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Allowance for Credit Losses

6 Months Ended

Jun. 30, 2020

Allowance for Credit Losses Methodology

The Allowance for Credit Losses is an important element in the Bank's financial statements. In accordance with CECL, the ACL represents management's estimate of lifetime credit losses for assets within its scope, specifically loans and leases and unfunded commitments. To calculate the ACL, management uses models to estimate the PD and LGD for loans utilizing inputs that include forecasted future economic conditions and that are dependent upon specific macroeconomic variables relevant to each of the Bank's loan and lease portfolios. Moody's Analytics, a third party, provided the historical and forward-looking macroeconomic data used in the development of the models used to calculate the ACL.

For ACL calculation purposes, the Bank considered the financial and economic environment at the time of assessment and economic scenarios that differed in the levels of severity and sensitivity to the ACL results. At each measurement date, the Bank selects the scenario that reflects its view of future economic conditions and is determined to be the most probable outcome.

All forecasts are updated monthly for each variable where applicable and incorporated as relevant into the ACL calculation. Actual credit loss results will differ from the estimate of credit losses, either in a strong economy or a recession, as our portfolio will change through time due to growth, risk mitigation actions and other factors. In addition, the scenarios used will differ and change through time as economic conditions change. Economic scenarios might not capture deterioration or improvement in the economy timely enough for the Bank to be able to adequately assess the impact to the ACL.

Select macroeconomic variables are projected over the forecast period, and they could have a material impact in determining the ACL. As the length of the forecast period increases, information about the future becomes less readily available and projections are inherently less certain.

The following is a discussion of the changes in the factors that influenced management's current estimate of expected credit losses. The changes in the ACL estimate for all portfolio segments, during the three and six months ended June 30, 2020, were primarily related to changes in the economic assumptions. The Bank opted to use Moody's Analytics June consensus economic forecast for estimating the ACL as of June 30, 2020. This scenario is based on Moody's Analytics review of a variety of surveys of baseline forecasts of the U.S. economy. These surveys vary in date of latest vintage, number of updates per year, list of variables forecast, duration of forecast, frequency of data (quarterly or annual), and the number of respondents to a survey. In the preparation of the Moody's Analytics consensus forecast, the focus is on the next three to five years, since that is the most typical duration in the surveyed results. Moody's Analytics approach is to give greater consideration to whatever forecasts were produced most recently, since they will include the most up-to-date historical information, and to those variables for which the number of surveyed responses is largest.

In the consensus scenario selected, the probability that the economy will perform better than this consensus is equal to the probability that it will perform worse and included the following factors:

•real GDP peak-to-trough is approximately negative 12%, on a cumulative basis;

•U.S. unemployment rate is 15.8% in the second quarter of 2020 and is expected to be 11.2% in the third quarter of 2020;

•substantial recovery in the third quarter of 2020, then continued growth;

•return to less than 5% unemployment by 2024;

•LIBOR rates include the rate decrease that occurred in April 2020.

The Bank uses an additional scenario that differs in terms of severity within the variables, both favorable and unfavorable to assess sensitivity in the ACL results and to inform qualitative adjustments. The Bank selected the Moody's Analytics April baseline scenario for this analysis. In the baseline scenario selected, the probability that the economy will perform better than the baseline scenario is equal to the probability that it will perform worse and includes the following factors:

•recession in the first and second quarters of 2020;

•real GDP peak-to-trough is approximately negative 11%, on a cumulative basis;

•U.S. unemployment rate expected to peak at 13% in the second quarter of 2020;

•substantial recovery in the third quarter of 2020, then slow growth with higher acceleration later in 2021;

•return to less than 5% unemployment by 2023.

The results using the April baseline scenario for sensitivity analysis were reviewed by management, but management believes the consensus scenario better reflects the economic environment.

The ACL is measured on a collective (pool) basis when similar characteristics exist. The Company has selected models at the portfolio level using a risk-based approach, with larger, more complex portfolios having more complex models. Except as noted below, the macroeconomic variables that are inputs to the models are reasonable and supportable over the life of the loans in that they reasonably project the key economic variables in the near term and then converge to a long run equilibrium trend. These models produce reasonable and supportable estimates of loss over the life of the loans as the projected credit losses will also converge to a steady state in line with the variables applied. The Company measures the ACL using the following methods:

Commercial Real Estate ("CRE"): Non-owner occupied commercial real estate, multifamily, and construction loans are analyzed using a model that uses four primary property variables: Net Operating Income ("NOI"), Property Value, Property Type, and Location. For PD estimation, the model simulates potential future paths of NOI given commercial real estate market factors determined from macroeconomic forecasts. Using the resulting expected debt service coverage ratios, together with predicted loan-to-values and other variables, the model estimates PD from the range of conditional possibilities. In addition, the model estimates maturity PD capturing refinance default risk to produce a total PD for the loan. The model estimates LGD, inclusive of principal loss and liquidation expenses, empirically using predicted loan-to-value as well as certain market and other factors. The LGD calculation also includes a separate maturity risk component. The primary economic drivers in the model are GDP Growth, U.S. unemployment rate, and 10-Year Treasury yield. The model produces PD and LGD on a quarter-by-quarter basis for the life of loan.

