Vision 2014: CCAR Loss Forecasting - Learn What You Are Up Against

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CCAR Loss Forecasting — learn what you are up against

Jeff Meli Experian

John Taylor Experian

#vision2014

2 © 2014 Experian Information Solutions, Inc. All rights reserved. Experian Public.

Work smart and hard…

Don’t look where

you fell, look where

you slipped.

– African proverb


Work smart and hard…

Then you can stand and

challenge uncertainty!


CCAR as more than a “regulatory checkmark”

Risk parameter sensitivity and stress testing

Integrating CCAR activities into risk appetite decision process

Session overview


CCAR is more than a

regulatory checkmark


What do you do with this knowledge is of paramount importance!

From a micro prudential perspective, the CCAR

provides a structured means for supervisors to

assess not only whether banks hold enough capital,

but also whether banks are able to rapidly and

accurately determine their risk exposures, an

essential element of effective risk management.

The cross-firm nature of the stress tests also helps

supervisors identify outliers—both in terms of results

and practices—that can provide a basis for further,

more targeted reviews.

– Chairman Ben Bernanke, 2013


Comprehensive Capital Analysis and Review (CCAR) from the Fed…

Enhanced requirement for Loss Forecasting Models, testing/validation and data

Should be macroeconomic dependent under regulatory stress scenarios

Enable forward looking capital planning and account for unique risks

Using outcomes for risk appetite decisions is prudent

CCAR Loss Forecasting and stress testing should inform risk appetite

CCAR administration realities…

Banks strive to meet minimum required capital under loss forecasting regulatory stress scenarios only

CCAR process can be disconnected from risk appetite setting by business’

CCAR components like stress testing and risk parameter sensitivity of loss forecasts should be more than “regulatory box checking”


Large U.S. banks are mandated to undergo stress testing and often asked to demonstrate an ability to understand expected loss model parameter sensitivity for loss forecasting estimates

For the Fed’s annual Comprehensive Capital Analysis and Review (CCAR) exercise, regulator establishes downside parameters and runs its own stress tests

► Banks must meet a 5% equity-to-risk-based-assets test under severe stress scenarios

► Not all scenarios are “likely” but some should be incorporated into future risk appetite decisions

Risk parameter sensitivity testing

► Used to identify highly sensitive risk segments

► Used to determine highly sensitive risk segment impact to risk appetite limits

CCAR related regulatory activities for risk management


Loan-level models have gained more favor in recent years across banks, etc.

Greater accuracy in prediction with more granular data

Ability to incorporate macroeconomic factors for stress testing

Trade-off against model complexity

Disaggregation to an appropriate level of data granularity and ability to estimate portfolio performance with a variety of portfolio segmentations

Fed CCAR model’s general approach: loan-level PD transition models and LGD models including loan level

CCAR foundation best served with loan level models (bottom-up foundation)

EAD

EL

PD Aggregated

to portfolio

segments

and total

LGD Loss given default

Exposure at default

Expected loss

Probability of default


Using risk parameter

sensitivity analytics


What should you know?

Some important terminology…

Risk parameter sensitivity: analysis to measure the volatility of certain portfolio risk segments from changes in PD and LGD

K calculation: formula used by regulators to calculate capital for various portfolios

Enterprise risk appetite: boundary of risk taking in terms of key metrics such as loss taking capacity and profitability volatility that ensure appropriate return for risk


Risk parameter sensitivity planning

Identify risk segments most sensitive to future capital increase and lower profitability…

Use “K” capital requirements formula with stressed values from base and stressed scenarios

Assess adequate return hurdles necessary for “likely” stressed scenarios

Determine segmented appropriate risk appetite for highly sensitive risk segments

Avoid what could be coming by actively leveraging your stress scenario estimates within risk and business decision


Identify PD and LGD segments

Calculate baseline capital metrics


Segment Balance ($) Baseline

Capital ($)

Capital ($) /

Balance ($)

1 $139,465,330 $17,737,960 12.72%

2 $94,182,964 $5,278,842 5.60%

3 $121,980,070 $5,670,736 4.65%

---- ---- ---- ----

16 $68,780,484 $7,953,062 11.56%

Portfolio $2,839,862,934 $188,539,350 6.64%


Identify PD and LGD segments

Calculate baseline capital metrics


Segment Balance ($) Capital ($) Baseline PD Segment

Δ Capital ($)

1 $139,465,330 $17,737,960 0.06% $744,474

2 $94,182,964 $5,278,842 0.08% $220,120

3 $121,980,070 $5,670,736 0.13% $233,572

---- ---- ---- ---- ----

16 $68,780,484 $7,953,062 5.06% 257,752

Portfolio $2,839,862,934 $188,539,350

Make segment-level adjustments

Calculate impact on capital requirements


Call out segments with greatest capital impact and sensitivity to metrics

Strategic action can then be taken on these segments


Segment Balance ($) Capital ($) Baseline PD Δ Capital ($) Δ Capital (%) Elasticity Capital Share

(%)

Δ Capital

Share

1 $139,465,330 $17,737,960 0.06% $744,474 4.20% 0.839 5.69% 3.96%

2 $94,182,964 $5,278,842 0.08% $220,120 4.17% 0.834 1.69% 4.10%

3 $121,980,070 $5,670,736 0.13% $233,572 4.12% 0.824 1.82% 4.04%

14 $329,125,756 $24,448,296 3.10% $846,344 3.46% 0.692 7.78% 3.19%

15 $225,190,822 $19,006,946 3.84% $641,158 3.37% 0.675 6.05% 3.17%


Integration of CCAR and

risk appetite within

business strategy


Regulatory requirements and review recommendations

Integrating CCAR Loss Forecasting into the bank’s risk appetite

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Sensitivity analytics

Loan level PD, LGD EAD models

Scenario analysis

Stre

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Re

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Given severity

Given scenario

Minimum capital requirements

Loss forecasting stress testing

methodologies

Business actions

Results output


Integrating risk appetite into business operations

Finance functions Risk management functions

Regulatory capital

(or economic cap)

Profitability calculations

Growth return hurdles

Cost of funds by product

Future earnings volatility

Remove barriers between

finance and risk to integrate

required regulatory activity and

output into business operations

Business lending return

hurdles informed from

capital can be used to

migrate portfolio risk

taking creating stable

earnings over time

Enterprise risk appetite

Business and strategic goals

Stress testing and risk

parameter sensitivity analytics

Risk adjusted return on capital

(RAROC)

Best case: ERA, stress

testing and parameter

sensitivity can be

applied to more than

capital planning, but

return hurdles as well


Leverage industry best practices... by using loan level models for loss forecasting that can be leveraged across business activities

Leverage risk parameter sensitivity... to identify high volatility segments based on “likely” macroeconomic stress scenarios

Actively manage risk appetite... by integrating knowledge of sensitive risk segments into business planning and risk appetite setting strategic processes cross-functionally

Look forward... by proactively using CCAR Loss Forecasting to make future lending decisions

The business benefits


For additional information, please contact:

[email protected]

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