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Allowance for Credit Losses
 3 Months Ended
Mar. 31, 2022
Provision for Loan and Lease Losses [Abstract]  
Allowance for Credit Losses Allowance for Credit Losses
 
The Company maintains an ACL for loans and unfunded loan commitments in accordance with ASC 326 - Financial Instruments - Credit Losses. ASC 326 requires the Company to recognize estimates for lifetime credit losses on loans and unfunded loan commitments at the time of origination or acquisition. The recognition of credit losses at origination or acquisition represents the Company’s best estimate of lifetime expected credit losses, given the facts and circumstances associated with a particular loan or group of loans with similar risk characteristics. Determining the ACL involves the use of significant management judgement and estimates, which are subject to change based on management’s ongoing 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 sufficiently 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 PD, (ii) the estimated LGD, 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 in 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 expected 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 an originated 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 expected to be collected. The ACL for credit facilities is determined by discounting estimates for cash flows not expected to be collected.

Probability of Default

The PD for investor loans secured by real estate 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 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. This model also incorporates assumptions for PD at a loan’s maturity. Significant loan and property level attributes include: loan-to-value (“LTV”) ratios, debt service coverage, loan size, loan vintage, and property types.
The PD for business loans secured by real estate and 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 these loans, the PD assigned to them also changes. As with investor loans secured by real estate, the PD for business loans secured by real estate and 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 for loans in the Company’s loan portfolio, such as: LTVs, estimated time to resolution, property size, and current and estimated future market price changes for underlying collateral. The LGD is highly dependent upon LTV 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 index for CRE pricing, GDP growth rate, unemployment rates, and the Consumer Price Index. 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 segment, 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 is 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.
Economic Forecasts

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 a loan. The Company uses economic scenarios from an independent third party. 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 appropriateness of 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 likelihood that the economy would perform better than each scenario, 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 ongoing COVID-19 pandemic, the war between Russia and Ukraine, and ongoing inflationary pressures throughout the U.S. economy. 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 March 31, 2022, the Company’s ACL model used three 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 a weighting of 30%. The Company evaluated the weightings of each economic scenario in the current period 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. The use of three weighted scenarios at March 31, 2022 and the weighting assigned to each scenario is consistent with the approach used in the Company’s ACL model at December 31, 2021.

Given recent developments in the geopolitical landscape with the war between Russia and Ukraine, ongoing inflationary pressures in the U.S. economy, and general uncertainty surrounding future economic conditions, the Company took into consideration these and other factors when determining the appropriateness of economic scenarios used in the ACL model at March 31, 2022. As a result, the Company used the economic forecast as of December 31, 2021 in the ACL model, which was more reflective of the current economic environment as well as the likelihood of future economic conditions occurring as of March 31, 2022. Further, economic scenarios used in the ACL model include the current and estimated future impact associated with the ongoing COVID-19 pandemic.

The Company currently forecasts PDs and LGDs based on economic scenarios over a two-year period, which we believe is a reasonable and supportable period. Beyond this point, PDs and LGDs 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.

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 March 31, 2022, the Company’s ACL model incorporated the following assumptions for key economic variables in the base-case, upside, and downside scenarios, which are largely unchanged from those used in the ACL model at December 31, 2021:

Base-case Scenario:

•U.S. unemployment declines to 3.5% through the end of 2022 and holds relatively constant at approximately 3.5% throughout 2023.
•U.S. real GDP growth decelerates throughout 2022 from approximately 5.4% to approximately 2.8% by the end of 2022. U.S. real GDP growth accelerates slightly from 2.7% from the beginning of 2023 to 2.8% towards the end of 2023.
•CRE index growth accelerates in 2022 from 0.4% in the second quarter of 2022 to approximately 8.3% by the end of 2022. Growth in the CRE index then decelerates from approximately 11.2% at the beginning of 2023 to 6.8% by the end of 2023.
•The 10-year U.S. Treasury yield ends 2022 at approximately 2.4%, and increases to approximately 3.1% by the end of 2023.

