loan stress testing and segmentation - f · pdf filetrends in commercial real estate lending,...

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158 Route 206 Gladstone, NJ 07934 P: (908) 234-9398 [email protected] www.finpro.us

Loan Stress Testing and Segmentation

2016 State of Banking Summit

November 10, 2016

© 2016 – FinPro, Inc.

What are we seeing in the Banking environment?

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Trends in commercial real estate lending, which has reached record levels at U.S. banks, are unsustainable, Fitch Ratings warned:

The agency said in a press release Monday that CRE loans have risen at a nearly 4% compound annual growth rate over the last five years

Multifamily lending increased at a 10.7% clip over those years, while areas such as hotel, industrial, retail and office lending have slowed

Balances on construction loans, which experienced the highest loss severity during the financial crisis and would likely do so again during the next downturn, have declined in the last five years

Small and midsize banks have the largest CRE exposure

All of the banks where CRE exceeds more than 300% of risk-based capital have less than $50 billion in assets, and most have less than $10 billion in assets

Not all small, CRE-concentrated banks are necessarily at risk

Fitch, however, said it believes banks have tightened lending standards for construction, reflecting lessons learned from the crisis and subsequent regulations that require lenders to hold more capital against loans to highly leveraged projects

The resilient institutions were more selective in their underwriting and reported modest growth into the

most recent downturn, or lent against rent-regulated multifamily buildings

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“Fitch Issues CRE Warning as Bank Portfolios Hit Record Levels “ this week . . .

Source: American Banker November 8, 2016

Given market availability, higher yields, and underwriting expertise, it often makes

sense for an institution to have concentrations.

FinPro’s clients have been able to boost their CRE lending above the thresholds

by following the guidance and upgrading their credit analysis procedures, internal

controls and software.

Supervisory Oversight

An institution that has experienced rapid growth in CRE lending, has notable exposure to a specific type of CRE, or is approaching or exceeds the following supervisory criteria may be identified for further supervisory analysis of the level and nature of its CRE concentration risk:

Total reported loans for construction, land development, and other land represent 100 percent or more of the institution's total capital, or

Total commercial real estate loans as defined in this Guidance represent 300 percent or more of the institution's total capital, and the outstanding balance of the institution's commercial real estate loan portfolio has increased by 50 percent or more during the prior 36 months

Portfolio Stress Testing and Sensitivity Analysis

An institution with CRE concentrations should perform portfolio-level stress tests or sensitivity analysis to quantify the impact of changing economic conditions on asset quality, earnings, and capital

Further, an institution should consider the sensitivity of portfolio segments with common risk characteristics to potential market conditions

The sophistication of stress testing practices and sensitivity analysis should be consistent with the size, complexity, and risk characteristics of its CRE loan portfolio

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Commercial Real Estate Lending Joint Guidance 2006 . . .

Source: FIL104-2006 Commercial Real Estate Lending Joint Guidance December 12,2006

FinPro has many clients who have loan portfolio concentrations above 300% who

have recently undergone safety and soundness examinations without criticism.

Preparedness and communication are they keys. We need to prove to the

regulators that we are measuring, monitoring and controlling the risk.

Recent Supervisory Findings

Many CRE asset and lending markets are experiencing substantial growth, and that increased competitive pressures are contributing significantly to historically low capitalization rates and rising property values

At the same time, other indicators of CRE market conditions (such as vacancy and absorption rates) and portfolio asset quality indicators (such as non-performing loan and charge-off rates) do not currently indicate weaknesses in the quality of CRE portfolios

Many institutions' CRE concentration levels have been rising

Examination activities have revealed an easing of CRE underwriting standards, including less-restrictive loan covenants, extended maturities, longer interest-only payment periods, and limited guarantor requirements

Observed certain risk management practices at some institutions that cause concern, including a greater number of underwriting policy exceptions and insufficient monitoring of market conditions to assess the risks associated with these concentrations

Supervisory Expectations for Financial Institutions risks associated with these concentrations

financial institutions should review their policies and practices related to CRE lending and should maintain risk management practices and capital levels commensurate with the level and nature of their CRE concentration risk

In particular, financial institutions should maintain underwriting discipline and exercise prudent risk management practices that identify, measure, monitor, and manage the risks arising from their CRE lending activity

During 2016, supervisors from the banking agencies will continue to pay special attention to potential risks associated with CRE lending … In particular, the agencies will focus on those financial institutions that have recently experienced, or whose lending strategy plans for, substantial growth in CRE lending activity

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Statement on Prudent Risk Management for Commercial Real Estate Lending 2015 . . .

