Allowance for Credit Losses | Allowance for Credit Losses The Company accounts for credit losses on loans in accordance with ASC 326 - Financial Instruments - Credit Losses , to determine the ACL. ASC 326 requires the Company to recognize estimates for lifetime losses on loans and unfunded loan commitments at the time of origination or acquisition. The recognition of losses at origination or acquisition represents the Company’s best estimate of the lifetime expected credit loss associated with a loan given the facts and circumstances associated with the particular loan, and involves the use of significant management judgement and estimates, which are subject to change based on management’s on-going assessment of the credit quality of the loan portfolio and changes in economic forecasts used in the model. The Company uses a discounted cash flow model when determining estimates for the ACL for commercial real estate loans and commercial loans, which comprise the majority of the loan portfolio, and uses a historical loss rate model for retail loans. The Company also utilizes proxy loan data in its ACL model where the Company’s own historical data is not available. The discounted cash flow model is applied on an instrument-by-instrument basis, and for loans with similar risk characteristics, to derive estimates for the lifetime ACL for each loan. The discounted cash flow methodology relies on several significant components essential to the development of estimates for future cash flows on loans and unfunded commitments. These components consist of: (i) the estimated probability of default, (ii) the estimated loss given default, which represents the estimated severity of the loss when a loan is in default, (iii) estimates for prepayment activity on loans and (iv) the estimated exposure to the Company at default (“EAD”). These components are also heavily influenced by changes economic forecasts employed in the model over a reasonable and supportable period. The Company’s ACL methodology for unfunded loan commitments also includes assumptions concerning the probability an unfunded commitment will be drawn upon by the borrower. These assumptions are based on the Company’s historical experience. The Company’s discounted cash flow ACL model for commercial real estate and commercial loans uses internally derived estimates for prepayments in determining the amount and timing of future contractual cash flows to be collected. The estimate of future cash flows also incorporates estimates for contractual amounts the Company believes may not be collected, which are based on assumptions for PD, LGD and EAD. EAD is the estimated outstanding balance of the loan at the time of default. It is determined by the contractual payment schedule and expected payment profile of the loan, incorporating estimates for expected prepayments and future draws on revolving credit facilities. The Company discounts cash flows using the effective interest rate on the loan. The effective interest rate represents the contractual rate on the loan; adjusted for any purchase premiums, purchase discounts, and deferred fees and costs associated with the origination of the loan. The Company has made an accounting policy election to adjust the effective interest rate to take into consideration the effects of estimated prepayments. The ACL for loans is determined by measuring the amount by which a loan’s amortized cost exceeds its discounted cash flows. Probability of Default The PD for commercial real estate loans is based largely on a model provided by a third party, using proxy loan information. The PDs generated by this model are reflective of current and expected changes in economic conditions and conditions in the commercial real estate market, and how they are expected to impact loan level and property level attributes, and ultimately the likelihood of a default event occurring. Significant loan and property level attributes include: loan to value ratios, debt service coverage, loan size, loan vintage and property types. The PD for commercial loans is based on an