Upside Scenario:

•U.S. unemployment rate declines to approximately 3.1% through the end of 2022 and holds relatively constant at approximately 3.0% throughout 2023.
•U.S. real GDP growth decelerates throughout 2022 from approximately 9.3% to approximately 4.2% by the end of 2022. U.S. real GDP growth decelerates from approximately 4.4% in early 2023 to approximately 1.9% by the end of 2023.
•CRE index growth accelerates in 2022 from approximately 1.9% in the second quarter of 2022 to approximately 14.1% by the end of 2022. Growth in the CRE index then decelerates from approximately 15.0% at the beginning of 2023 to approximately 6.9% by the end of 2023.
•The 10-year U.S. Treasury yield ends 2022 at approximately 2.3%, and then increases to approximately 3.0% by the end of 2023.

Downside Scenario:

•U.S. unemployment rate increases to approximately 8.2% through the end of 2022 and then declines moderately to approximately 8.0% by the end of 2023.
•U.S. real GDP declines decelerate in 2022 from approximately -4.0% in the second quarter to approximately -1.9% by the end of 2023. U.S. real GDP then returns to accelerating growth throughout 2023, with growth of approximately 3.4% by the end of 2023.
•CRE index declines accelerate in 2023 from approximately -3.5% in the second quarter of 2023 to approximately -19.5% by the end of 2023. The CRE index declines decelerate through the third quarter of 2023 from approximately -10.9% to -3.8%. The CRE index then returns to growth in the fourth quarter of 2023.
•The 10-year U.S. Treasury yield ends 2022 at approximately 1.2%, and then increases to approximately 2.1% by the end of 2023.
Qualitative Adjustments

The Company recognizes that historical information used as the basis for determining future expected credit losses may not always, by itself, 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 March 31, 2022, qualitative adjustments primarily relate to certain segments of the loan portfolio deemed by management to be of a higher-risk profile where management believes the quantitative component of the Company’s ACL model may not have fully captured the associated impact to the ACL. In addition, qualitative adjustments also relate to heightened uncertainty as to future macroeconomic conditions and the related impact on certain loan segments. Qualitative adjustments to the ACL were made for SBA investor loans secured by real estate, construction loans, and franchise loans. Management reviews the need for an 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 tables 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 periods indicated:

Three Months Ended March 31, 2022
(Dollars in thousands) Beginning ACL Balance  Charge-offs  Recoveries Provision for Credit Losses Ending
ACL Balance
Investor loans secured by real estate
CRE non-owner occupied$37,380 $— $— $(1,406)$35,974 
Multifamily55,209 — — (884)54,325 
Construction and land5,211 — — 8 5,219 
SBA secured by real estate3,201 (70)— (81)3,050 
Business loans secured by real estate
CRE owner-occupied29,575 — 10 2,306 31,891 
Franchise real estate secured7,985 — — (8)7,977 
SBA secured by real estate4,866 — — 329 5,195 
Commercial loans
Commercial and industrial38,136 (2,179)1,841 800 38,598 
Franchise non-real estate secured15,084 — — (780)14,304 
SBA non-real estate secured565 (50)2 (27)490 
Retail loans
Single family residential255 — — (22)233 
Consumer loans285 — — (24)261 
Totals$197,752 $(2,299)$1,853 $211 $197,517 
Three Months Ended March 31, 2021
(Dollars in thousands) Beginning ACL Balance  Charge-offs  Recoveries Provision for Credit Losses  Ending
ACL Balance
Investor loans secured by real estate
CRE non-owner occupied$49,176 $(154)$— $(3,477)$45,545 
Multifamily62,534 — — 17,281 79,815 
Construction and land12,435 — — 828 13,263 
SBA secured by real estate5,159 (265)— 247 5,141 
Business loans secured by real estate
CRE owner-occupied50,517 — 15 (8,938)41,594 
Franchise real estate secured11,451 — — (575)10,876 
SBA secured by real estate6,567 (98)— (18)6,451 
Commercial loans
Commercial and industrial46,964 (1,279)601 (2,913)43,373 
Franchise non-real estate secured20,525 (156)— (1,466)18,903 
SBA non-real estate secured995 — 2 (107)890 
Retail loans
Single family residential1,204 — — (382)822 
Consumer loans491 — — (165)326 
Totals$268,018 $(1,952)$618 $315 $266,999 

The decrease in the ACL for loans held for investment during the three months ended March 31, 2022 of $235,000 was comprised of $446,000 in net charge-offs, partially offset by a $211,000 provision for credit losses. The provision for credit losses for the three months ended March 31, 2022 was reflective of higher loans held for investment and growing economic uncertainties, offset by improved economic forecasts and asset quality.