Source: SR15-17 Joint Release Feed, FDCI, OCC December , 2015

Portfolio Segmentation

The new accounting standard requires institutions to measure expected credit losses on a collective or pool basis when similar risk characteristics exist

If a financial asset does not share risk characteristics with other financial assets, the new accounting standard requires expected credit losses to be measured on an individual asset basis.

Data

To implement the new accounting standard, institutions should collect data to support estimates of expected credit losses in a way that aligns with the method or methods that will be used to estimate their allowances for credit losses

Depending on the method selected, institutions may need to capture additional data

Institutions also may need to retain data longer than they have in the past on loans that have been paid off or charged off.

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The new FASB accounting standard for calculation of reserves, CECL - Current expected credit losses, will require the capture of additional loan data also needed for CRE stress testing and segmentation analysis . . .

Get ahead of the curve, we are going to need this data for:

• Segmentation

• Stress Testing

• CECL

• Annual Credit Review


What has FinPro seen?

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1. Multiple systems

2. Missing documentation

3. Incorrect or incomplete data

4. Data not up to date

5. Data stored in multiple places in multiple platforms

6. Documents scattered

7. Documents and data not digitized

8. Incomplete underwriting

9. Incomplete annual reviews

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FinPro started with CRE stress testing and segmentation as a consulting engagement and here’s what we found . . .

Small number of core banking software vendors has cornered the U.S. market — FIS, Fiserv, Jack Henry, and D+H (through its acquisition of Harland). Together they have about 96% market share

There is a second tier of vendors – down from 117 companies to around 20

The top four vendors have been compared to the large pharmaceutical companies "they wait for others to innovate. When others innovate, they acquire them”

Some banks still use core software purchased 30 or more years ago, and have layered on top of it "ancillary" products such as online banking and mobile banking software, creating a complex IT environment that is hard to manage and upgrade to launch new products and comply with emerging regulations

Banks should be seeking out modern architectures that can withstand the test of time

A few core banking products out there are well positioned to last the next 20 to 30 years, the rest "are a rewrite waiting to happen

This poses a number of challenges when trying to stress test a Bank’s portfolio:

Many of the stress testing data fields are not standard core data fields and must be added using specially configured user defined fields

These can be hard to access, hard to load and hard to maintain

Many Bank’s do not maintain the stress testing data on core, or only limited data

We often see LTV and DSC on the core but not the data required to calculate and stress test those ratios

Many Banks have to pay to run a core extract of their own data for use in a third party application

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Banks struggle with multiple technology platforms and outdated systems . . .

Data mining is the key to success . . .

Loan underwriting systems need to be brought into the digital age

Loan documents and data need to be digitized

Loan files contain a wealth of information that is currently not being properly captured or utilized for a whole host of risk management practices

Does your loan system currently capture and report on:

Vacancy rates

NOI

DSC

LTV

Personal Guarantee

Recourse vs. Non-Recourse

Interest only term

Total loan to one borrower exposure

Purpose (Cash out refinance or purchase?)

Address of collateral; not borrower

Collateral data on all collateral for multiple collateral loans

Data for all Borrower/Guarantor

Total exposure, including first, second and other liens

Credit tenant name/ exposure

Cap rates utilized during underwriting

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The industry is screaming right now for tools to aid in the data mining, segmentation and stress testing process . . .

Borrower Information

Tax Documents

Up-to-date Account

Information

Borrower

Information

Collateral Info

• Rent Rolls

• Operating Statement

• Appraisal Information

• YOY Tracking

Standardized Loan Codes

Risk Rating

Analysis

• Standardized Risk Rating Matrix

• YOY Tracking

Loan Reports

• Credit Memo

• Letter of Intent

• Commitment Letter

• Global Cash flows

Loan Tracking

• Delinquency Notifications

• Annual Reviews

Loan

Information

Pathway InformationPortfolio

Reports

Stress Testing /

Concentration

Reports

Policy

Compliance

Internal

Approval

Workflow

Quality Control /

Auditing

Adherence to

Regulatory

Requirements


What did we build and why?

