steering with expected loss

Steering with Expected Loss Methodological Approaches to IFRS 9 Impairment

Wolfgang Reitgruber

FVP, Credit Risk Modelling, UniCredit S.p.A.

Risk Expert, Institute for Management Sciences, University of Technology, Vienna

5th Annual Risk Management Forum, GLC, Vienna, September 11, 2015

The presented opinions and methods in this presentation are solely the responsibility of the author and should not be interpreted as reflecting those of UniCredit S.p.A. View my research on my SSRN Author page: http://ssrn.com/author=2428110

© Wolfgang Reitgruber 2015. All rights reserved.

Content

• Challenges in Credit Risk Steering

• Calibration of IFRS 9 Impairment

• Introduction into Impact of Risk©

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Transition from IAS 39 to IFRS 9 Impairment

• IAS 39 • Provisions mostly based on single case analysis of non-performing exposures

• Certain parameter-based approaches for efficiency reason (small tickets)

• IBNR concept for performing loans – methodologically questionable LIP

Largest part of provisions driven by single case analysis

Small P&L impact from methods changes (LIP, portfolio-based provision coverages)

• Upcoming IFRS 9 Impairment Standards • Change from fact-based "Incurred loss" to stochastic "Expected loss" provisioning

• Based on forward looking "Point in time" estimates

• Identification of "significant risk increase" since inception

• Implicit Preconditions • Regulatory IRB environment: reconciled models/parameters / based on same input data

• Non-IRB environment: justification of (overall) provisions with incurred credit risk

• Detailed P&L walk for each accounting period

Separate random (idiosyncratic, unsystematic) from systematic impacts (trends)

Separate pure risk development from model adjustments and bucket transitions

3


Methodological Challenges – 1 year ECL

• PD • Identification of "forward looking" calibration target by segment

• Segments defined by "comparable economic development" (default rate trend)

• Who provides these predictions? (External/regulation? Internal/market? Internal/risk?)

• Functional relationship between existing PDs (IRB or other, TTC or hybrid) and IFRS 9

PD based: Capped scaling? Smooth transfer function? Based on correlation structure?

Model based: Adjust calibration module of existing model?

• EAD • EAD estimation (exposure at default) instead of regulatory CCF focus

• Modeling of balance reductions, discounting and early prepayments

• LGD (PL and NPL, lifetime) • Discounting by original effective interest rate vs regulatory treatment

• Forward looking estimate of collateral values (market trends), cash flows (economic

development) and guarantees (PD migration) until liquidation

• For PL: conditional on default event within 1 year

4


Methodological Challenges – lifetime EL (LEL)

• General • PD, EAD and LGD curves needed (explicit or implicit through approximations):

• PD • Robust estimation of long term (marginal) default rates by segment

• How long and on which segments are PIT predictions feasible?

Identification of (stable) segments with comparable long term default rates

Transparent modelling approach (-> justify P&L impact!)

Alternatives to migration matrices highly welcome

• EAD • Estimation based on contractual and behavioral components

• Lifetime EAD conditional on "significant risk increase":

Changing early prepayment behavior (client)

More restrictive use of free credit lines (bank)

5


Needed: Key Risk Indicators Focusing on ECL/LCL

• Reconciled • P&L impact based on accounting standards (IAS 39, IFRS 9 Impairment)

• Capital impact based on pillar I or II (A-IRB, economic capital models)

• Link between regulatory requirements (especially Shortfall) and impairment

• Relevant • Alignment with management objectives and top-level business reporting

• External visibility through disclosure requirements

• Drive Accountability • Separation of actual development into trend, parameter quality and noise

• Alignment of internal roles and responsibilities with:

operational performance, economic development and model quality

• Proper consideration of randomness in budgeting processes and capital planning

• Significant • Test for statistical and practical significance

• Avoiding inefficient management responses based on random deviations

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Content




7


Credit Risk Steering Wheel

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Calibration of IFRS 9 Processes

• Benchmark iACV© based on amortized cost method • iACV© = idealized Amortized Cost Value

• Effective interest rate based on expected cash flow net of loss estimates at origination

• In line with standard economic theory of financial assets (economic value)

• Corresponding to “Fair Value” under stable and unchanged market conditions

• Changed loss expectations immediately recognized through changed expected cash flows

• IFRS 9 Final Standard compared to iACV© • Gross Carrying Amount defined by contractual cash flow and original effective interest rate

• Gross Carrying Amount = iACV© in case of constant and unchanged hazard rate

• Initial loss expectation included in GCA

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“Methodological thoughts on EL estimates for IFRS 9 Impairment: hidden reserves, cyclical loss predictions and LGD backtesting”, 2015 Long version: http://papers.ssrn.com/abstract=2641688. Short whitepaper: http://ssrn.com/abstract=2642107

Potential Hidden Reserve/Liability =

= iACV© – Net Carrying Amount


Example

• Non-amortizing loan, 5 years term, constant gross carrying amount (100)

• X-axis = time in years, Y-axis = net value after allowances (or economic value)

• Continuously increasing 1-year PDs (rating downgrades),

causing transition to bucket two after 1.5 years

• The smooth curve describes the benchmark iACV©

• The grey curve describes the net accounting value

according to IFRS 9:

• It starts conservative (12-months ECL allowance),

gets non-conservative with increasing risk level

• In bucket two the accounting value is strictly

conservative, at a higher level than in bucket one

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90

91

92

93

94

95

96

97

98

99

100

0,0 0,5 1,0 1,5 2,0 2,5

iACV©

IFRS 9


Double Counting Expected Loss?

