Iirme credit risk presentation tarun dara

Managing Credit Risk across a Diverse Corporate Portfolio

Tarun Dara, Mubadala GE Capital

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“It is not the strongest or the most intelligent who will survive but those who can best manage change” - Charles Darwin

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5 C’s of Credit Character Capacity Capital Collateral Conditions Profitability Yield is greater than threshold set

Traditional View: Individual Transaction

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• Probability of Default Within 1 year

• Default = Bankruptcy,

90 Days Past Due,

Restructuring to Avoid Default

• Economic Losses Post Default

• Includes All Costs, Timing of Recoveries

• Function Of Collateral, Seniority

• Expected Size of Exposure at Default

• Need to model for Revolvers & for other unfunded commitments

• “Cost Of Doing Business”

• Given Predictable, not “Risk” per se

• Typically reflected in Pricing

Probability of Default

Loss Given

Default

Exposure At Default

Expected Losses

= X X

Credit Risk Quantified : Individual Transaction

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75

380

75 100

225

150 145

60 60 70 100

60 60

265

175

0

50

100

150

200

250

300

350

400

0.23% 0.27% 0.30% 0.31% 0.34% 0.36% 0.45% 0.47% 0.50% 0.54% 0.60% 0.68% 0.90% 0.91% 1.03%

EAD

($

mm

)

EL %

50

350

635

245 320

225 175

0

100

200

300

400

500

600

700

0.59% 0.89% 1.34% 2.01% 3.03% 4.55% 6.84%

EAD

($

mm

)

PD %

75

1060

705

160

0

200

400

600

800

1000

1200

0%-15% 15%-30% 30%-45% 45%-65%

EAD

($

mm

)

LGD %

Credit Risk Measures for a Diverse Portfolio

PD Distribution LGD Distribution

EL Distribution

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At deal level we understand the “risk characteristics”

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What should be the portfolio composition ?

How do we maximize portfolio return ?

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Economic Capital is Provided to Cover Extreme or “Tail Risk” Events

EL

Probability of a “Tail Risk” Event is a function of Unexpected Loss (Volatility)

Expected Loss Vs. Unexpected Loss

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Low

High

Pro

bab

ility

of

Loss

Very Small Size of Loss Very Large

1

EL

1

“Tail Risk” loss event 99.9% Confidence Level

3

UL

2

Average Loss (Expected Loss or “EL” )

Volatility (Unexpected Loss or “UL”)

Extreme Loss or “Tail Risk”

2

3

Portfolio Risk Measures

Confidence level scaled to target rating level

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Ecap (Economic Capital) is the amount of capital a business or product require, for a given amount of risk, to achieve a specified level of confidence that an extreme loss will not exceed the capital

Measured as the potential loss in excess of EL over one year time period at a specified confidence level or criterion

Represents comprehensive risk measurement which can be thought of as “unit of risk”

Economic Capital

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Business risk Structural

ALM Equity

risk Operational

risk Credit

risk

Inter-risk correlations

Overall EC

Comprehensive Ecap Framework

- Losses resulting from inadequate or failed internal processes, people and systems or from external events

- Change in Economic Value of Equity under interest rate and FX scenarios

- Change in value of Equity investments under market scenarios

- Losses resulting from volume and margin decline

- Change in value of credit positions due to default and credit migrations - Most substantial risk type

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Two approaches to measure Credit Risk Ecap In-house formula based model Moody’s Risk Frontier

Credit Risk Ecap: Measurement

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Critical Assumptions: Ratings S&P, KMV,

FICO etc.

Loss History (Recoveries, Collateral

etc.) Outstanding's at default

Probability of Default PD

Loss Given Default LGD

Exposure at Default EAD

Expected Loss EL

x x =

Unexpected Loss ( UL)

(Standard deviation in Expected Loss)

Credit Risk Economic Capital

Credit Rating Capital Multiplier

Desired Credit Rating

Diversification Credit Default Correlations

Historical Correlation of the Portfolio

• Cycle-Neutral

• Benchmark Correlation / Diversification Assumption

• Benchmark Capital Multiplier

• 1 Year Time Horizon

Model Formula

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• A simulation approach to calculate the capital required to maintain a certain level of risk in a credit portfolio

• Allocates capital to individual exposures in the portfolio

• Uses multiple factors based on the global economy, region, sector, industry and country

• Correlation between any two firms’ returns can be explained by the firms’ relationship to a set of common factors

• The greater the link of two individual firms to common economic factors, the greater the likelihood that their fortunes will rise and fall together

Moody’s Risk Frontier

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Systematic

Idiosyncratic

Idiosyncratic

Systematic

Industry, Country and Sales Size determine how much risk is systematic (undiversifiable) vs. idiosyncratic (diversifiable)

Blue Chip MNC has very low stand-alone risk, but that risk is mainly associated to factors that affect the entire economic system and, therefore, all other obligors in a portfolio (i.e. it cannot be diversified away).