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LONOS Started as a consulting engagement – we realized the following benefits:

1. One source to capture, store and access data

2. Gets the data and documents digitized

3. Eliminates restrictions of core system

4. Keeps history of financials, appraisals, rent rolls and operating statements

5. Better document management – forces review of rent rolls and operating statements

6. More thorough documentation

7. Makes it easy to handle multiple borrow/guarantors and multiple collateral

8. Captures data required for CECL

9. Cleaner and more complete stress testing data

10. Overcomes limits of existing stress testing systems

11. Can be tied to policies (policy exceptions, risk ratings, etc.)

12. Better underwriting

13. Better annual reviews

14. No additional people cost

15. Platform of the future – phase 2 modules (CECL)

16. Breaks down silos – will integrate into CGMT platform

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FinPro built a loan underwriting, segmentation and stress testing system to address the issues we uncovered while running CRE stress test analyses . . .

Loan level stress testing is critical, not all loans are created equal . . .

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Upon a more detailed analysis, the loan with more attractive credit

characteristics should have a lower level of reserves.

Two commercial real estate loans, with the same balance and rate, but

drastically different characteristics.

A Tale of Two Commercial Real Estate Loans

$5,000 Loan Value ($000s) $5,000

6.5% Interest Rate 6.5%

$98 Monthly Payment ($000s) $98

105.0% Debt Service Coverage Ratio 150.0%

$103 Cash Available to Cover Debt $147

$78 Shock to Available Cash (-$25,000) $122

79.4% New Debt Service Coverage Ratio 124.4%

90.0% Loan to Value 65.0%

$5,556 Property Value $7,692

$4,444 Decrease in Property Value (-20%) $6,154

112.5% Resulting Loan to Value 81.3%


$5,000 Loan Value ($000s) $5,000












$5,000 Loan Value ($000s) $5,000












$5,000 Loan Value ($000s) $5,000












$5,000 Loan Value ($000s) $5,000











Breaking out loan concentrations into a more granular view can also tell a different story . . .

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100 1.00 1.20 1.25 1.30 1.40 1.50 1.80 2.00 1E+32

45% 2% 3% 1% 0% 2% 5% 10% 3% 30%

55% 1% 4% 0% 1% 1% 5% 5% 5% 11%

65% 5% 3% 2% 10% 3% 5% 10% 4% 5%

75% 5% 7% 1% 9% 5% 10% 4% 3% 5%

80% 0% 0% 0% 0% 4% 0% 1% 0% 0%

90% 0.0% 0.0% 0.0% 0.0% 6% 0% 0% 0% 7%

100% 0.0% 0.0% 0.0% 0.0% 0% 0% 1% 1% 0%

110% 0.0% 0.0% 0.0% 0.0% 0% 1% 0% 0% 0%

1E+32 0.0% 0.0% 0.0% 0.0% 0% 0% 0% 0% 0%

100 1.00 1.20 1.25 1.30 1.40 1.50 1.80 2.00 1E+32

45%

55% Higher Probability Default

65% Lower Potential Loss

75% 34% 156%

80%

90%

100%

110%

1E+32 6% 10%

Lower Probability Default

Higher Potential Loss

Higher Probability Default

Higher Potential Loss

LTV

DSC

LTV

DSC

Lower Probability Default

Lower Potential Loss

Loan Composition Dec-15 Balance

% of Risk-

based

Capital

Residential Mortgages 75,352 178.83%

Home Equity Loans 32,100 76.18%

Multi-family Mortgages 6,834 16.22%

Owner Occ. Commercial Real Estate 75,074 178.17%

Non Owner Occ. Commercial Real Estate 91,098 216.20%

Construction & Land Loans 38,060 90.33%

Farm Loans 1,608 3.82%

Agricultural Prod Loans 117 0.28%

Commercial & Industrial Loans 25,446 60.39%

Consumer Loans 818 1.94%

Other Loans 16 0.04%

Total Loans 346,523

Regulatory CRE Guidance 135,992 322.75%

Step 1: Select concentrationmetric from dropdown

Portfolio breakdown as a percentage of Risk-based Capital

Low risk of loss

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MULTIPLE CUSTOM STRESS TEST SCENARIOS ARE CREATED TO PREDICT POTENTIAL LOSS IN THE BANK’S CRE PORTFOLIO