• Per "todays" balance sheet – Deviation from "fair value" • The earlier bucket transition to 2, the more deviation to be observed

• In bucket 2, initial lifetime loss is counted twice (as currently in bucket 3)

• Bucket 1 might be well-balanced depending on transition process

• Increasing P&L volatility expected

• Lifetime? • "Just" earlier recognition of losses, but no overall increase

• Some small impact due to discounting possible

• No impact on overall pricing necessary

• Capital impact? • Still up to the regulator – current shortfall/excess definition not symmetric!

• Regulators think of adjustments to shortfall/excess definition

• Market reaction to increased P&L volatility?

11


Business Case – Defaulting Loan

Starting bucket 1

Transition to bucket 2 in year 1.5

Default event in year 4

• Cumulative risk identical

• IFRS 9 less conservative in year 1

• IFRS 9 more conservative in year 2&3

• (Almost) fair assessment in default

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Business Case – Risk Increase, no Default

Starting bucket 1

Transition to bucket 2 in year 1.5

Curing to bucket 1 in year 3.5

• Cumulative risk identical

• IFRS 9 less conservative in year 1

• IFRS 9 more conservative in year 2&3

• Higher overall volatility in IFRS 9

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Content




14


Static View on Impact of Risk©

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New Business - New Customers

- New Transactions

- Line Increases

- Risk Strategy

- Risk Appetite

Impact of Risk©

P&L Impact Provisions and

Write-Off

Capital Impact Shortfall/Excess

EL minus Provisions

Expected Loss (Prediction)

Link to Pricing

Unexpected Loss (Deviation)

Link to Write-Off/Provision

Ongoing Business - Rating Migration, Stability

- Increase/Decrease of

Risk Density

- Economic Trend

- Customer Management

PL Dashboard - Surplus/Shortfall of

Default vs ELPL

- Collection Strategy

- Focus on PD (PIT/TTC,

backtesting, power)

NPL Dashboard - Surplus/Shortfall of

Recoveries vs ELNPL

- Workout Strategy

- Focus on LGD Best Est.

(PIT/TTC, backtesting)


Dynamic View on Impact of Risk©

16

“Generated ELPL”

covering next

period defaults

“ELPL Consumption”,

covering current period defaults

“ELNPL Evolution”,

covering current period cures,

repayments, recoveries & write-offs

Write-off

Deviations

measured by the

PL Dashboard

Deviations

measured by the

NPL Dashboard

BOP EOP

Impact

of Risk©

“Expected loss and Impact of Risk: backtesting parameter-based expected loss in a Basel II framework”, Journal of Risk Model Validation, Vol. 7/3, pp 59-84, 2013 Long draft version: http://ssrn.com/abstract=2636871. Short whitepaper: http://ssrn.com/abstract=2638807.


Example of a PL Dashboard

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0

5

10

15

EL vs Defaults

EL PL EAD*LGD

0

10

20

30

40

50

60

0 20 40 60 80 100

Distribution

EL 44 Mio

Loss:

11 Mio • 11Mio losses 2012, significant at 1% level

• Under TTC loss distribution assumption

• Feb 2013 loss event at 95% level

• Once a year possible under TTC conditions

• Root Cause investigation:

• Cyclical economy? -> PIT adjustment for PD

• High asset correlations? -> Likely

• PD model calibration potential? -> Possible


Credit Risk Steering Wheel – Completed

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Currently Available Modules

• Workshop "The Steering Wheel" • 2 days interactive training

• Participation from various units: methods development, validation, reporting, budgeting,

pricing, capital planning, management, …

• Review of local model landscape (segments, validation, usage, …)

• Introduction into Impact of Risk, PL/NPL Dashboards and IFRS 9 calibration

• Discussion on possible implementations, leveraging on the local environment

• Introduction "Impact of Risk" • ½ day training, to be integrated into a general IFRS 9 training or as standalone module

• Introduction into Impact of Risk, PL/NPL Dashboards and IFRS 9 calibration

• Discussion and Q&A on methodological details

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Wolfgang Reitgruber

FVP, Credit Risk Modelling, UniCredit S.p.A.

Risk Expert, Institute for Management Sciences, University of Technology, Vienna

[email protected]

Tel. +43 664 812 3393

http://www.linkedin.com/in/wolfgangreitgruber

Thank You For Your Interest !

Questions Welcome !

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The presented opinions and methods in this presentation are solely the responsibility of the author and should not be interpreted as reflecting those of UniCredit S.p.A. View my research on my SSRN Author page: http://ssrn.com/author=2428110 The concepts and terms “iACV“, “Impact of Risk”, “IoR”, “PL Dashboard” and “NPL Dashboard” are copyright by

steering with expected loss

Economy & Finance