internally developed PD rating scale that assigns PDs based on the Company’s internal risk grades for loans. This internally developed PD rating scale is based on a combination of the Company’s own historical data and observed historical data from the Company’s peers, which consist of banks that management believes align with our business profile. As credit risk grades change for loans in the commercial segment, the PD assigned to them also changes. As with commercial real estate loans, the PD for commercial loans is also impacted by current and expected economic conditions. The Company considers loans to be in default when they are 90 days or more past due and still accruing or placed on nonaccrual status. Loss Given Default LGDs for commercial real estate loans are derived from a third party, using proxy loan information, and are based on loan and property level characteristics in the Company’s loan portfolio, such as: loan to values, estimated time to resolution, property size and current and estimated future market price changes for underlying collateral. The LGD is highly dependent upon loan to value ratios, and incorporates estimates for the expense associated with managing the loan through to resolution. LGDs also incorporate an estimate for the loss severity associated with loans where the borrower fails to meet their debt obligation at maturity, such as through a balloon payment or the refinancing of the loan through another lender. External factors that have an impact on LGDs include: changes in the CRE Price Index, GDP growth rate, unemployment rates and the Moody’s Baa rating corporate debt interest rate spread. LGDs are applied to each loan in the commercial real estate portfolio, and in conjunction with the PD, produce estimates for net cash flows not expected to be collected over the estimated term of the loan. LGDs for commercial loans are also derived from a third party that has a considerable database of credit related information specific to the financial services industry and the type of loans within this segment, and is used to generate annual default information for commercial loans. These proxy LGDs are dependent upon data inputs such as: credit quality, borrower industry, region, borrower size and debt seniority. LGDs are then applied to each loan in the commercial portfolio, and in conjunction with the PD, produce estimates for net cash flows not expected to be collected over the estimated term of the loan. Historical Loss Rates for Retail Loans The historical loss rate model for retail loans are derived from a third party that has a considerable database of credit related information for retail loans. Key loan level attributes and economic drivers in determining the loss rate for retail loans include FICO scores, vintage, as well as geography, unemployment rates and changes in consumer real estate prices. Forecasts U.S. GAAP requires the Company to develop reasonable and supportable forecasts of future conditions, and estimate how those forecasts are expected to impact a borrower’s ability to satisfy their obligation to the Bank and the ultimate collectability of future cash flows over the life of the loan. The Company uses economic scenarios from Moody’s Analytics in its estimation of a borrower’s ability to repay a loan in future periods. These scenarios are based on past events, current conditions and the likelihood of future events occurring. These scenarios typically are comprised of: (1) a base-case scenario, (2) an upside scenario, representing slightly better economic conditions than currently experienced and (3) a downside scenario, representing recessionary conditions. Management periodically evaluates economic scenarios and may decide that a particular economic scenario or a combination of probability-weighted economic scenarios should be used in the Company’s ACL model. The economic scenarios chosen for the model, the extent to which more than one scenario is used, and the weights that are assigned to them, are based on the Company’s estimate of the probability of each scenario occurring, which