EXAMPLES OF SINGLE VARIABLE STRESS TESTS:

• Stress Test 1: Expense Increases by 5%

• Stress Test 2: Income Declines by 5%

• Stress Test 3: Rates Increase by 2%

• Stress Test 4: Cap Rate Increase by 1%

EXAMPLES OF MULTI-VARIABLE STRESS TESTS:

(in line with the 3 FRB stress tests):

• Scenario 1: Baseline

- Income Increases 2% (GDP change)

- Expense Increases 2% (CPI change)

- Rates Increase 0.75% (average change over the 3 yrs)

- Property values increase 4.5% (CRE value change)

• Scenario 2: Adverse

- Income Decreases 1.75% (GDP change)

- Expense Decrease 0.50% (CPI change)

- Rates Increase 0.33% (average change over the 3 yrs)

- Property values decrease 12.0% (CRE value change)

• Scenario 3: Severely Adverse

- Income Decreases 4.35% (GDP change)

- Expense Increase 0.75% (CPI change)

- Rates decrease 1.50% (average change over the 3 yrs)

- Property values decrease 30.0% (CRE value change)

Estimated Current: Severely Adverse Loss Given

Count Balance Deficiency $ Default $

10% - - - -

20% - - - -

30% 6 4,727,892 - -

40% 6 2,849,825 - -

50% 3 2,195,957 - -

60% 7 7,591,272 - -

70% 4 1,186,693 - -

80% 11 7,165,581 - -

90% 8 4,148,665 62,664 42,038

100% 11 11,394,308 1,350,757 305,247

110% 8 5,985,743 1,178,795 810,794

120% 10 12,512,575 3,238,953 1,761,242

130% 10 19,709,638 6,412,231 3,646,604

140% 5 4,414,125 1,559,410 527,515

150% 1 8,160,000 3,466,326 -

160% 1 6,000,000 2,709,504 1,354,752

170% 1 1,473,761 731,875 658,687

180% 3 5,092,810 2,621,940 512,512

190% - - - -

200% - - - -

1E+19 2 1,389,991 869,186 513,270

Total 97 105,998,835 24,201,639 10,132,660

Total Above 100% LTV 41 64,738,642

Total Above 80% LTV 60 80,281,615

Actual Adjusted

Sep-16 Sep-16

Tier 1 leverage capital 13.52% 11.85% 7.50%

Total Risk-based 18.93% 16.75% 10.50%

LTV SUMMARY

In order to stress test the CRE loan portfolio, a range of stress tests and scenarios need to be created and run . . .

*Source: FRB 2016 Supervisory scenarios for Annual Stress Tests required under Dodd-Frank Act Stress Testing Rules and the Capital Plan Rules

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And stress testing should also provide insight on what loans have more imbedded credit risk . . .