The decrease in the ACL for loans held for investment during the three months ended March 31, 2021 of $1.0 million is reflective of $1.3 million in net charge-offs, partially offset by a $315,000 provision for credit losses. The provision for credit losses for the three months ended March 31, 2021 was reflective of unfavorable economic conditions and forecasts used in the Company’s ACL model.
The following tables present PD bands for investor loans secured by real estate, business loans secured by real estate, and commercial loans segments of the loan portfolio as of the dates indicated.

Term Loans by Vintage
(Dollars in thousands)20222021202020192018PriorRevolvingRevolving Converted to Term During the PeriodTotal
March 31, 2022
Investor loans secured by real estate
CRE non-owner-occupied
0% - 5.00%$176,426 $651,475 $250,051 $369,190 $339,561 $791,623 $9,354 $— $2,587,680 
>5.00% - 10.00%— 8,632 1,141 718 16,386 54,229 — — 81,106 
Greater than 10%— 10,526 5,896 59,354 — 29,588 500 — 105,864 
Multifamily
0% - 5.00%461,776 2,251,232 865,755 1,057,766 398,127 926,880 286 — 5,961,822 
>5.00% - 10.00%4,218 23,077 5,903 24,620 1,799 14,581 — — 74,198 
Greater than 10%— 5,065 — — — — — — 5,065 
Construction and Land
0% - 5.00%45,018 106,397 62,442 15,840 5,618 7,389 — — 242,704 
>5.00% - 10.00%1,185 23,088 13,821 4,815 — — — — 42,909 
Greater than 10%— 3,500 3,388 7,901 3,409 — — — 18,198 
SBA secured by real estate
0% - 5.00%1,966 130 496 6,135 10,129 23,213 — — 42,069 
>5.00% - 10.00%— — — — — — — — — 
Greater than 10%— — — — — 573 — — 573 
Total investor loans secured by real estate690,589 3,083,122 1,208,893 1,546,339 775,029 1,848,076 10,140 — 9,162,188 
Business loans secured by real estate
CRE owner-occupied
0% - 5.00%250,202 830,646 263,304 279,071 143,848 597,055 4,719 — 2,368,845 
>5.00% - 10.00%— — — — 764 — — — 764 
Greater than 10%— — 4,673 2,516 5,140 10,046 — — 22,375 
Franchise real estate secured
0% - 5.00%24,715 152,674 35,974 54,053 35,233 73,922 — — 376,571 
>5.00% - 10.00%— 1,245 — — 1,250 2,813 — — 5,308 
Greater than 10%— 2,388 — — — — — — 2,388 
SBA secured by real estate
0% - 5.00%6,107 7,452 1,596 5,785 3,459 22,774 — — 47,173 
>5.00% - 10.00%— — 761 1,348 1,302 9,414 — — 12,825 
Greater than 10%— — — — 1,887 6,581 — — 8,468 
Total business loans secured by real estate281,024 994,405 306,308 342,773 192,883 722,605 4,719 — 2,844,717 
Term Loans by Vintage
(Dollars in thousands)20222021202020192018PriorRevolvingRevolving Converted to Term During the PeriodTotal
March 31, 2022
Commercial loans
Commercial and industrial
0% - 5.00%75,796 410,671 67,470 178,211 101,951 177,185 854,129 1,247 1,866,660 
>5.00% - 10.00%2,111 6,964 1,608 7,018 3,819 3,589 317,797 — 342,906 
Greater than 10%963 1,941 — 12 1,365 1,763 25,522 1,500 33,066 
Franchise non-real estate secured
0% - 5.00%23,120 158,940 15,289 62,490 36,456 35,717 555 — 332,567 
>5.00% - 10.00%462 769 8,020 14,244 5,244 7,306 106 — 36,151 
Greater than 10%— — — 1,550 3,517 14,537 — — 19,604 
SBA not secured by real estate
0% - 5.00%663 467 477 87 266 2,451 — — 4,411 
>5.00% - 10.00%— — 66 1,775 490 2,301 — — 4,632 
Greater than 10%— — — 140 244 692 642 — 1,718 
Total commercial loans$103,115 $579,752 $92,930 $265,527 $153,352 $245,541 $1,198,751 $2,747 $2,641,715 