is based in part on analysis performed by an independent third-party. Economic scenarios chosen, as well as the assumptions within those scenarios, and whether to use a probability-weighted multiple scenario approach, can vary from one period to the next based on changes in current and expected economic conditions and due to the occurrence of specific events such as the COVID-19 pandemic. The Company recognizes the non-linearity of credit losses relative to economic performance and thus the Company believes consideration of and, if appropriate under the circumstances, use of multiple probability-weighted economic scenarios is appropriate in estimating credit losses over the forecast period. This approach is based on certain assumptions. The first assumption is that no single forecast of the economy, however detailed or complex, is completely accurate over a reasonable forecast time-frame, and is subject to revisions over time. By considering multiple scenario outcomes and assigning reasonable probability weightings to them, some of the uncertainty associated with a single scenario approach, the Company believes, is mitigated. As of January 1, 2020, upon the adoption of ASC 326, the Company’s ACL model used three probability-weighted scenarios representing a base-case scenario, an upside scenario and a downside scenario. The weightings assigned to each scenario were as follows: the base-case scenario, or most likely scenario, was assigned a weighting of 40%, while the upside and downside scenarios were each assigned weightings of 30%. As of June 30, 2020, the Company’s ACL model used the same three probability weighted scenarios, updated for current expected economic conditions, including the current and estimated future impact associated with the on-going COVID-19 pandemic. The Company evaluated the weightings of each economic scenario in the current period with the assistance of an independent third party, and determined the current weightings of 40% for the base-case scenario, and 30% for each of the upside and downside scenarios appropriately reflect the likelihood of outcomes for each scenario given the current economic environment. For the three months ended March 31, 2020, the Company’s ACL model used three probability-weighted scenarios, however the composition and weightings of those scenarios differed from those used in the model as of June 30, 2020 due to the rapid emergence of the of the COVID-19 pandemic in the first quarter of 2020. These scenarios included (i) a base-case scenario with a weighting of 37.5%, (ii) a critical pandemic scenario with a weighting of 30%, and (iii) a more severe down-side scenario with a weighting of 32.5%. The composition of these scenarios and their assigned weightings were determined with the assistance of an independent third party, and were reflective of the rapidly changing economic conditions, economic uncertainty and volatility in financial markets brought on by the COVID-19 pandemic and the estimated likelihood of each scenario occurring as of March 31, 2020. The Company currently forecasts economic conditions over a two-year period, which we believe is a reasonable and supportable period. Beyond the point which the Company can provide for a reasonable and supportable forecast, economic variables revert to their long-term averages. The Company has reflected this reversion over a period of three years in each of its economic scenarios used to generate the overall probability-weighted forecast. Changes in economic forecasts impact the PD, LGD and EAD for each loan, and therefore influence the amount of future cash flows for each loan the Company does not expect to collect. The Company derives the economic forecasts it uses in its ACL model from an independent third party that has a large team of economists, data-base managers and operational engineers with a history of producing monthly economic forecasts for over 25 years. The forecasts produced by this third party have been widely used by banks, credit unions, government agencies and real estate developers. These economic