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Organization and Basis of Presentation | 6 Months Ended
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Jun. 30, 2020
Organization Consolidation And Presentation Of Financial Statements [Abstract] |
Organization and Basis of Presentation | Note 1 — Organization and Basis of Presentation Hanmi Financial Corporation (“Hanmi Financial,” the “Company,” “we,” “us” or “our”) is a bank holding company whose primary subsidiary is Hanmi Bank (the “Bank”). Our primary operations are related to traditional banking activities, including the acceptance of deposits and the lending and investing of money through the operation of the Bank. In management’s opinion, the accompanying unaudited consolidated financial statements of Hanmi Financial and its subsidiaries reflect all adjustments of a normal and recurring nature that are necessary for a fair presentation of the results for the interim periods ended June 30, 2020, but are not necessarily indicative of the results that will be reported for the entire year or any other interim period. Certain information and footnote disclosures normally included in annual financial statements prepared in accordance with U.S. generally accepted accounting principles (“GAAP”) have been condensed or omitted. The unaudited consolidated financial statements are prepared in conformity with GAAP and in accordance with the instructions to Form 10-Q pursuant to the rules and regulations of the Securities and Exchange Commission. The interim information should be read in conjunction with our Annual Report on Form 10-K for the year ended December 31, 2019 (the “2019 Annual Report on Form 10-K”). The preparation of interim unaudited consolidated financial statements in conformity with GAAP requires management to make estimates and assumptions that affect the reported amounts of assets and liabilities, the disclosure of contingent assets and liabilities at the date of the financial statements, and the reported amounts of revenues and expenses during the reporting period. These estimates and assumptions affect the amounts reported in the unaudited financial statements and disclosures provided, and actual results could differ. Descriptions of our significant accounting policies are included in Note 1 - Summary of Significant Accounting Policies in the Notes to Consolidated Financial Statements in the 2019 Annual Report on Form 10-K. FASB ASU 2016-13, Financial Instruments - Credit Losses (Topic 326): Measurement of Credit Losses on Financial Instruments, On January 1, 2020, the Company adopted ASU 2016-13 Financial Instruments – Credit Losses (Topic 326): Measurement of Credit Losses on Financial Instruments, which replaced the incurred loss methodology with an expected loss methodology that is referred to as the current expected credit loss (CECL) methodology. The measurement of expected credit losses under the CECL methodology is applicable to financial assets measured at amortized cost, including loan receivables and held-to-maturity debt securities. It also applies to off-balance sheet credit exposures not accounted for as insurance (loan commitments, standby letters of credit, financial guarantees, and other similar instruments) and net investments in leases recognized by a lessor in accordance with Topic 842 on leases. In addition, ASU 2016-13 made changes to the accounting for available-for sale debt securities. The Company adopted ASU 2016-13 using the prospective transition approach for debt securities for which the Company would have recognized other-than-temporary impairment prior to January 1, 2020. However, the Company had no such securities and as a result, there was no effect on the balance sheet related to securities from the adoption of ASU 2016-13. As a result, the amortized cost basis remained the same before and after the effective date of ASU 2016-13. The adoption of ASU 2016-13 resulted in a $17.4 million increase to the beginning balance of the allowance for credit losses, a $0.3 million decrease to the beginning balance of the allowance for off-balance sheet items, and an after-tax charge of $12.2 million to the beginning balance of retained earnings. According to ASU 2016-13, the Bank was required to measure its expected credit losses of financial assets on a collective (pool) basis when similar risk characteristic(s) exist. The Bank segmented the loans primarily by loan types, considering that the same type of loans share considerable similar risk characteristics, including the collateral type, loan purpose, contract term, amortization and payment structure. The Company measured expected credit losses of financial assets on a collective (pool) basis, when the financial assets share similar risk characteristics. Depending on the nature of the pool of financial assets with similar risk characteristics, the Company used a discounted cash flow (“DCF”) method, Probability of Default / Loss Given Default method (“PD/LGD”), or a Weighted Average Remaining Maturity (“WARM”) method to estimate expected credit losses. The Company’s methodologies for estimating the allowance for credit losses consider ed available relevant information about the collectability of cash flows, including information about past events, current conditions, and reasonable and supportable forecasts. The methodologies appl ied historical loss information, adjusted for asset-specific characteristics, economic conditions at the measurement date, and forecasts about future economic conditions expected to exist through the contractual lives of the financial assets that were reasonable and supportable, to the identified pools of financial assets with similar risk characteristics for which the historical loss experience was observed. The Company’s methodologies revert to historical loss information on a straight-line basis over twelve quarters when it can no longer develop reasonable and supportable forecasts. The Company has disaggregated the portfolios of financial assets into the following material segments of like-kind loans or leases with similar risk characteristics using the following methodologies: The Company used the discounted cash flow (DCF) method to estimate allowances for credit losses for the commercial property, construction, and residential real estate loan portfolios, the commercial and industrial loan portfolio, and the consumer loan portfolio. For all