Estimated Current Count Balance Deficiency $

0% 10% 148 3,618,820 -

10% 20% 131 8,096,427 -

20% 30% 98 12,987,306 -

30% 40% 124 20,856,876 -

40% 50% 130 24,335,238 -

50% 60% 165 38,057,287 -

60% 70% 192 58,527,524 -

70% 80% 216 74,261,351 -

80% 90% 43 11,376,296 -

90% 100% 4 2,229,136 -

100% 110% 1 235,199 19,199

110% 120% 1 339,168 34,668

120% 130% 2 576,490 106,300

130% 140% - - -

140% 150% 1 530,891 160,891

150% 160% - - -

160% 170% - - -

170% 180% 1 488,887 213,887

180% 190% - - -

190% 200% - - -

200% 1 535,236 475,236

Total 1,258 257,052,131

Total Above 100% LTV 7 2,705,871 1,010,181

Total Above 80% LTV 54 16,311,303

Not Classified 175 22,190,058

Total 1,433 279,242,189

LTV SUMMARY - Current Quarter

Estimated Current Count Balance Deficiency $

0% 10% 116 2,348,437 -

10% 20% 114 5,751,759 -

20% 30% 88 9,208,200 -

30% 40% 84 9,887,028 -

40% 50% 99 18,364,005 -

50% 60% 110 20,376,269 -

60% 70% 112 26,790,775 -

70% 80% 146 32,805,011 -

80% 90% 165 56,549,854 -

90% 100% 170 58,659,491 -

100% 110% 39 10,341,138 513,938

110% 120% 8 3,264,294 390,694

120% 130% - - -

130% 140% 2 574,367 157,967

140% 150% - - -

150% 160% 2 576,490 200,338

160% 170% - - -

170% 180% 1 530,891 234,891

180% 190% - - -

190% 200% - - -

200% 2 1,024,123 756,123

Total 1,258 257,052,131

Total Above 100% LTV 54 16,311,303 2,253,951

Total Above 80% LTV 389 131,520,647

Not Classified 175 22,190,058

Total 1,433 279,242,189

LTV SUMMARY - Current Quarter (Stress Test - 20% )

Identify and review these loans

Regulatory guidance encourages institutions to stratify the CRE portfolio by

property type,

geographic market,

tenant concentrations,

tenant industries,

developer concentrations, and

risk rating.

Other useful stratifications may include

loan structure (for example, fixed rate or adjustable),

loan purpose (for example, construction, short-term, or permanent),

loan-to-value limits,

debt service coverage,

policy exceptions on newly underwritten credit facilities, and

Affiliated loans (for example, loans to tenants).

An institution should also be able to identify and aggregate exposures to a borrower, including its credit exposure relating to derivatives

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Regulatory guidance and industry best practices management dictate that a Bank should segment its CRE portfolio in detail to identify areas of concentration and elevated risk . . .

Category LoansExposure as %

of RBC Expected LossEL as %of

RBC Loss RateDSC1.00 34,039,114 11% 3,533,698 1% 10%1.20 76,399,658 25% 1,089,224 0% 1%1.25 26,827,694 9% 976,483 0% 4%1.30 62,121,198 21% 3,284,996 1% 5%1.40 104,054,544 35% 2,386,946 1% 2%1.50 161,269,410 54% 2,800,911 1% 2%1.80 739,127,104 246% 16,883,709 6% 2%2.00 385,726,901 129% 2,477,119 1% 1%

Greater than 2.00 364,175,099 121% 2,022,563 1% 1%

Total 1,953,740,723 651% 35,455,649 12% 2%Cap Rates4% 67,798,410 23% 11,728,498 4% 17%6% 382,304,703 127% 10,065,179 3% 3%8% 944,646,970 315% 12,346,539 4% 1%10% 262,730,694 88% 1,241,598 0% 0%12% 93,902,083 31% 62,777 0% 0%15% 81,086,716 27% 9,893 0% 0%

Greater than 15% 121,271,148 40% 1,165 0% 0%

Total 1,953,740,723 651% 35,455,649 12% 2%

Category LoansExposure as %

of RBC Expected LossEL as %of

RBC Loss Rate

Exposure Limit % of

RBC

In Complia

nce?

Non-Owners OccupiedCommercial - other business property 13,768,467 5% 19,360 0% 0.1% 25% YesHealth Care 54,777,816 18% - 0% 0.0% 15% NoHotels and Other Hospitality 91,328,122 30% 415,453 0% 0.5% 50% YesIndustrial (incl Warehouse) 16,145,001 5% 330,136 0% 2.0% 50% YesMedical Offices 36,475,970 12% 44,581 0% 0.1% 75% YesMixed Commercial (Retail/Office) 35,395,160 12% 128,104 0% 0.4% 75% YesMixed Use (Cml/Resi) 48,010,220 16% 545,162 0% 1.1% 25% YesMulti Family (4+ units) 1,318,534,256 440% 26,289,781 9% 2.0% 500% YesOffice 64,931,959 22% 2,292,190 1% 3.5% 75% YesRetail 148,752,147 50% 2,980,686 1% 2.0% 100% Yes