Term Loans by Vintage
(Dollars in thousands)20212020201920182017PriorRevolvingRevolving Converted to Term During the PeriodTotal
December 31, 2021
Investor loans secured by real estate
CRE non-owner-occupied
0% - 5.00%$654,823 $233,718 $375,691 $392,892 $193,762 $682,357 $4,022 $— $2,537,265 
>5.00% - 10.00%37,931 22,965 9,174 2,713 23,559 23,707 5,331 — 125,380 
Greater than 10%15,806 13,261 50,175 — 1,067 27,670 513 — 108,492 
Multifamily
0% - 5.00%2,242,420 929,964 1,174,859 442,410 470,107 548,156 286 — 5,808,202 
>5.00% - 10.00%13,226 7,393 24,646 1,807 8,922 6,676 — — 62,670 
Greater than 10%5,062 14,770 — 1,230 — — — — 21,062 
Construction and land
0% - 5.00%110,545 81,029 23,030 8,321 3,857 3,559 — — 230,341 
>5.00% - 10.00%5,500 14,264 9,931 4,094 — — — — 33,789 
Greater than 10%3,487 2,428 7,595 — — — — — 13,510 
SBA secured by real estate
0% - 5.00%130 497 6,259 12,374 15,149 11,572 — — 45,981 
>5.00% - 10.00%— — — — — — — — — 
Greater than 10%— — — — 600 336 — — 936 
Total investor loans secured by real estate3,088,930 1,320,289 1,681,360 865,841 717,023 1,304,033 10,152 — 8,987,628 
Term Loans by Vintage
(Dollars in thousands)20212020201920182017PriorRevolvingRevolving Converted to Term During the PeriodTotal
December 31, 2021
Business loans secured by real estate
CRE owner-occupied
0% - 5.00%853,044 273,469 287,249 161,635 187,130 456,170 6,738 292 2,225,727 
>5.00% - 10.00%— — — — — 8,101 — — 8,101 
Greater than 10%— — 2,553 6,075 2,966 5,592 — — 17,186 
Franchise real estate secured
0% - 5.00%154,009 36,335 55,091 37,559 53,519 33,635 1,361 — 371,509 
>5.00% - 10.00%843 — — 2,488 2,769 1,243 — — 7,343 
Greater than 10%1,529 — — — — — — — 1,529 
SBA secured by real estate
0% - 5.00%6,379 2,364 6,040 8,986 8,718 16,947 — — 49,434 
>5.00% - 10.00%— — 1,291 139 2,006 7,681 — — 11,117 
Greater than 10%— — — 2,062 2,700 3,871 — — 8,633 
Total business loans secured by real estate1,015,804 312,168 352,224 218,944 259,808 533,240 8,099 292 2,700,579 
Commercial loans
Commercial and industrial
0% - 5.00%417,780 77,755 192,478 114,593 120,869 67,194 680,662 3,380 1,674,711 
>5.00% - 10.00%8,349 1,880 7,757 2,878 2,476 3,595 375,829 341 403,105 
Greater than 10%1,326 — 159 2,683 863 1,302 18,060 903 25,296 
Franchise non-real estate secured
0% - 5.00%155,064 18,370 64,503 39,389 21,483 21,524 — — 320,333 
>5.00% - 10.00%8,801 5,573 20,703 5,672 2,189 8,840 — — 51,778 
Greater than 10%— — 1,589 3,627 13,346 1,903 — — 20,465 
SBA not secured by real estate
0% - 5.00%474 564 1,088 370 732 1,636 — — 4,864 
>5.00% - 10.00%— — 205 410 2,074 512 — — 3,201 
Greater than 10%— — 756 339 685 547 653 — 2,980 
Total commercial loans$591,794 $104,142 $289,238 $169,961 $164,717 $107,053 $1,075,204 $4,624 $2,506,733 
A significant driver in the ACL for loans in the investor real estate secured and business real estate secured segments is estimated LTV ratio. The following tables summarize the amortized cost of loans in these segments by current estimated LTV and by year of origination as of the dates indicated:
Term Loans by Vintage
(Dollars in thousands)20222021202020192018PriorRevolvingRevolving Converted to Term During the PeriodTotal
March 31, 2022
Investor loans secured by real estate
CRE non-owner-occupied
55% and below$80,360 $370,848 $138,963 $182,092 $166,633 $592,412 $9,854 — $1,541,162 
>55-65%88,510 238,821 90,596 154,776 54,175 250,482 — — 877,360 
>65-75%7,556 60,735 27,529 56,266 130,804 27,166 — — 310,056 
Greater than 75%— 229 — 36,128 4,335 5,380 — — 46,072 
Multifamily
55% and below111,585 409,021 197,947 256,819 169,113 449,182 286 — 1,593,953 
>55-65%209,094 944,247 367,310 466,705 194,097 348,010 — — 2,529,463 
>65-75%142,824 896,113 303,401 353,096 36,716 134,308 — — 1,866,458 
Greater than 75%2,491 29,993 3,000 5,766 — 9,961 — — 51,211 
Construction and land
55% and below46,203 129,135 79,651 10,675 4,155 7,389 — — 277,208 
>55-65%— 3,850 — 8,916 4,872 — — — 17,638 
>65-75%— — — 8,965 — — — — 8,965 
Greater than 75%— — — — — — — — — 
SBA secured by real estate
55% and below1,966 — — — 1,469 2,908 — — 6,343 
>55-65%— — — 2,392 1,941 4,307 — — 8,640 
>65-75%— 130 — 2,654 3,113 7,158 — — 13,055 
