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How to reconcile the demands of risk and finance on a single,
flexible platform
Author: Shlomo Cohen, Risk SME, AxiomSL
Date: 14 April 2016
Preparing for the IFRS 9 game-changer
Preparing for the IFRS 9 game-changer: How to reconcile the demands of risk and finance on a single, flexible platform
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Table of contents
Executive summary ................................................................................................ 3
Overview of IFRS 9 implementation challenges .............................................................. 4
1. Upgrading data handling for joint risk and accounting compliance .................................. 5
2. Changing the nature of internal databases .............................................................. 7
3. Addressing the goals of both CROs and CFOs ............................................................ 9
4. Reconciling conflicting regulatory and accounting demands ........................................ 11
Conclusion: IFRS 9 calls for a game-changer: AxiomSL .................................................... 13
About the author ................................................................................................. 15
About AxiomSL .................................................................................................... 15
Contact ............................................................................................................. 16
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Executive summary
International Financial Reporting Standard 9 (IFRS 9) is a new accounting standard for financial
instruments, which firms around the world must implement by 1 January 2018 at the latest. It has
been designed to value assets and liabilities in a more risk-sensitive manner than the incumbent
International Accounting Standard 39 (IAS 39). Despite being an accounting standard and not a
supervisory measure, it introduces a new approach to credit risk.
IFRS 9 presents many challenges for financial firms, including accommodating the differing demands
of risk and finance, and managing large volumes of risk and financial data, which must be refreshed
at more regular intervals than ever before. This white paper reveals how these challenges can be
overcome by using a single, integrated platform with a flexible data model.
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Overview of IFRS 9 implementation
challenges
The major challenges of implementing IFRS 9
revolve around the requirement to
accommodate the perspectives of both risk and
finance. Historically, these two functions have
operated in isolation from one another,
developing very different cultures. To grasp
the uncertainties of the future, the risk world
is fond of statistics, which it uses to analyze
historical patterns and spot recurring behavior.
In essence, it is a world based on principles
rather than formal rules. In contrast, the world
of finance and, more specifically, accounting is
characterized by many detailed rules. At
times, the excessive complexity of these rules
results in situations that defy common sense.
These very different cultures have deep roots
in the bank and they translate into different
types of organizations: typically, risk
management has some degree of liberty as
long as it is compliant with regulations;
accounting, on the other hand, has to strictly
follow accounting rules without any kind of
freedom. Accordingly, risk and accounting data
is organized differently, and the goal of
combining these different types of data is a
real challenge.
This white paper analyzes the technical
challenges of implementing IFRS 9 and suggests
effective ways for firms to maximize their
return on investment in data management.
The common feature of the solutions proposed
in this white paper is the ability to feed
processes and reports with data that is
dynamically collected from a number of
internal and external sources, with no
duplication of data and no need to change the
IT infrastructure. This enables a rapid
implementation at limited cost, all the while
maintaining strong data lineage for mining and
auditing. This is exactly what AxiomSL’s state-
of-the-art platform offers.
Proper data management will produce
significant benefits by integrating risk and
finance, but only if the following challenges
are addressed:
1. Data handling must be upgraded to
support joint risk and accounting
compliance
2. The nature of internal databases must be
changed
3. The diverging goals of chief risk officers
(CROs) and chief financial officers (CFOs)
must be addressed
4. Conflicting regulatory and accounting
views of risk must be reconciled
Each of these issues is described below and
appropriate solutions are proposed.
The common feature of the solutions
proposed here is the ability to feed
processes and reports with data that is
dynamically collected from a number of
internal and external sources, with no
duplication of data and no need to
change the IT infrastructure
Preparing for the IFRS 9 game-changer: How to reconcile the demands of risk and finance on a single, flexible platform
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1. Upgrading data handling for joint risk
and accounting compliance
The Basel Committee on Banking Supervision’s
239 (BCBS 239) Principles for Effective Risk
Data Aggregation and Risk Reporting refer to
risk data, not accounting data, which is
managed based on accounting standards.