The owner-occupied commercial real-estate portfolio utilizes a top down macroeconomic model using linear regression. This model produces portfolio level quarterly net charge-off rates for 10 years. The primary economic drivers for this model are the 7-year A vs Aa corporate bond spread and S&P 500 corporate after-tax profits.

Commercial: Non-homogeneous commercial loans and leases and residential development loans are analyzed in a multi-step process. An initial PD is estimated using a model driven by an obligor's selected financial statement ratios, together with cycle-adjusting information based on the obligor's state and industry. An initial LGD is derived separately based on collateral type using collateral value and a haircut to reflect the loss in liquidation. Another model then applies an auto-regression technique to the initial PD and LGD metrics to estimate the PD and LGD curves according to the macroeconomic scenario over a one-year reasonable and supportable forecast. The primary economic drivers in the model are the S&P 500 Stock Price Index, S&P 500 Market Volatility Index, U.S. unemployment rate, as well as appropriate yield curves and credit spreads. This model utilizes output reversion methodology, which, after one year, reverts on a straight-line basis over two years to long-term PD estimated using financial statement ratios of each obligor.

The model for the homogeneous lease and equipment finance agreement portfolio uses lease and equipment finance agreement information, such as origination and performance, as well as macroeconomic variables to calculate PD and LGD values. The PD calculation is based on survival analysis while LGD is calculated using a two-step regression. The model calculates LGD using an estimate of the probability that a defaulted lease or equipment finance agreement will have a loss, and an estimate of the loss amount. The primary economic drivers for the model are GDP, U.S. unemployment rate, and a home price growth index. The model produces PD and LGD curves at the lease level for each month in the forecast horizon.

Residential: The models for residential real estate and Home Equity Lines of Credit ("HELOC") utilize loan level variables, such as origination and performance, as well as macroeconomic variables to calculate PD and LGD. The U.S. unemployment rate and home price growth rate indexes are primary economic drivers in both the residential real estate and HELOC models. In addition, the prime rate is also a primary driver in the HELOC model. The models focus on establishing an empirical relationship between default probabilities and a set of loan-level, borrower, and macroeconomic credit risk drivers. The LGD calculation for residential real estate is based on an estimate of the probability that a defaulted loan will have a loss, and then an estimate of the loss amount. HELOCs utilize the same model using residential real estate LGD values to assign loans to cohorts based on FICO scores and loan age. The model produces PD and LGD curves at the loan level for each quarter in the forecast horizon.

Consumer: Historical net charge-off information as well as economic forecast assumptions are used to project loss rates for the Consumer segment.

All loans and leases that have not been modeled receive a loss rate via an extrapolated rate methodology. The loans and leases receiving an extrapolated rate are typically newly originated loans and leases or loans and leases without the granularity of data necessary to be modeled. Based on the vintage year, credit classification, and reporting category of the modeled loans and leases, a loss factor is calculated and applied to the non-modeled loans and leases.

Along with the quantitative factors produced by the above models, management also considers prepayment speeds and qualitative factors when determining the ACL. The Company uses a prepayment model that forecasts the constant prepayment rates based on institution specific data. Below are the nine qualitative factors considered where applicable:

•Changes in lending policies and procedures, including changes in underwriting standards and collection, charge-off, and recovery practices not considered elsewhere in estimating credit losses.

•Changes in national, regional, and local economic and business conditions and developments that affect the collectability of the portfolio, including the condition of various market segments.

•Changes in the nature and volume of the portfolio and in the terms of loans and leases.

•Changes in the experience, ability, and depth of lending management and other relevant staff.

•Changes in the volume and severity of past due loans and leases, the volume of non-accrual loans and leases, and the volume and severity of adversely classified or graded loans and leases.

•Changes in the quality of the Bank's credit review system.

•Changes in the value of the underlying collateral for collateral-dependent loans and leases.

•The existence and effect of any concentrations of credit, and changes in the level of such concentrations.