Greater than 75%— — 496 1,089 3,606 9,413 — — 14,604 
Total investor loans secured by real estate690,589 3,083,122 1,208,893 1,546,339 775,029 1,848,076 10,140 — 9,162,188 
Business loan secured by real estate
CRE owner-occupied
55% and below121,356 401,001 109,427 104,982 79,468 450,860 4,719 — 1,271,813 
>55-65%59,295 202,766 52,624 63,290 29,886 107,522 — — 515,383 
>65-75%60,334 190,253 105,172 103,746 35,344 32,545 — — 527,394 
Greater than 75%9,217 36,626 754 9,569 5,054 16,174 — — 77,394 
Franchise real estate secured
55% and below17,475 39,481 16,725 14,418 12,385 23,380 — — 123,864 
>55-65%— 45,789 11,986 3,995 7,313 12,726 — — 81,809 
>65-75%1,792 33,932 5,426 32,540 9,235 35,728 — — 118,653 
Greater than 75%5,448 37,105 1,837 3,100 7,550 4,901 — — 59,941 
SBA secured by real estate
55% and below1,040 2,508 589 1,646 962 17,411 — — 24,156 
>55-65%— 724 555 199 1,454 9,264 — — 12,196 
>65-75%— 1,178 327 3,465 647 7,823 — — 13,440 
Greater than 75%5,067 3,042 886 1,823 3,585 4,271 — — 18,674 
Total business loans secured by real estate$281,024 $994,405 $306,308 $342,773 $192,883 $722,605 $4,719 $— $2,844,717 
Term Loans by Vintage
(Dollars in thousands)20212020201920182017PriorRevolvingRevolving Converted to Term During the PeriodTotal
December 31, 2021
Investor loans secured by real estate
CRE non-owner-occupied
55% and below$366,617 $141,752 $184,553 $171,879 $130,679 $533,990 $9,866 $— $1,539,336 
>55-65%277,092 91,539 155,908 86,933 79,043 172,713 — — 863,228 
>65-75%64,619 36,653 58,350 131,975 5,662 25,446 — — 322,705 
Greater than 75%232 — 36,229 4,818 3,004 1,585 — — 45,868 
Multifamily
55% and below397,562 226,129 285,520 181,826 197,276 279,880 286 — 1,568,479 
>55-65%932,115 416,712 510,840 219,710 185,773 198,802 — — 2,463,952 
>65-75%906,910 306,272 391,686 41,174 94,142 67,964 — — 1,808,148 
Greater than 75%24,121 3,014 11,459 2,737 1,838 8,186 — — 51,355 
Construction and land
55% and below116,575 95,293 26,501 4,172 3,857 3,559 — — 249,957 
>55-65%2,957 2,428 5,095 6,650 — — — — 17,130 
>65-75%— — 8,960 1,593 — — — — 10,553 
Greater than 75%— — — — — — — — — 
SBA secured by real estate
55% and below— — — 632 693 2,159 — — 3,484 
>55-65%— — 2,399 1,950 1,903 3,595 — — 9,847 
>65-75%130 — 2,767 3,630 4,444 4,346 — — 15,317 
Greater than 75%— 497 1,093 6,162 8,709 1,808 — — 18,269 
Total investor loans secured by real estate3,088,930 1,320,289 1,681,360 865,841 717,023 1,304,033 10,152 — 8,987,628 
Business loan secured by real estate
CRE owner-occupied
55% and below400,857 95,504 107,766 87,779 134,184 347,926 6,738 292 1,181,046 
>55-65%214,798 67,639 60,192 32,283 35,513 80,347 — — 490,772 
>65-75%188,022 78,589 112,217 41,874 12,241 25,460 — — 458,403 
Greater than 75%49,367 31,737 9,627 5,774 8,158 16,130 — — 120,793 
Franchise real estate secured
55% and below32,189 16,889 8,954 12,469 9,163 14,552 1,361 — 95,577 
>55-65%47,521 3,603 10,270 7,442 4,749 9,349 — — 82,934 
>65-75%39,409 13,991 32,743 11,289 29,641 9,768 — — 136,841 
Greater than 75%37,262 1,852 3,124 8,847 12,735 1,209 — — 65,029 
SBA secured by real estate
55% and below4,333 590 1,821 1,123 4,512 14,850 — — 27,229 
>55-65%452 555 199 954 1,524 8,497 — — 12,181 
>65-75%1,082 328 3,478 5,208 4,853 2,793 — — 17,742 
Greater than 75%512 891 1,833 3,902 2,535 2,359 — — 12,032 
Total business loans secured by real estate$1,015,804 $312,168 $352,224 $218,944 $259,808 $533,240 $8,099 $292 $2,700,579 
The following tables present the FICO bands, at origination, for the retail segment of the loan portfolio as of the dates indicated:
Term Loans by Vintage
(Dollars in thousands)20222021202020192018PriorRevolvingRevolving Converted to Term During the PeriodTotal
March 31, 2022
Retail loans
Single family residential
Greater than 740$— $309 $194 $— $— $30,820 $18,657 — $49,980 
>680 - 740— — — — 31 5,410 4,278 — 9,719 
>580 - 680— — — — — 6,651 755 — 7,406 
Less than 580— — — — — 12,842 31 — 12,873 
Consumer loans
Greater than 740— 7 25 26 10 929 1,847 — 2,844 
>680 - 740— 3 — 11 — 330 1,852 — 2,196 
>580 - 680— — — 4 — 51 46 — 101 
Less than 580— — — — — — 16 — 16 
Total retail loans$— $319 $219 $41 $41 $57,033 $27,482 $— $85,135 