forecasts cover all states and metropolitan areas in the Unites States, and reflect changes in economic variables such as: GDP growth, interest rates, employment rates, changes in wages, retail sales, industrial production, metrics associated with the single-family and multifamily housing markets, vacancy rates, changes in equity market prices and energy markets. It is important to note that the Company’s ACL model relies on multiple economic variables, which are used under several economic scenarios. Although no one economic variable can fully demonstrate the sensitivity of the ACL calculation to changes in the economic variables used in the model, the Company has identified certain economic variables that have significant influence in the Company’s model for determining the ACL. As of June 30, 2020, the Company’s ACL model incorporated the following assumptions for key economic variables in the base-case and downside scenarios: Base-case Scenario: • CRE Price Index decreases by an approximate annualized rate of 16% through the remainder of 2020 with the rate of decline slowing in Q1 2021 to 8%, before returning to growth in the second quarter of 2021. • A significant decrease in real GDP of an approximate 33% annualized rate in Q2 2020, followed by an approximate 20% increase in Q3 2020 before returning to levels of marginal growth through the second quarter of 2021. • Elevated levels of U.S. unemployment reaching approximately 14% in Q2 2020 and then declining to levels of 9% to 10% through the end of 2021. Upside Scenario: • CRE Price Index decreases by an approximate annualized rate of 15% and 6% during the third and fourth quarters of 2020, respectively, before returning to growth by the first quarter of 2021. • An approximate annualized decrease in real GDP of 27% in Q2 2020, followed by a 20% increase in real GDP in the third quarter of 2020, and growth of approximately 4% growth through the end of the second quarter of 2021. • Elevated levels of U.S. unemployment at approximately 13% for Q2 2020, followed by unemployment of approximately 9% through the remainder of 2020, and decreasing gradually to approximately 7% by the end of 2021. Downside Scenario: • CRE Price Index decreases by an approximate annualized rate of 25% and 26% in the third and fourth quarters of 2020, respectively, with the rate of decline decreasing to 21% and 4% in the first and second quarters of 2021, respectively, before returning to growth in the third quarter of 2021. • A decrease in real GDP of an approximate annualized rate of 36% in the second quarter of 2020, followed by an increase in GDP of approximately 13% in the third quarter of 2020, and then declining by approximately 4% in the fourth quarter of 2020, 3% in the first quarter of 2021, 1% growth in the second quarter of 2021 and growth of 5% to 6% in the remaining two quarters of 2021. • Elevated levels of U.S. unemployment at approximately 15% for Q2 2020, followed by unemployment of approximately 11% and 12% in Q3 and Q4 2020. Unemployment is projected to remain elevated at approximately 12% through the end of 2021. Qualitative Adjustments The Company recognizes that historical information used as the basis for determining future expected credit losses may not always, by themselves, provide a sufficient basis for determining future expected credit losses. The Company, therefore, periodically considers the need for qualitative adjustments to the ACL. Qualitative adjustments may be related to and include, but not be limited to, factors such as: (i) management’s assessment of economic forecasts used in the model and how those forecasts align with management’s overall evaluation of current and expected economic conditions, (ii) organization specific risks such as credit concentrations, collateral specific risks, regulatory risks and external factors that may ultimately impact credit quality, (iii) potential model limitations such as limitations identified through back-testing, and other limitations associated with factors such as underwriting changes, acquisition of new portfolios