•The effect of other external factors such as competition and legal and regulatory requirements on the level of estimated credit losses in the Bank's existing portfolio.

The Company evaluated each qualitative factor as of June 30, 2020, and concluded that a $42.0 million decrease to the model results was appropriate, due to model limitations in the current economic environment. Certain models were deemed to be over predicting losses in the current environment, because the economic variables used in these models do not take into account government stimulus programs, such as expanded unemployment benefits, and also do not take into account the payment deferral programs offered by the Bank. Other models were deemed to be under predicting losses, because certain economic variables were lagging indicators and had not yet shown the effects of the current recession.

Loss factors from the models, prepayment speeds, and qualitative factors are input into the Company's CECL accounting application which aggregates the information. The Company then uses two methods to calculate the current expected credit loss: 1) the discounted cash flow ("DCF") method, which is used for all loans except lines of credit and 2) the non-discounted cash flow method which is used for lines of credit due to difficulty of calculating an effective interest rate when lines have yet to be drawn on. The DCF method utilizes the effective interest rate of individual assets to discount the expected credit losses adjusted for prepayments. The difference in the net present value and the amortized cost of the asset will result in the required allowance. The non-discounted cash flow method uses the exposure at default, along with the expected credit losses adjusted for prepayments to calculate the required allowance.

The following tables summarize activity related to the allowance for credit losses by portfolio segment for the three and six months ended June 30, 2020:


	Three Months Ended June 30, 2020
(in thousands)	Commercial Real Estate		Commercial		Residential		Consumer & Other		Total
Allowance for credit losses on loans and leases
Balance, beginning of period	$	99,778	$	146,607	$	34,251	$	10,784	$	291,420

Provision for credit losses for loans and leases ⁽¹⁾	52,890		21,301		6,157		1,136		81,484

Charge-offs	—		(17,549)		(143)		(1,761)		(19,453)
Recoveries	160		2,256		283		595		3,294
Net recoveries (charge-offs)	160		(15,293)		140		(1,166)		(16,159)
Balance, end of period	$	152,828	$	152,615	$	40,548	$	10,754	$	356,745
Reserve for unfunded commitments
Balance, beginning of period	$	15,760	$	2,927	$	1,741	$	499	$	20,927

Provision (recapture) for credit losses on unfunded commitments ⁽¹⁾	5,048		(6)		320		79		5,441
Balance, end of period	20,808		2,921		2,061		578		26,368
Total allowance for credit losses	$	173,636	$	155,536	$	42,609	$	11,332	$	383,113


	Six Months Ended June 30, 2020
(in thousands)	Commercial Real Estate		Commercial		Residential		Consumer & Other		Total
Allowance for credit losses on loans and leases
Balance, beginning of period	$	50,847	$	73,820	$	24,714	$	8,248	$	157,629
Impact of adoption CECL	5,077		44,009		2,099		(1,186)		49,999
Adjusted balance, beginning of period	55,924		117,829		26,813		7,062		207,628
Provision for credit losses for loans and leases ⁽¹⁾	96,498		70,974		13,342		6,172		186,986

Charge-offs	—		(40,157)		(154)		(3,597)		(43,908)
Recoveries	406		3,969		547		1,117		6,039
Net recoveries (charge-offs)	406		(36,188)		393		(2,480)		(37,869)
Balance, end of period	$	152,828	$	152,615	$	40,548	$	10,754	$	356,745
Reserve for unfunded commitments
Balance, beginning of period	$	534	$	2,539	$	149	$	1,884	$	5,106
Impact of adoption CECL	4,030		(487)		1,267		(1,572)		3,238
Adjusted balance, beginning of period	4,564		2,052		1,416		312		8,344
Provision for credit losses on unfunded commitments⁽¹⁾	16,244		869		645		266		18,024
Balance, end of period	20,808		2,921		2,061		578		26,368
Total allowance for credit losses	$	173,636	$	155,536	$	42,609	$	11,332	$	383,113

⁽¹⁾ The total provision for credit losses as disclosed on the income statement includes an additional $160,000 in provision related to accrued interest on loans deferred due to COVID-19, which is not included in the tables above.