Nevertheless, implementing IFRS 9 requires a
large amount of data that will have to fulfill
both sets of requirements. So, what is the
underlying logic of each framework? How do
they conflict? And how can they be
accommodated?
Accounting aims to provide accurate and
auditable figures. Billion-dollar balance sheets
must be published with figures that are precise
down to the last dollar, and it must be possible
to trace these financial figures back to their
sources. Moreover, the figures must be
disclosed within tight timelines and must be
accurate and transparent.
All of this financial data is intended to inform
stakeholders about how well the company is
performing, so they can make informed
decisions about its future. The financial figures
are also used to calculate taxes - a serious
matter. This is why the disclosures bear the
signatures of both the chief executive officer
(CEO) and CFO. Inaccuracies, whether
inadvertent or otherwise, may result in a jail
sentence. Consequently, accounting is
performed in a very controlled, structured and
rigid production environment.
Vision, anticipation, openness and
reactivity are required when
measuring risk and supporting
risk/return decision-making
Preparing for the IFRS 9 game-changer: How to reconcile the demands of risk and finance on a single, flexible platform
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Risk works in a different, less structured
ecosystem because it is intended to support
decision-making in an uncertain environment.
The risk function tries to reduce the
uncertainties of the future by clarifying the
alternatives. The resulting insights are used to
support decisions about which risks to take and
to what extent; and which risks to hedge or
avoid. Outputs are holistic by nature - risk
appetite, risk tolerance, risk hedging etc.
Despite the efforts of regulators to formalize
and industrialize risk assessment, practitioners
need vision, anticipation, openness and
reactivity when measuring risk and supporting
risk/return decision-making. This calls for
flexible and easy-to-change decision-support
systems, with an underlying IT environment
that should also share these characteristics.
Trying to combine the goals of accountants and
risk managers leads to the following question:
can data be managed in a controlled,
structured and rigid production environment
while simultaneously being available for open,
flexible and evolving decision support?
AxiomSL’s platform provides both the
controlled environment required by accounting
and the flexibility required by risk. By imposing
no constraints on where the data is located
and by avoiding duplication and double
storage, data can be used in a rigid production
structure as well as in a flexible, adaptable
decision-support environment. Complex logic
can be defined graphically and understood by
both IT and business users. The platform
enriches the data, but retains the links to all
sources, providing full data lineage. Thus, all
data changes, whether due to human
interaction or system logic, are tracked and
auditable. Full data lineage is also critical
during testing and production to understand
the results. The ability to drill down to the raw
data sources, which are already known to the
users, is essential for establishing trust in the
system and for reassuring management about
the reliability of the final results.
AxiomSL’s platform
provides both the
controlled environment
required by accounting
and the flexibility
required by risk
Preparing for the IFRS 9 game-changer: How to reconcile the demands of risk and finance on a single, flexible platform
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2. Changing the nature of internal
databases
In order to implement IFRS 9, databases will
need to be larger, more dynamic and open to
external data.
Under IFRS 9, the correct assessment of
expected credit loss (ECL) will require
significant changes to internal databases. The
fact that almost all assets will have to be
impaired will dramatically increase data
granularity and data volumes; the point-in-
time (PIT) requirement will make high-
frequency updates compulsory; and the
forward-looking approach will require a
significant inflow of external financial and
economic data.
Why will data need to be more granular?
Assessing ECL under the IFRS 9 framework
means calculating impairments for all assets in
the ‘amortized cost’ or ‘fair value through
other comprehensive income’ categories.
These two accounting categories should
comprise the bulk of all assets. This means the
number of assets to be impaired will increase
dramatically from thousands to millions. This is
a whole new ball game: in terms of data
management, the processes of purifying and
enriching the data, and the operations of
extraction and transfer, will have to be
massively enhanced and automated.