and changes in portfolio segmentation and (iv) management’s overall assessment of the adequacy of the ACL, including an assessment of model data inputs used to determine the ACL. As of June 30, 2020, qualitative adjustments included in the ACL totaled $15.0 million. These adjustments relate to potential limitations in the model. Management determined through additional review that certain key model drivers are potentially underestimating the impact of the on-going COVID-19 pandemic may have on small and medium sized businesses, and may not be fully reflecting the potential for a more turbulent economic recovery. Management reviews the need for and appropriate level of qualitative adjustments on a quarterly basis, and as such, the amount and allocation of qualitative adjustments may change in future periods. The following table provides the allocation of the ACL for loans held for investment as well as the activity in the ACL attributed to various segments in the loan portfolio as of and for the period indicated: Three Months Ended June 30, 2020 Beginning ACL Balance (1) Initial ACL Recorded for PCD Loans Charge-offs Recoveries Provision for Credit Losses Ending (Dollars in thousands) Investor loans secured by real estate CRE non-owner occupied $ 15,896 $ 3,025 $ — $ — $ 44,086 $ 63,007 Multifamily 14,722 8,710 — — 40,079 63,511 Construction and land 9,222 2,051 — — 7,531 18,804 SBA secured by real estate 935 — (554) — 1,629 2,010 Business loans secured by real estate CRE owner-occupied 26,793 3,766 — 11 17,643 48,213 Franchise real estate secured 7,503 — — — 5,557 13,060 SBA secured by real estate 4,044 235 — 3 86 4,368 Commercial loans Commercial and industrial 15,742 2,325 (2,286) 21 26,165 41,967 Franchise non-real estate secured 16,616 — (1,227) — 6,287 21,676 SBA non-real estate secured 516 924 (556) (2) (282) 600 Retail loans Single family residential 1,137 — (62) 1 403 1,479 Consumer loans 2,296 206 — 1 1,073 3,576 Totals $ 115,422 $ 21,242 $ (4,685) $ 35 $ 150,257 $ 282,271 Six Months Ended June 30, 2020 Beginning ACL Balance (1) Adoption of ASC 326 Initial ACL Recorded for PCD Loans Charge-offs Recoveries Provision for Credit Losses Ending (Dollars in thousands) Investor loans secured by real estate CRE non-owner occupied $ 1,899 $ 8,423 $ 3,025 $ (387) $ — $ 50,047 $ 63,007 Multifamily 729 9,174 8,710 — — 44,898 63,511 Construction and land 4,484 (124) 2,051 — — 12,393 18,804 SBA secured by real estate 1,915 (1,401) — (554) — 2,050 2,010 Business loans secured by real estate CRE owner-occupied 2,781 20,166 3,766 — 23 21,477 48,213 Franchise real estate secured 592 5,199 — — — 7,269 13,060 SBA secured by real estate 2,119 2,207 235 (315) 74 48 4,368 Commercial loans Commercial and industrial 13,857 87 2,325 (2,776) 26 28,448 41,967 Franchise non-real estate secured 5,816 9,214 — (1,227) — 7,873 21,676 SBA non-real estate secured 445 218 924 (792) 2 (197) 600 Retail loans Single family residential 655 541 206 (62) 1 138 1,479 Consumer loans 406 1,982 — (8) 1 1,195 3,576 Totals $ 35,698 $ 55,686 $ 21,242 $ (6,121) $ 127 $ 175,639 $ 282,271 ______________________________ (1) Beginning ACL balance represents the ALLL accounted for under ASC 450 and ASC 310, which is reflective of probable incurred losses as of the balance sheet date. The following table provides the allocation of the ALLL for loans held for investment as well as the activity attributed to various segments in the loan portfolio as of and for the period indicated, as determined in accordance with ASC 450 and ASC 310, prior to the adoption of ASC 326: For the Three Months Ended June 30, 2019 Beginning ALLL Balance Charge-offs Recoveries Provision for Credit Losses Ending (Dollars in thousands) Investor loans secured by real estate CRE non-owner-occupied $ 1,668 $ (488) $ — $ 585 $ 1,765 Multifamily 669 — — 36 705 Construction and land 5,960 — — (552) 5,408 SBA secured by real estate 2,704 (721) — (661) 1,322 Business loans secured by real estate CRE owner-occupied 1,969 — 15 315 2,299 Franchise real estate secured 2,173 (1,376) — (218) 579 SBA secured by