The following tables summarize activity related to the allowance for loan and lease losses by loan and lease portfolio segment and the reserve for unfunded commitments for the three and six months ended June 30, 2019:


	Three Months Ended June 30, 2019
(in thousands)	Commercial Real Estate		Commercial		Residential		Consumer & Other		Total
Allowance for credit losses on loans and leases
Balance, beginning of period	$	47,841	$	64,370	$	22,173	$	10,488	$	144,872
Provision	1,324		16,069		1,398		561		19,352
Charge-offs	(387)		(14,697)		(67)		(1,556)		(16,707)
Recoveries	219		2,611		150		572		3,552
Net (charge-offs) recoveries	(168)		(12,086)		83		(984)		(13,155)
Balance, end of period	$	48,997	$	68,353	$	23,654	$	10,065	$	151,069
Reserve for unfunded commitments
Balance, beginning of period	$	603	$	2,347	$	162	$	1,542	$	4,654
(Recapture) provision for credit losses on unfunded commitments	(42)		248		(5)		2		203
Balance, end of period	561		2,595		157		1,544		4,857
Total allowance for credit losses	$	49,558	$	70,948	$	23,811	$	11,609	$	155,926

	Six Months Ended June 30, 2019
(in thousands)	Commercial Real Estate		Commercial		Residential		Consumer & Other		Total
Allowance for credit losses on loans and leases
Balance, beginning of period	$	47,904	$	63,957	$	22,034	$	10,976	$	144,871
Provision	3,075		27,338		1,517		1,106		33,036
Charge-offs	(2,538)		(27,907)		(202)		(3,212)		(33,859)
Recoveries	556		4,965		305		1,195		7,021
Net (charge-offs) recoveries	(1,982)		(22,942)		103		(2,017)		(26,838)
Balance, end of period	$	48,997	$	68,353	$	23,654	$	10,065	$	151,069
Reserve for unfunded commitments
Balance, beginning of period	$	628	$	2,250	$	160	$	1,485	$	4,523
(Recapture) provision for credit losses on unfunded commitments	(67)		345		(3)		59		334
Balance, end of period	561		2,595		157		1,544		4,857
Total allowance for credit losses	$	49,558	$	70,948	$	23,811	$	11,609	$	155,926

The following table presents the unfunded commitments for the period ended June 30, 2020 and 2019:


(in thousands)	Total
Unfunded loan and lease commitments
June 30, 2020	$	5,849,611
June 30, 2019	$	5,587,294

Asset Quality and Non-Performing Loans and Leases

We manage asset quality and control credit risk through diversification of the loan and lease portfolio and the application of policies designed to promote sound underwriting and loan and lease monitoring practices. The Bank's Credit Quality Administration is charged with monitoring asset quality, establishing credit policies and procedures and enforcing the consistent application of these policies and procedures across the Bank. Reviews of non-performing, past due loans and leases and larger credits, designed to identify potential charges to the allowance for credit losses, and to determine the adequacy of the allowance, are conducted on an ongoing basis. These reviews consider such factors as the financial strength of borrowers, the value of the applicable collateral, loan and lease loss experience, estimated loan and lease losses, growth in the loan and lease portfolio, prevailing economic conditions and other factors.

Loans and Leases Past Due and Non-Accrual Loans and Leases

Typically, loans in a non-accrual status will not have an allowance for credit loss as they will be written down to their net realizable value or charged-off. However, the net realizable value for homogeneous leases and equipment finance agreements is determined by the LGD calculated by the CECL model and therefore leases and equipment finance agreements on non-accrual will have an allowance for credit losses until they become 181 days past due, at which time they are charged-off. The Company recognized no interest income on non-accrual loans and leases during the three and six months ended June 30, 2020. Loans of approximately $1.8 billion, are currently deferred under the CARES Act and are classified as current as their contractual payments have been deferred.

The following tables present the amortized cost basis of the loans and leases past due, by loan and lease class, as of June 30, 2020 and December 31, 2019:


	June 30, 2020
(in thousands)	Greater than 30 to 59 Days Past Due		60 to 89 Days Past Due		Greater than 90 Days and Accruing		Total Past Due		Non-Accrual ⁽¹⁾		Current		Total Loans and Leases
Commercial real estate
Non-owner occupied term, net	$	6,006	$	—	$	—	$	6,006	$	8,095	$	3,575,383	$	3,589,484
Owner occupied term, net	6,336		142		1		6,479		4,148		2,449,327		2,459,954
Multifamily, net	—		—		—		—		599		3,466,230		3,466,829
Construction & development, net	—		—		—		—		—		662,703		662,703
Residential development, net	—		—		—		—		—		164,180		164,180
Commercial
Term, net	94		—		3		97		11,027		4,253,968		4,265,092
Lines of credit & other, net	3,766		193		1		3,960		763		935,720		940,443
Leases & equipment finance, net	4,177		10,774		834		15,785		7,780		1,498,804		1,522,369
Residential
Mortgage, net⁽²⁾	1,965		3,438		39,728		45,131		—		4,011,457		4,056,588
Home equity loans & lines, net	1,411		643		1,475		3,529		—		1,185,899		1,189,428
Consumer & other, net	1,068		570		361		1,999		—		352,386		354,385
Total, net of deferred fees and costs	$	24,823	$	15,760	$	42,403	$	82,986	$	32,412	$	22,556,057	$	22,671,455

⁽¹⁾ Loans and leases on non-accrual had a related allowance for credit losses of $7.1 million at June 30, 2020, related to an amortized cost basis of $32.4 million.