Why will data need to be updated more
frequently? The spirit of IFRS 9 is to identify
credit risk increases as early as possible. This is
apparent in the PIT requirement and the
changes to the buckets in which assets are
grouped. PIT measures such as PIT probability
of default (PD), loss given default (LGD) and
joint default correlations will probably have to
be updated at least once a month. This is the
update frequency for many macro-economic
indicators affecting the markets. Higher
frequencies must also be considered: the
supervisory guidance specifies that “ECL must
capture all significant increases in credit risk”
(guidance #45), so ECL assessment must be
linked to market information and must be
ready to be updated at short notice.
Why will external data be needed? ECL is
assessed as a probability-weighted discounted
cash shortfall. The weighting refers to possible
future scenarios. These scenarios have to
include “information that is available (…) at
the reporting date about past events, current
conditions and future economic conditions”
(IFRS 9 5.5.17). As ECL changes will have to be
disclosed and explained, a significant mass of
external economic and market data, both
qualitative and quantitative, will have to be
collected and stored for future retrieval and
analysis.
In terms of data management,
the processes of purifying and
enriching the data, and the
operations of extraction and
transfer, will have to be massively
enhanced and automated
Preparing for the IFRS 9 game-changer: How to reconcile the demands of risk and finance on a single, flexible platform
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How can financial firms design an open
solution that can handle this granularity,
frequent updates and large volumes of
external data?
AxiomSL’s platform can store, manage and
control data at different levels of granularity;
and the frequency at which this data is
updated can be tailored to meet the needs of
individual parts of the business. The AxiomSL
platform is unified and can be used to control
all data and processes. A single environment,
team and architecture can be leveraged to
manage large volumes of historical, retail,
statistical data and precise balance-sheet
information for corporate clients. This unique
approach allows financial firms to reuse
resources, including hardware, software and
teams, leading to significant reductions in the
total cost of ownership (TCO).
A single environment, team and
architecture should be leveraged
to manage large volumes of
historical, retail, statistical data
and precise balance-sheet
information for corporate clients
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3. Addressing the goals of both CROs and
CFOs
IFRS 9 compliance will require risk data. Both
the CRO and CFO will want to own this data
because it is critical raw material they need to
meet their own current and emerging
requirements.
The CFO signs off the financial accounts and is
liable to the shareholders and the auditors
with regards to the transparency and fairness
of the disclosures. Consequently, s/he is used
to controlling accounting data from A to Z. The
new issues faced by the CFO include a massive
increase in the number of assets to impair and
a higher volatility of provisions, which s/he
will have to dynamically forecast and manage.
Securing the quality and availability of data
will be a critical success factor.
The concern is the same for the CRO: s/he is
on the frontline managing regulatory pressure,
including compliance with BCBS 239, Basel III,
the Asset Quality Review (AQR) and European
Banking Authority (EBA) stress tests. The CRO
must deliver complex reports at high
frequency. To that end, s/he has an explicit
responsibility from the board to fulfill all
upcoming supervisory requirements. Moreover,
s/he will undoubtedly be summoned by finance
to provide the credit risk data required for
IFRS 9 compliance. As a result, the new issues
facing CROs include managing more granular
data down to the transaction level, moving
towards PIT and introducing forward-looking
components into their analysis.
So, should the CFO or CRO own the credit risk
data used for ECL assessment? Should the data
be duplicated or can it be shared? Will CEO
arbitrage be necessary or should there be a
chief data officer (CDO) position to decouple
data sourcing and usage (see the chart below)?
Options Main benefits Main challenges
CFO owns the data Firsthand IFRS 9 user
Controls everything
Provisions managed dynamically
Understanding and using risk data
CRO owns the data Maintains coherence
Regulatory compliance
Knows risk systems
Complying with accounting
requests
Duplicate sets of data
(one for CRO and one
for CFO)
Both CRO and CFO own
Can implement different
frequencies, perimeters and
content constraints
The possibility of discrepancies
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The current trend is to give ownership of the
data to the CFO because s/he owns the
impairment process and because the data used
to assess PIT measures and the forward-looking
stance are mostly related to the accounting
standard. Nevertheless, CRO supervision is
usually granted.