real estate 1,966 (254) — (101) 1,611 Commercial loans Commercial and industrial 13,587 (393) 47 555 13,796 Franchise non-real estate secured 5,698 (160) — 648 6,186 SBA non-real estate secured 503 (244) 1 170 430 Retail loans Single family residential 758 — 1 (55) 704 Consumer loans 201 — — 20 221 Totals $ 37,856 $ (3,636) $ 64 $ 742 $ 35,026 For the Six Months Ended June 30, 2019 Beginning ALLL Balance Charge-offs Recoveries Provision for Credit Losses Ending (Dollars in thousands) Investor loans secured by real estate CRE non-owner-occupied $ 1,624 $ (488) $ — $ 629 $ 1,765 Multifamily 740 — — (35) 705 Construction and land 5,964 — — (556) 5,408 SBA secured by real estate 1,827 (721) — 216 1,322 Business loans secured by real estate CRE owner-occupied 1,908 — 23 368 2,299 Franchise real estate secured 743 (1,376) — 1,212 579 SBA secured by real estate 1,824 (254) — 41 1,611 Commercial loans Commercial and industrial 13,695 (695) 114 682 13,796 Franchise non-real estate secured 6,066 (160) — 280 6,186 SBA non-real estate secured 654 (244) 4 16 430 Retail loans Single family residential 808 — 1 (105) 704 Consumer loans 219 (5) 1 6 221 Totals $ 36,072 $ (3,943) $ 143 $ 2,754 $ 35,026 The change in the ACL during the three months ended June 30, 2020 of $166.8 million is reflective of a $150.3 million in provision for credit losses, $4.7 million in net charge-offs, and the establishment of $21.2 million in net ACL for PCD loans acquired in the Opus acquisition. The change in the ACL for the six months ended June 30, 2020 of $246.6 million is reflective of a $55.7 million adjustment associated with the Company’s adoption of ASC 326 on January 1, 2020, which was recorded through a cumulative effect adjustment to retained earnings, as well as a $175.6 million provision for credit losses on loans, net charge-offs of $6.0 million, and the establishment of $21.2 million in net ACL for PCD loans previously mentioned. The provision for credit losses during the three and six months ended June 30, 2020 includes approximately $75.9 million related to the initial ACL required for the acquisition of non-PCD loans in the Opus acquisition. Under ASC 326, the Company is required to record an ACL for estimates of life-time credit losses on loans at the time of acquisition. For non-PCD loans, the initial ACL is established through a charge to provision for credit losses at the time of acquisition. However, the ACL for PCD loans is established through an adjustment to the loan’s purchase price (or initial fair value). In addition, the provision for credit losses for the three and six months ended June 30, 2020 is also reflective of unfavorable changes in economic forecasts used in the Company’s ACL model driven by the COVID-19 pandemic. Allowance for Credit Losses for Off-Balance Sheet Commitments The Company maintains an allowance for credit losses on off-balance sheet commitments related to unfunded loans and lines of credit, which is included in other liabilities of the consolidated balance sheets. The allowance for off-balance sheet commitments was $22.0 million at June 30, 2020 and $3.3 million at December 31, 2019. The change in the allowance for off-balance sheet commitments can be attributed to several factors, including: (i) an $8.3 million increase in the first quarter of 2020 attributed to the Company’s adoption of ASC 326, (ii) a $8.6 million provision for credit losses in the second quarter of 2020 related to the assumption of off-balance sheet loan commitments in the acquisition of Opus and the initial ACL the Company was required to establish at the time of acquisition, and (iii) a $1.9 million in provision for credit losses for the first six months of 2020 related primarily to the deterioration in economic forecasts, primarily in the second quarter of 2020, used in the Company’s CECL model. The total provision for credit losses for off-balance sheet commitments totaled $10.4 million and $10.5 million for the three and six months ended June 30, 2020, respectively. The Company applies an expected credit loss estimation methodology