⁽²⁾ Includes government guaranteed GNMA mortgage loans that the Bank has the right but not the obligation to repurchase that are past due 90 days or more, totaling $2.6 million at June 30, 2020.


	December 31, 2019
(in thousands)	Greater than 30 to 59 Days Past Due		60 to 89 Days Past Due		Greater than 90 Days and Accruing		Total Past Due		Non-Accrual		Current and Other ⁽¹⁾		Total Loans and Leases
Commercial real estate
Non-owner occupied term, net	$	—	$	—	$	121	$	121	$	2,920	$	3,542,525	$	3,545,566
Owner occupied term, net	975		470		1		1,446		4,600		2,490,042		2,496,088
Multifamily, net	—		—		—		—		—		3,514,774		3,514,774
Construction & development, net	—		—		—		—		—		678,740		678,740
Residential development, net	—		—		—		—		—		189,010		189,010
Commercial
Term, net	136		381		—		517		3,458		2,228,842		2,232,817
Lines of credit & other, net	3,548		376		36		3,960		767		1,207,666		1,212,393
Leases & equipment finance, net	10,685		11,176		3,086		24,947		14,499		1,426,043		1,465,489
Residential
Mortgage, net⁽²⁾	—		8,104		36,642		44,746		—		4,170,678		4,215,424
Home equity loans & lines, net	2,173		867		1,804		4,844		—		1,232,668		1,237,512
Consumer & other, net	2,043		948		615		3,606		—		404,265		407,871
Total, net of deferred fees and costs	$	19,560	$	22,322	$	42,305	$	84,187	$	26,244	$	21,085,253	$	21,195,684

⁽¹⁾ Other includes purchased credit impaired loans of $89.5 million.

⁽²⁾ Includes government guaranteed GNMA mortgage loans that the Bank has the right but not the obligation to repurchase that are past due 90 days or more, totaling $4.3 million at December 31, 2019.

Collateral Dependent Loans and Leases

The following table summarizes the amortized cost basis of the collateral dependent loans and leases by the type of collateral securing the assets as of June 30, 2020. There have been no significant changes in the level of collateralization from the prior periods.


(in thousands)	Residential Real Estate		Commercial Real Estate		General Business Assets		Other		Total
Commercial real estate
Non-owner occupied term, net	$	—	$	8,328	$	—	$	—	$	8,328
Owner occupied term, net	102		4,845		—		—		4,947
Multifamily, net	—		840		—		—		840


Commercial
Term, net	763		—		575		671		2,009
Line of credit & other, net	952		68		9,167		2,863		13,050
Leases & equipment finance, net	—		—		7,780		—		7,780
Residential
Mortgage, net	2,507		—		—		—		2,507
Home equity loans & lines, net	101,862		—		—		—		101,862

Total net of deferred fees and costs	$	106,186	$	14,081	$	17,522	$	3,534	$	141,323

Troubled Debt Restructurings

At June 30, 2020 and December 31, 2019, troubled debt restructured loans of $15.0 million and $18.6 million, respectively, were classified as accruing TDR loans. The TDRs were granted in response to borrower financial difficulties, and generally provide for a temporary modification of loan repayment terms. In order for a new TDR loan to be considered for accrual status, the loan's collateral coverage generally will be greater than or equal to 100% of the loan balance, the loan is current on payments, and the borrower must either prefund an interest reserve or demonstrate the ability to make payments from a verified source of cash flow.

The following tables present troubled debt restructurings by accrual versus non-accrual status and by portfolio segment as of June 30, 2020 and December 31, 2019:


	June 30, 2020
(in thousands)	Accrual Status		Non-Accrual Status		Total Modification		# of Contracts
Commercial real estate, net	$	1,367	$	3,957	$	5,324	8
Commercial, net	3,037		8,508		11,545		3
Residential, net	10,519		—		10,519		67
Consumer & other, net	109		—		109		5
Total, net of deferred fees and costs	$	15,032	$	12,465	$	27,497	83