December 31, 2021
Retail loans
Single family residential
Greater than 740$313 $211 $— $— $1,446 $40,605 $17,553 — $60,128 
>680 - 740— — — 32 103 7,602 5,579 — 13,316 
>580 - 680— — — — 450 6,989 756 — 8,195 
Less than 580— — — — 9 13,612 32 — 13,653 
Consumer loans
Greater than 7407 28 32 19 9 944 2,196 — 3,235 
>680 - 7404 — 17 — 2 431 1,859 — 2,313 
>580 - 680— — 5 — — 54 42 — 101 
Less than 580— — — — — — 16 — 16 
Total retail loans$324 $239 $54 $51 $2,019 $70,237 $28,033 $— $100,957 

Allowance for Credit Losses for Off-Balance Sheet Commitments

The Company maintains an ACL on off-balance sheet commitments related to unfunded loans and lines of credit, which is included in other liabilities of the consolidated statements of financial condition. The allowance for off-balance sheet commitments was $27.5 million at March 31, 2022, $27.3 million at December 31, 2021, and $32.8 million at March 31, 2021. The provision expense for off-balance sheet commitments of $218,000 during the three months ended March 31, 2022 was related primarily to the increase in off-balance sheet commitments. The provision expense of $1.7 million during the three months ended March 31, 2021 related primarily to an increase in outstanding unfunded loan commitments in conjunction with continued unfavorable economic conditions and forecasts reflected in the Company’s CECL model.

The Company applies an expected credit loss estimation methodology for off-balance sheet commitments that is largely 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 utilization at default. These assumptions are based on the Company’s own historical internal loan data.