for off-balance sheet commitments that is commensurate with the methodology applied to each respective segment of the loan portfolio in determining the ACL for loans held-for-investment. The loss estimation process includes assumptions for the probability that a loan will fund, as well as the expected amount of funding. These assumptions are based on the Company’s own historical internal loan data. The following table presents loans individually and collectively evaluated for impairment and their respective ALLL allocation at December 31, 2019 as determined in accordance with ASC 450 and ASC 310, prior to the adoption of ASC 326: December 31, 2019 Loans Evaluated Individually for Impairment ALLL Attributed to Individually Evaluated Loans Loans Evaluated Collectively for Impairment ALLL Attributed to Collectively Evaluated Loans (Dollars in thousands) Investor loans secured by real estate CRE non-owner-occupied $ 1,088 $ — $ 2,069,053 $ 1,899 Multifamily — — 1,575,726 729 Construction and land — — 438,786 4,484 SBA secured by real estate 390 — 68,041 1,915 Business loans secured by real estate CRE owner-occupied — — 1,846,554 2,781 Franchise real estate secured — — 353,240 592 SBA secured by real estate 1,517 — 86,864 2,119 Commercial loans Commercial and industrial 7,529 — 1,385,741 13,857 Franchise non-real estate secured 10,834 — 553,523 5,816 SBA non-real estate secured 1,118 — 16,308 445 Retail loans Single family residential 366 — 254,658 655 Consumer loans — — 50,975 406 Totals $ 22,842 $ — $ 8,699,469 $ 35,698 The following table presents PD bands for commercial real estate and commercial loan segments of the loan portfolio as of the date indicated. It should be noted that SBA PPP loans, which are in the commercial loans segment, have been excluded from this table since they are not included in the Company’s ACL model. Commercial Real Estate Term Loans by Vintage 2020 2019 2018 2017 2016 Prior Revolving Revolving Converted to Term During the Period Total June 30, 2020 (Dollars in thousands) Investor loans secured by real estate CRE non-owner-occupied 0% - 5.00% $ 153,133 $ 561,104 $ 474,139 $ 258,886 $ 279,780 $ 793,398 $ 10,924 $ — $ 2,531,364 >5.00% - 10.00% — 2,897 8,428 86,660 37,621 39,947 — — 175,553 Greater than 10% 2,296 3,988 322 14,155 2,585 52,870 559 — 76,775 Multifamily 0% - 5.00% 520,782 1,723,731 991,561 746,855 460,328 678,741 1,031 — 5,123,029 >5.00% - 10.00% 1,599 17,431 8,692 2,176 4,098 8,906 — — 42,902 Greater than 10% — 12,607 9,794 12,545 10,409 14,271 — — 59,626 Construction and Land 0% - 5.00% 13,838 32,921 4,296 20,357 — 6,919 66 — 78,397 >5.00% - 10.00% — 40,785 21,154 3,275 — — 395 — 65,609 Greater than 10% — 67,142 129,990 14,739 — 1,549 — — 213,420 SBA secured by real estate 0% - 5.00% 495 10,704 12,115 16,181 7,135 11,352 — — 57,982 >5.00% - 10.00% — — 512 — — — — — 512 Greater than 10% — — 594 — 394 — — — 988 Total investor loans secured by real estate $ 692,143 $ 2,473,310 $ 1,661,597 $ 1,175,829 $ 802,350 $ 1,607,953 $ 12,975 $ — $ 8,426,157 Business loans secured by real estate CRE owner-occupied 0% - 5.00% $ 211,860 $ 402,474 $ 309,907 $ 304,611 $ 234,139 $ 488,345 $ 3,124 $ — $ 1,954,460 >5.00% - 10.00% 186 33,118 35,922 22,510 26,918 42,552 1,504 — 162,710 Greater than 10% 5,979 16,066 7,086 3,386 6,797 13,173 497 — 52,984 Franchise real estate secured 0% - 5.00% 18,724 86,263 74,832 95,221 28,550 42,831 — — 346,421 >5.00% - 10.00% 754 — 632 8,627 3,028 101 — — 13,142 Greater than 10% 928 2,545 728 — — 883 — — 5,084 SBA secured by real estate 0% - 5.00% 1,905 7,693 13,476 16,611 8,547 24,605 365 — 73,202 >5.00% - 10.00% — — 683 1,699 2,306 3,416 — — 8,104 Greater than 10% — — — 914 148 3,174 — — 4,236 Total business loans secured by real estate $ 240,336 $ 548,159 $ 443,266 $ 453,579 $ 310,433 $ 619,080 $ 5,490 $ — $ 2,620,343 Commercial Real Estate Term Loans by Vintage 2020 2019 2018 2017 2016 Prior Revolving Revolving Converted to Term During the Period Total June 30, 2020 (Dollars in thousands) Commercial Loans Commercial and industrial 0% - 5.00% $ 91,538 $ 376,850 $ 268,429 $ 