	December 31, 2019
(in thousands)	Accrual Status		Non-Accrual Status		Total Modification		# of Contracts
Commercial real estate, net	$	3,968	$	—	$	3,968	3
Commercial, net	4,105		—		4,105		2
Residential, net	10,460		—		10,460		54
Consumer & other, net	43		—		43		3
Total, net of deferred fees and costs	$	18,576	$	—	$	18,576	62

The following table presents loans that were determined to be TDRs during the three and six months ended June 30, 2020 and 2019:


	Three Months Ended						Six Months Ended
(in thousands)	June 30, 2020		June 30, 2019		June 30, 2020		June 30, 2019
Commercial real estate, net	$	—	$	—	$	—	$	118
Commercial, net	8,508		—		8,508		1,842
Residential, net	756		7		6,434		7
Consumer & other, net	50		—		74		—
Total, net of deferred fees and costs	$	9,314	$	7	$	15,016	$	1,967

For the periods presented in the table above, the outstanding recorded investment was the same pre and post modification and all modifications were combination modifications. There were $8.6 million and $9.5 million in financing receivables modified as troubled debt restructurings within the previous 12 months for which there was a payment default during the three and six months ended June 30, 2020. There were no financing receivables modified as troubled debt restructurings within the previous 12 months for which there was a payment default during the three and six months ended June 30, 2019.

COVID-19 Related Payment Deferral and Forbearance

Due to the deterioration of the US economy resulting from the COVID-19 pandemic, the Company has had an increase in loan payment deferral and forbearance requests. Once a deferral or forbearance request is received, a late charge waiver is put in place and payments are suspended for up to six months. Accrued and unpaid interest during the deferral period will be collected upon the expiration of the deferral or on a regular repayment schedule at the end of the deferral period. For certain loan types, the maturity date may be extended one to six months to allow for full amortization. These loans are generally classified based on their past due status prior to their deferral period, so they are classified as performing loans that accrue interest.

Credit Quality Indicators

Management regularly reviews loans and leases in the portfolio to assess credit quality indicators and to determine appropriate loan classification and grading. In addition, the board reviews and approves the credit quality indicators each year. The Bank differentiates its lending portfolios into homogeneous and non-homogeneous loans and leases. Homogeneous loans and leases are risk rated on a single risk rating scale based on the past due status of the loan or lease.

The Bank's risk rating methodology for its non-homogeneous loans and leases uses a dual risk rating approach to assess the credit risk. This approach uses two scales to provide a comprehensive assessment of credit default risk and recovery risk. The probability of default scale measures a borrower's credit default risk using risk ratings ranging from 1 to 16, where a higher rating represents higher risk. For non-homogeneous loans and leases, PD rating of 1 through 9 are "pass" grades, PD grades 10-16 correspond to the regulatory-defined categories of watch (10-11), special mention (12), substandard (13-14), doubtful (15), and loss (16). The loss given default scale measures the amount of loss that may not be recovered in the event of a default, using six alphabetic ratings from A-F, where a higher rating represents higher risk. The LGD scale quantifies recovery risk associated with an event of default and predicts the amount of loss that would be incurred on a loan or lease if a borrower were to experience a major default and includes variables that may be external to the borrower, such as industry, geographic location, and credit cycle stage. It could also include variables specific to the borrower such as their probability of default and bankruptcies as well as variables specific to the loan or lease, including collateral valuation, covenant structure and debt type. The product of the borrower's PD and a loan or lease LGD is the loan or lease expected loss, expressed as a percentage. This provides a common language of credit risk across different loans.

The PD scale estimates the likelihood that a borrower will experience a major default on any of its debt obligations within a specified time period. Examples of major defaults include payments 90 days or more past due, non-accrual classification, bankruptcy filing, or a full or partial charge-off of a loan or lease. As such, the PD scale represents the credit quality indicator for non-homogeneous loans and leases.

The credit quality indicator rating categories follow regulatory classification and can be generally described by the following groupings for loans and leases:

Pass—A pass loan or lease is a loan or lease with a credit risk level acceptable to the Bank for extending credit and maintaining normal credit monitoring.

Watch—A watch loan or lease is considered pass rated but has a heightened level of unacceptable default risk due to an emerging risk element or declining performance trend. Watch ratings are expected to be temporary, with issues resolved or manifested to the extent that a higher or lower risk rating would be appropriate within a short period of time.

Special Mention—A special mention loan or lease has potential weaknesses that deserve management's close attention. If left uncorrected, these potential weaknesses may result in deterioration of the repayment prospects for the asset or in the institution's credit position at some future date. These borrowers have an elevated probability of default but not to the point of a substandard classification.

