCR
CVA
Stress
Test
Volcker
MIFID II
 EMIR which prescribes the central clearing of specific
categories of OTC transactions and reporting to a trade
repository.
 SA-CCR which imposes to new capital charges for the
accounting of counterparty risk for
margined/unmargined, bilateral/clearer derivative
transactions.
 CVA which is an adjustment to the fair value (or price) of
derivative instruments to account for counterparty credit
risk (to be further amended under FRTB-CVA framework).
 Stress Test exercises which estimate economic impact
under unfavourable market scenarios with focus on
regulatory capital.
 Volcker which prohibits banks from conducting certain
investment activities with their own accounts and
establishes new rules on trading desk classification and
PL explain.
 MIFID II which establish new investor protection and
distribution rules in addition to new market infrastructure
and transparency requirements may hinder the
profitability of existing business lines.