211,610 $ 58,496 $ 94,984 $ 508,985 $ 1,593 $ 1,612,485 >5.00% - 10.00% 9,735 11,741 24,030 11,639 14,449 8,862 271,951 547 352,954 Greater than 10% 5,496 339 3,625 1,007 7,121 9,415 57,848 1,023 85,874 Franchise non-real estate secured 0% - 5.00% 9,535 197,360 117,509 69,287 46,925 40,305 1,476 — 482,397 >5.00% - 10.00% 812 6,619 3,593 9,290 2,382 4,704 729 — 28,129 Greater than 10% — 2,443 514 7,737 — 2,535 — — 13,229 SBA not secured by real estate 0% - 5.00% 646 2,341 1,301 2,517 571 3,842 — 3,537 14,755 >5.00% - 10.00% — — 132 1,745 367 439 — — 2,683 Greater than 10% — 86 394 856 — 1,519 764 — 3,619 Total commercial loans $ 117,762 $ 597,779 $ 419,527 $ 315,688 $ 130,311 $ 166,605 $ 841,753 $ 6,700 $ 2,596,125 A significant driver in the ACL for loans in the investor real estate secured and business real estate secured segments is loan to value (“LTV”). The following table summarizes the amortized cost of loans in these segments by current estimated LTV and by year of origination as of the date indicated: Term Loans by Vintage 2020 2019 2018 2017 2016 Prior Revolving Revolving Converted to Term During the Period Total June 30, 2020 (Dollars in thousands) Investor loans secured by real estate CRE non-owner-occupied 55% and below $ 73,769 $ 241,867 $ 191,322 $ 156,622 $ 189,946 $ 618,498 $ 10,924 — $ 1,482,948 >55-65% 54,874 214,909 119,539 177,366 104,448 231,545 559 — 903,240 >65-75% 22,526 108,464 169,089 23,368 25,379 31,566 — — 380,392 Greater than 75% 4,260 2,749 2,939 2,345 213 4,606 — — 17,112 Multifamily 55% and below 123,726 387,468 341,633 223,446 95,645 290,333 599 — 1,462,850 >55-65% 164,019 734,321 386,341 266,322 167,271 283,527 432 — 2,002,233 >65-75% 234,636 609,946 270,888 269,910 211,919 122,199 — — 1,719,498 Greater than 75% — 22,034 11,185 1,898 — 5,859 — — 40,976 Construction and land 55% and below 13,838 136,216 107,812 30,148 — 8,468 461 — 296,943 >55-65% — 4,632 42,778 8,223 — — — — 55,633 >65-75% — — 3,697 — — — — — 3,697 Greater than 75% — — 1,153 — — — — — 1,153 SBA secured by real estate 55% and below — 1,148 655 841 332 436 — — 3,412 >55-65% — 3,187 1,647 3,860 623 4,791 — — 14,108 >65-75% 495 3,724 7,802 5,364 4,358 2,829 — — 24,572 Greater than 75% — 2,645 3,117 6,116 2,216 3,296 — — 17,390 Total investor loans secured by real estate $ 692,143 $ 2,473,310 $ 1,661,597 $ 1,175,829 $ 802,350 $ 1,607,953 $ 12,975 $ — $ 8,426,157 Business loan secured by real estate CRE owner-occupied 55% and below $ 55,579 $ 153,995 $ 171,876 $ 196,583 $ 150,233 $ 377,115 $ 5,125 — $ 1,110,506 >55-65% 63,067 100,226 89,960 64,803 73,724 81,403 — — 473,183 >65-75% 56,327 175,639 63,734 54,957 39,714 58,581 — — 448,952 Greater than 75% 43,052 21,798 27,345 14,164 4,183 26,971 — — 137,513 Franchise real estate secured 55% and below 7,461 18,360 14,615 16,057 11,567 20,926 — — 88,986 >55-65% 928 8,900 13,096 29,110 7,823 5,919 — — 65,776 >65-75% 2,911 49,851 25,927 9,859 11,062 14,848 — — 114,458 Greater than 75% 9,106 11,697 22,554 48,822 1,126 2,122 — — 95,427 SBA secured by real estate 55% and below 736 1,735 6,537 4,784 2,348 10,568 365 — 27,073 >55-65% 104 514 2,337 2,643 2,252 4,121 — — 11,971 >65-75% 264 2,687 754 4,602 3,167 5,871 — — 17,345 Greater than 75% 801 2,757 4,531 7,195 3,234 10,635 — — 29,153 Total business loans secured by real estate $ 240,336 $ 548,159 $ 443,266 $ 453,579 $ 310,433 $ 619,080 $ 5,490 $ — $ 2,620,343 The following table presents FICO bands for the retail segment of the loan portfolio as of the date indicated: Term Loans by Vintage 2020 2019 2018 2017 2016 Prior Revolving Revolving Converted to Term During the Period Total June 30, 2020 (Dollars in thousands) Retail Loans Single family residential Greater than 740 $ 4,863 $ 8,236 $ 13,274 $ 9,719 $ 31,203 $ 96,475 $ 27,050 — $ 190,820 >680 - 740 — 1,190 2,268 4,794 2,660 18,190 9,095 — 38,197 >580 - 680 — — — 466 3,178 9,030 959 — 13,633 Less than 580 — — 11 12 1,333 21,128 36 — 22,520 Consumer loans Greater than 740 72 95 863 51 20 2,661 1,993 — 5,755 >680 - 740 — 59 7 37,988 — 488 1,737 — 40,279 >580 - 680 — 20 — — 3 150 51 — |