Vacant Land 317,602 0% - 0% 0.0% 15% Yes

Total 1,828,436,722 609% 33,045,453 11% 1.8% 650% YesOwner Occupied1st or Jr l iens on residential property 121,193 0% - 0% 0.0% 25% YesCommercial - other business property 43,825,727 15% 1,588,589 1% 3.6% 50% YesGolf Courses 2,088,606 1% - 0% 0.0% 50% YesIndustrial (incl Warehouse) 19,677,834 7% 933 0% 0.0% 100% YesMedical Offices 20,868,552 7% 408,547 0% 2.0% 75% YesMixed Commercial (Retail/Office) 4,964,632 2% 89,368 0% 1.8% 100% YesMixed Use (Cml/Resi) 4,032,825 1% 545 0% 0.0% 50% YesOffice 15,985,380 5% 2,718 0% 0.0% 50% YesRetail 13,739,252 5% 319,496 0% 2.3% 75% Yes

Vacant Land - 0% - 0% 0.0% 10% Yes

Total 125,304,001 42% 2,410,196 1% 1.9% 100% Yes

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Segmentation analysis needs to look at the portfolio by a range of stratifications and measure to established portfolio limits . . .

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Segmentation analysis also identifies areas where a deeper look is required . . .

In this example of a Bank with a high multi family concentration, rents are on the lower end of market rent. In a stressed environment these loans are anticipated to outperform similar properties with higher average rents as Management anticipates tenants will "trade down" to apartments with a lower rents. As such, the higher-rent apartments are expected to see higher losses under stress.

NJ NY PA Total

10 1,341 1,567 3,097 1,460

15 1,473 1,450 646 1,440

20 1,085 1,292 748 1,180

30 1,145 1,207 852 1,141

40 1,008 1,156 725 1,093

75 983 1,130 820 1,038

100 1,058 999 1,054 1,032

1E+32 866 956 782 859

Total 989 1,123 826 1,022

Total Units

Average Rent Per Unit per month

1. Integrated Borrower, Collateral, Appraisal, Rent Roll Information

No more flipping through various Excel workbooks and word documents to find the information you need on a loan or inconsistencies in the same borrower's information between files. Standardize your information gathering onto one platform with LONOS. The database fully contemplates all of the many to many relationships. Therefore, updating information is done in one place and automatically linked to the associated files, giving you more reliable, trustworthy data.

2. Detailed Stress Testing

Interested in seeing how your portfolio stacks up in an economic downturn? Want to stress geographical and property/collateral specific factors? LONOS makes this easy, providing you with the tools to stress test at the individual loan level and at the portfolio level.

3. Integrated Policy Adherence

Want to impress the board while streamlining compliance? LONOS integrates policy adherence scorecards with approval information at the loan level. We recognize your risk appetite is unique, the rules are easily customized by you to conform to your loan policy.

4. Integrated Risk Grading

LONOS can easily by customized by the institution to incorporate any risk grading scoring matrix. The tool automatically grades quantitative fields from data already in LONOS based on ranges imputed by the administrative user. Customizable to each loan type, qualitative measures can also be incorporated.

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LONOS is built on a modular platform with components which address current needs in data capture, segmentation and stress testing, policy adherence and risk grading, and accommodate future modules such as CECL . . .

LONOS Better Data, Streamlined Process, Enhanced Analytics

1. Quality Control in Process and Data

2. Capture More Detailed Data, While Integrating with Core Data

3. More Detailed Loan Segmentation

4. Enables Heightened Risk Management Stress Testing

5. Allows for More Flexible and Detailed Analytics

6. Mitigates Regulatory Criticism

7. Streamlined Operational Efficiencies

8. Integrated Loan Status Tracking with Approval Process

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And LONOS addresses a number of critical needs that Bank face right now . . .

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Thank you for participating in today’s conference . . .

To schedule a demo or for more information, please contact:

Don Musso

908-234-9398 ext. 101

[email protected]

Stephen Brown Klinger

908-234-9398 ext. 112

[email protected]

Steve Musso

908-234-9398 ext. 105

[email protected]