AxiomSL’s state-of-the-art dynamic data model
makes it possible to implement any of these
options. For instance, giving the CFO
ownership of credit risk data can be done
without changing the risk IT infrastructure.
CROs and CFOs are both on
the frontline managing
regulatory and accounting
changes, including compliance
with IFRS 9 and Basel III
Preparing for the IFRS 9 game-changer: How to reconcile the demands of risk and finance on a single, flexible platform
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4. Reconciling conflicting regulatory and
accounting demands
IFRS 9 introduces a ‘naïve’ and refreshing view
of how to assess credit risk. This includes using
past and present data as well as available
forecasts, assessing risk based on the whole
life of transactions and properly including
diversification effects.
In contrast, even the most sophisticated
current regulatory approach, the Internal
Ratings-Based (IRB) Approach, does not offer a
proper way to assess credit risk. This
methodology, unchanged for the last 12 years,
assesses credit risk using through-the-cycle
(i.e. backward-looking) measures. It only looks
at a one-year time horizon regardless of the
real maturity of the transactions.
Diversification and concentration effects are
still based on an over-simplistic asset
correlation methodology. Recovery risk
assessment is collapsed into one single figure,
the downturn LGD.
Facing the tsunami of changes that are to
come, competent authorities are trying to stay
in control. The ‘Guidance on Credit Risk and
Accounting for ECLs’ was published by the
BCBS in December 2015. Regarding loan
portfolios, it adds to and reinforces the IFRS 9
requirements. The guidance was developed
based on the principle of non-objection by the
International Accounting Standards Board
(IASB) and, consequently, it remains quite soft.
In particular, even though it does mention the
discrepancies between the approaches
(“…regulatory capital models may not be
directly usable in the measurement of
accounting ECL due to differences between the
objectives of and inputs used for each of these
purposes” [Guidance #9]), it gives no
indication of how to overcome them.
Moreover, the same vocabulary is used across
the accounting and regulatory frameworks, and
is certain to be a source of confusion.
Commonly used parameters of credit risk
assessment, such as exposure at default (EAD),
PDs, LGDs, correlations and expected loss (EL),
are used indiscriminately, despite the fact that
they represent different concepts and realities
(see box below).
Regulatory view IFRS 9 view
EAD expected value one year ahead
(typically nominal + one year of interest)
EAD = net present value (NPV) for two of the
three asset classes
PDs through-the-cycle PDs point-in-time
One-year PD Multi-year PDs
Downturn LGD LGD distribution
Best ‘worst’ case Weighted average scenarios
One-year time horizon One-year and lifetime
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It is therefore essential to have explicit definitions, a
well-defined data model and attributes that remain
attached to the data wherever it is sent or used.
There are two features of AxiomSL’s state-of-the-
art, flexible data model that are particularly
important for fulfilling the above requirement: on
the one hand, every data source is clearly identified,
named and mapped in the data model; and on the
other, even when delivered within complex
reporting, the data remains in its source
environment and is not duplicated. This data lineage
avoids the risk of losing track of the data’s nature
and identity. It also facilitates data mining and
auditing, and guarantees the reliability of the
reporting, all the while allowing for quick checks and
controls at any stage of the reporting process.
It is essential to have
explicit definitions, a
well-defined data model
and attributes that
remain attached to the
data wherever it is used
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Conclusion: IFRS 9 calls for a game-
changer: AxiomSL
Fintech is said to be a game-changer - and it
really is. Data has become a critical asset for
all financial institutions, and Fintech
companies now give firms the ability to
manage it more efficiently than ever.
IFRS 9 is premised on widespread adoption of
Fintech - its requirements would have been
unthinkable just a few years ago, before
technology played such a significant role at
financial firms.