Substandard—A substandard asset is inadequately protected by the current net worth and paying capacity of the borrower or of the collateral pledged, if any. Assets classified as substandard must have a well-defined weakness or weaknesses that jeopardize the liquidation of the debt. They are characterized by the distinct possibility that the Bank will sustain some loss if the deficiencies are not corrected.

Doubtful—Loans or leases classified as doubtful have all the weaknesses inherent in those classified as substandard with the added characteristic that the weaknesses make collection or liquidation in full, based on currently existing facts, conditions, and values, highly questionable and improbable.

Loss—Loans or leases classified as loss are considered uncollectible and of such little value that their continuance as bankable assets is not warranted.

The following table represents the amortized costs basis of the loans and leases by credit classification and vintage year by loan and lease class of financing receivable as of June 30, 2020:


(in thousands)				Term Loans Amortized Cost Basis by Origination Year																																		Revolving Loans Amortized Cost Basis	Revolving to Non-Revolving Loans Amortized Cost
	June 30, 2020	2020				2019				2018				2017				2016				Prior												Total
Commercial real estate:
Non-owner occupied term, net
Credit quality indicator:
	Pass	$	313,883			$	725,232			$	578,859			$	387,750			$	411,471			$	1,116,727			$	3,091			$	4,191			$	3,541,204
	Special mention	1,155				6,777				—				8,638				6,359				5,664				—				—				28,593
	Substandard	867				6,337				—				—				—				12,013				—				—				19,217
	Doubtful	—				—				—				—				—				127				—				—				127
	Loss	—				—				—				—				—				343				—				—				343
Total non-owner occupied term, net				$	315,905			$	738,346			$	578,859			$	396,388			$	417,830			$	1,134,874			$	3,091			$	4,191			$	3,589,484
Owner occupied term, net
Credit quality indicator:
	Pass	$	201,511			$	430,033			$	321,456			$	357,099			$	278,233			$	746,367			$	5,495			$	806			$	2,341,000
	Special mention	5,577				12,551				43,576				10,457				3,454				8,326				—				—				83,941
	Substandard	2,657				3,019				1,737				3,017				5,189				18,882				—				—				34,501
	Doubtful	—				—				—				—				—				72				—				—				72
	Loss	—				—				—				—				—				440				—				—				440
Total owner occupied term, net				$	209,745			$	445,603			$	366,769			$	370,573			$	286,876			$	774,087			$	5,495			$	806			$	2,459,954
Multifamily, net
Credit quality indicator:
	Pass	$	198,388			$	868,496			$	642,383			$	664,016			$	321,813			$	708,085			$	27,853			$	2,967			$	3,434,001
	Special mention	—				—				—				—				—				32,229				—				—				32,229
	Substandard	—				—				—				—				—				599				—				—				599
	Doubtful	—				—				—				—				—				—				—				—				—
	Loss	—				—				—				—				—				—				—				—				—
Total multifamily, net				$	198,388			$	868,496			$	642,383			$	664,016			$	321,813			$	740,913			$	27,853			$	2,967			$	3,466,829
Construction & development, net
Credit quality indicator:
	Pass	$	26,389			$	202,023			$	262,912			$	162,129			$	6,928			$	687			$	—			$	—			$	661,068
	Special mention	—				—				1,635				—				—				—				—				—				1,635
	Substandard	—				—				—				—				—				—				—				—				—
	Doubtful	—				—				—				—				—				—				—				—				—
	Loss	—				—				—				—				—				—				—				—				—
Total construction & development, net				$	26,389			$	202,023			$	264,547			$	162,129			$	6,928			$	687			$	—			$	—			$	662,703


(in thousands)				Term Loans Amortized Cost Basis by Origination Year																																		Revolving Loans Amortized Cost Basis	Revolving to Non-Revolving Loans Amortized Cost
	June 30, 2020	2020				2019				2018				2017				2016				Prior												Total
Residential development, net
Credit quality indicator:
	Pass	$	8,060			$	15,012			$	2,762			$	—			$	—			$	—			$	135,994			$	2,352			$	164,180
	Special mention	—				—				—				—				—				—				—				—				—
	Substandard	—				—				—				—				—				—				—				—				—
	Doubtful	—				—				—				—				—				—				—				—				—
	Loss	—				—				—				—				—				—				—				—				—
Total residential development, net				$	8,060			$	15,012			$	2,762			$	—			$	—			$	—			$	135,994			$	2,352			$	164,180

Total commercial real estate				$	758,487			$	2,269,480			$	1,855,320			$	1,593,106			$	1,033,447			$	2,650,561			$	172,433			$	10,316			$	10,343,150