Best Pizza, LLC is very risky, but its risk is mainly due to factors that are specific to that company (e.g. neighborhood, health of owner/manager, competition on the street, local economy) and, therefore, not correlated with other obligors in a portfolio.

Low R2 High R2

Modeling Co-relation

Best Pizza LLC (PD : 0.1029) Blue Chip MNC (PD : 0.0003)

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Higher levels of LGDs are associated with increasing capital charges, even though the PDs decrease enough to keep the EL at the same level

Given the same EL, it’s always better to have lower LGD

Capital Sensitivity to LGD

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Australia, $220mm

USA $440mm

UK , $190mm Germany, $ 120mm

Japan, $50mm

UAE, $160 mm

Egypt, $310 mm

KSA, $390mm

Turkey, $120mm

Country, EAD (This is sample data set created for this discussion)

Diverse Corporate Portfolio

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Australia Germany

Japan

UAE

KSA

Turkey

Egypt

UK

USA

5.0%

7.0%

9.0%

11.0%

13.0%

15.0%

17.0%

19.0%

21.0%

0.25% 0.35% 0.45% 0.55% 0.65% 0.75% 0.85% 0.95%

Ecap

(%)

EL(%)

Ecap Requirements: Country Level

KSA has same level of EL as UK but significantly higher Ecap

Distinguish attractiveness of countries at same level of EL

Avg

. 0

.52

%

Avg. 13.0%

UAE & Turkey attract more capital than Australia despite similar EL levels

Germany, Japan look very attractive

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Bubble Size is based on the EAD of Sample Country

Ecap Requirements: Product Level

Asset Finance

Corporate Loan

Project Finance

Real Estate Working Capital

7.0%

8.0%

9.0%

10.0%

11.0%

12.0%

13.0%

14.0%

15.0%

16.0%

17.0%

0.20% 0.30% 0.40% 0.50% 0.60% 0.70% 0.80%

Ecap

(%)

EL(%)

Asset Finance EL level is close to highest but has the lowest Ecap

Working Capital has higher EL than Corp Loans but lower Ecap

Attractiveness at product level….

Avg

. 0

.52

%

Avg. 13.0%

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Bubble Size is based on the EAD of Sample Product

I

K

L

M

N

4.0%

6.0%

8.0%

10.0%

12.0%

14.0%

16.0%

18.0%

20.0%

22.0%

24.0%

0.2% 0.3% 0.4% 0.5% 0.6% 0.7% 0.8% 0.9% 1.0% 1.1%

Ecap

(%)

EL(%)

Avg

. 0.5

2%

Avg. 13.0%

Ecap Requirements: Deal Level

Deals in bottom right have lower capital requirements and in top left have higher capital requirements Confidential 19

Bubble Size is based on the Sample Deal EAD

D

G

I

K

M O

P

Q

R

T

V

W

Z

3.0%

4.0%

5.0%

6.0%

7.0%

8.0%

9.0%

3.0% 8.0% 13.0% 18.0% 23.0% 28.0%

Yie

ld

Ecap(%)

Ecap vis-à-vis Yields

Avg

. 13

%

Avg. 6.45%

Deals in top left are most profitable and the mix has changed Confidential 20

Bubble Size is based on the Sample Deal EAD

B

4.0%

8.0%

12.0%

16.0%

20.0%

24.0%

28.0%

4.0% 8.0% 12.0% 16.0% 20.0% 24.0% 28.0%

RA

RO

C

Ecap(%)

Ecap vis-à-vis Risk Adjusted Returns

Lim

it 2

0%

Hurdle 20%

Deals in top left quadrant meet the hurdle rate and Ecap % limit Confidential

21 Bubble Size is based on the Sample Deal EAD

Concluding Remarks

This framework is meant to supplement the underwriting of each

credit. Continue to maintain high standards of underwriting A Deal looking attractive on its own may not enhance portfolio

returns if it is carrying similar “risk characteristics” Diversification of portfolio is key for return maximization

Mechanism to proactively manage the portfolio

Extend this to perform stress testing which has taken a very

important role from regulatory standpoint

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Thank You

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Mubadala GE Capital Mubadala GE Capital PJSC is a specialized commercial finance company providing structured financing solutions to businesses across MENAT. Headquartered in Abu Dhabi and owned by Mubadala Development Company & GE Capital.

Tarun Dara Tarun is currently leading credit risk and portfolio analytics at Mubadala GE Capital. Over last 13 years he has worked in area of underwriting, corporate finance, portfolio analytics and financial risk consulting spread across India, Asia Pacific and Middle East region. His current focus is on building a robust portfolio and capital management framework, governance of risk models in use across diverse asset classes and portfolio quality reviews. Tarun holds an MBA in finance and strategy from IIT, Delhi ; MS (Hons) Economics from BITS, Pilani in India and has graduated from a financial management program with GE.

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