As demonstrated above, IFRS 9 will require:
an ever-increasing quantity of more
granular data
more frequent data updates to support the
PIT approach
the challenge of sharing the same data
between users with different objectives and
concerns
and the automation of complex processes,
such as ECL calculations for impairments,
without compromising data lineage and
auditability.
AxiomSL, the leading global provider of
regulatory calculation and reporting solutions,
has anticipated these challenges and offers a
robust technology platform that is fully
equipped to implement IFRS 9. The fully
integrated platform has been designed to
enable financial firms to make the best
decisions in terms of organization and
modeling, while reducing the time and effort
needed to access and manage the relevant
data.
External ECL models can be easily integrated
into the AxiomSL platform. AxiomSL has
formed a partnership with AlgoSave and has
integrated its model, which assesses ECL using
historical financial data, current market data
and economic forecasts. The model has been
field-tested in the asset management industry
and is now being made available to other types
of financial institutions. In this way, AxiomSL
offers a compelling solution to the challenges
presented by IFRS 9.
Preparing for the IFRS 9 game-changer: How to reconcile the demands of risk and finance on a single, flexible platform
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About the author
Shlomo Cohen, Risk SME, AxiomSL
Shlomo Cohen has more than 20 years’ experience in risk, regulation and
finance in the banking industry. As AxiomSL’s Risk SME, he is focused on
IFRS 9 and related requirements, such as CECL.
Before joining AxiomSL, Shlomo worked at Dexia bank for 12 years, where
he was responsible for economic capital and Basel II-III Pillar 2. In this
role, he worked on a wide range of issues, including capital allocation,
ALM, risk appetite, budgeting, macro-prudential regulation, and sovereign
and systemic risk. Prior to Dexia, he was founder and CEO of FTM, a
management consulting firm dedicated to enhancing the shareholder value
of financial institutions.
A graduate of MIT, Shlomo is a regular speaker at industry conferences and
seminars. He has contributed articles to many publications and lectures on
risk and finance.
About AxiomSL
AxiomSL is the leading global provider of regulatory reporting and risk management solutions for
financial services firms, including banks, broker dealers, asset managers and insurance companies. Its
unique enterprise data management (EDM) platform delivers data lineage, risk aggregation, analytics,
workflow automation, validation and audit functionality.
The AxiomSL platform seamlessly integrates clients’ source data from disparate systems and
geographical locations without forcing data conversion. It enriches and validates the data, and runs it
through risk and regulatory calculations to produce both internal and external reports. The platform
supports disclosures in multiple formats, including XBRL. The unparalleled transparency offered by
the high-performance platform gives users the ability to drill down on their data to any level of
granularity.
AxiomSL’s platform supports compliance with a wide range of global and local regulations, including
Basel III capital and liquidity requirements, the Dodd-Frank Act, FATCA, AEI (CRS), EMIR,
COREP/FINREP, CCAR, FDSF, BCBS 239, Solvency II, AIFMD, IFRS, central bank disclosures, and both
market and credit risk management requirements. The enterprise-wide approach offered by AxiomSL
enables clients to leverage their existing data and risk management infrastructure, and reduces
implementation costs, time to market and complexity.
AxiomSL was voted Best Reporting System Provider in the 2015 Waters Rankings and was highlighted
as a ‘category leader’ by Chartis Research in its 2015 Sell-side Risk Management Technology report.
The company’s work has also been recognized through a number of other accolades, including success
in the Best Reporting Initiative category of the American Financial Technology Awards and the
Customer Satisfaction section of the Chartis RiskTech100 rankings.
Preparing for the IFRS 9 game-changer: How to reconcile the demands of risk and finance on a single, flexible platform
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Contact
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Email: [email protected]
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Website: www.axiomsl.com
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Tel.: +65 6513-0391
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Tel.: +44 (0)20 3823 4600
Website: www.axiomsl.com
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Edited by: Nicholas Hamilton
Designed by: Laura Harland
Copyright ©2016 AxiomSL
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