Commercial:
Term, net
Credit quality indicator:
	Pass	$	2,114,332			$	425,727			$	365,014			$	274,397			$	82,331			$	251,285			$	697,208			$	15,161			$	4,225,455
	Special mention	75				426				2,302				1,134				6,278				3,820				—				—				14,035
	Substandard	—				579				1,222				5,581				1,603				2,437				900				13,050				25,372
	Doubtful	—				—				—				—				—				—				—				—				—
	Loss	—				—				—				—				—				230				—				—				230
Total term, net				$	2,114,407			$	426,732			$	368,538			$	281,112			$	90,212			$	257,772			$	698,108			$	28,211			$	4,265,092
Lines of credit & other, net
Credit quality indicator:
	Pass	$	12,288			$	26,424			$	28,065			$	1,132			$	3,332			$	867			$	781,992			$	5,763			$	859,863
	Special mention	2,530				1,027				—				56				77				349				37,443				2,000				43,482
	Substandard	1,420				625				—				350				484				1,714				27,304				5,200				37,097
	Doubtful	—				—				—				—				—				—				1				—				1
	Loss	—				—				—				—				—				—				—				—				—
Total lines of credit & other, net				$	16,238			$	28,076			$	28,065			$	1,538			$	3,893			$	2,930			$	846,740			$	12,963			$	940,443
Leases & equipment finance, net
Credit quality indicator:
	Pass	$	316,861			$	550,265			$	318,126			$	176,227			$	93,106			$	22,424			$	—			$	—			$	1,477,009
	Special mention	740				3,749				5,743				4,661				573				6,698				—				—				22,164
	Substandard	281				2,212				8,119				2,609				1,235				94				—				—				14,550
	Doubtful	431				3,235				2,196				1,094				372				151				—				—				7,479
	Loss	—				238				367				278				257				27				—				—				1,167
Total leases & equipment finance, net				$	318,313			$	559,699			$	334,551			$	184,869			$	95,543			$	29,394			$	—			$	—			$	1,522,369

Total commercial				$	2,448,958			$	1,014,507			$	731,154			$	467,519			$	189,648			$	290,096			$	1,544,848			$	41,174			$	6,727,904

Residential:
Mortgage, net
Credit quality indicator:
	Pass	$	353,958			$	1,335,457			$	501,636			$	494,052			$	529,473			$	799,467			$	—			$	—			$	4,014,043
	Special mention	—				—				996				663				300				3,443				—				—				5,402
	Substandard	—				1,523				2,110				6,318				8,311				12,215				—				—				30,477
	Doubtful	—				—				—				—				—				—				—				—				—
	Loss	—				917				—				832				—				4,917				—				—				6,666
Total mortgage, net				$	353,958			$	1,337,897			$	504,742			$	501,865			$	538,084			$	820,042			$	—			$	—			$	4,056,588


(in thousands)				Term Loans Amortized Cost Basis by Origination Year																																		Revolving Loans Amortized Cost Basis	Revolving to Non-Revolving Loans Amortized Cost
	June 30, 2020	2020				2019				2018				2017				2016				Prior												Total
Home equity loans & lines, net
Credit quality indicator:
	Pass	$	78			$	—			$	21			$	—			$	381			$	19,865			$	1,123,712			$	41,842			$	1,185,899
	Special mention	—				—				—				—				—				114				1,700				240				2,054
	Substandard	—				—				22				—				—				43				467				269				801
	Doubtful	—				—				—				—				—				—				—				—				—
	Loss	—				—				—				—				—				132				402				140				674
Total home equity loans & lines, net				$	78			$	—			$	43			$	—			$	381			$	20,154			$	1,126,281			$	42,491			$	1,189,428

Total residential				$	354,036			$	1,337,897			$	504,785			$	501,865			$	538,465			$	840,196			$	1,126,281			$	42,491			$	5,246,016

Consumer & other, net:
Credit quality indicator:
	Pass	$	20,733			$	31,017			$	15,392			$	68,696			$	32,706			$	19,689			$	162,433			$	1,718			$	352,384
	Special mention	—				26				9				393				359				216				538				99				1,640
	Substandard	—				44				—				62				—				29				150				71				356
	Doubtful	—				—				—				—				—				—				—				—				—
	Loss	—				—				—				—				—				4				1				—				5
Total consumer & other, net				$	20,733			$	31,087			$	15,401			$	69,151			$	33,065			$	19,938			$	163,122			$	1,888			$	354,385

Grand total				$	3,582,214			$	4,652,971			$	3,106,660			$	2,631,641			$	1,794,625			$	3,800,791			$	3,006,684			$	95,869			$	22,671,455