loan pools utilizing the DCF method, the Company utilized and forecasted the national unemployment rate as the primary loss driver. The Company also utilized and forecasted either the annualized average return rate from the National Council of Real Estate Investment Fiduciaries (NCREIF) Property Index for commercial real estate loans or the one-year percentage change in the S&P/Case-Shiller U.S National Home Price Index (NHPI) for residential real estate loans as a second loss driver depending on the nature of the underlying loan pool and how well that loss driver correlates to expected future losses. For all DCF models at January 1, 2020, the Company determined that four-quarters represented a reasonable and supportable forecast period and reverted to a historical loss rate over twelve quarters on a straight-line basis. The Company leveraged economic projections from the quarterly Federal Open Market Committee (FOMC) and the Federal Reserve Economic Database (FRED) to inform its loss driver forecasts over the four-quarter forecast period. For each of these loan segments, the Company applied an expected loss ratio based on the discounted cash flows adjusted as appropriate for qualitative factors. Qualitative loss factors are based on the Company's judgment of company, market, industry or business specific data, changes in the underlying loan composition of specific portfolios, trends relating to credit quality, delinquency, nonperforming and adversely rated loans, and reasonable and supportable forecasts of economic conditions. The Company used the Probability of Default/Loss Given Default (PD/LGD) method for the SBA portfolio to accommodate the unique nature of these loans. Although the PD/LGD methodology is an element of the DCF model, the stand-alone PD/LGD methodology minimizes complications related to the characteristics of SBA loans. A uniqueness of the SBA portfolio is that the U.S. Small Business Administration policy requires servicers to undertake all reasonable collection efforts before charging-off the loan. As a result, the recovery rate for SBA loans tend to be more volatile and not intuitively correlated to economic factors. The Company used a Weighted Average Remaining Maturity (WARM) method to estimate expected credit losses for equipment financing agreements or the equipment lease receivables portfolio. The Company applied an expected loss ratio based on internal historical losses adjusted as appropriate for qualitative factors. The Company's evaluation of market, industry or business specific data, changes in the underlying portfolio composition, trends relating to credit quality, delinquency, nonperforming and adversely rated leases, and reasonable and supportable forecasts of economic conditions informed the estimate of qualitative factors. As allowed by ASU 2016-13, the Company elected to maintain pools of loans accounted for under ASC 310-30. In accordance with the standard, management did not reassess whether modifications to individual acquired financial assets accounted for in pools were troubled debt restructurings as of the date of adoption. The Company estimated the allowance for credit losses on loans based on the underlying assets’ amortized cost basis, which was the amount at which the financing receivable is originated or acquired, adjusted for applicable accretion or amortization of premium, discount, and net deferred fees or costs, collection of cash, and charge-offs. In the event that collection of principal becomes uncertain, the Company has policies in place to reverse accrued interest in a timely manner. Therefore, the Company has made a policy election to exclude accrued interest from the measurement of allowance for credit losses. Expected credit losses are reflected in the allowance for credit losses through a charge to credit loss expense. When the Company deems all or a portion of a financial asset to be uncollectible, the appropriate amount is written off and the allowance for credit losses is reduced by the same amount. The Company applies judgment to determine when a financial asset is deemed uncollectible; however, generally speaking, an asset will be considered uncollectible no later than when all efforts at collection have been exhausted. Subsequent recoveries, if any, are credited to the allowance for credit losses when received. The following table illustrates the allowance for credit losses and the related impact under ASU 2016-13 to the Company as of January 1, 2020.
|  | As Reported Under ASU 2016-13 |  |  | Pre-ASU 2016-13 Adoption |  |  | Impact of ASU 2016-13 Adoption |
Real estate loans: |  |  |  |  |  |  |  |  |  |  |  |
Commercial property |  |  |  |  |  |  |  |  |  |  |  |
Retail |  | $ | 6,785 |  |  | $ | 4,911 |  |  | $ | 1,873 |
Hospitality |  |  | 12,387 |  |  |  | 6,686 |  |  |  | 5,702 |
Other |  |  | 13,415 |  |  |  | 8,060 |  |  |  | 5,355 |
Total commercial property loans |  |  | 32,587 |  |  |  | 19,657 |  |  |  | 12,930 |
Construction loans |  |  | 15,590 |  |  |  | 15,003 |  |  |  | 587 |
Residential property loans |  |  | 2,150 |  |  |  | 1,695 |  |  |  | 455 |
Total real estate loans |  |  | 50,327 |  |  |  | 36,355 |  |  |  | 13,972 |
Commercial and industrial loans: |  |  |  |  |  |  |  |  |  |  |  |
Commercial term loans |  |  | 12,175 |  |  |  | 14,077 |  |  |  | (1,903 | )
Commercial lines of credit |  |  | 1,358 |  |  |  | 1,887 |  |  |  | (529 | )
International loans |  |  | 176 |  |  |  | 242 |  |  |  | (65 | )
Total commercial loans |  |  | 13,709 |  |  |  | 16,206 |  |  |  | (2,497 | )
Leases receivable |  |  | 14,669 |  |  |  | 8,767 |  |  |  | 5,902 |
Consumer loans |  |  | 135 |  |  |  | 80 |  |  |  | 55 |
Allowance for credit losses on loans receivable |  | $ | 78,841 |  |  | $ | 61,408 |  |  | $ | 17,433 |
Allowance for credit losses on off-balance sheet items |  | $ | 2,062 |  |  | $ | 2,398 |  |  | $ | (336 | )
The Company used the methodologies described above in the implementation of CECL at January 1, 2020 and through March 31, 2020. The Company, however, adjusted the methodologies for the commercial property, construction, and residential real estate portfolios during the three months ended June 30, 2020 to reflect better the forecast of potential losses arising from the more unstable economic environment due to the COVID-19 pandemic. See Note 3 - Loans for a more detailed description of the changes in the allowance for credit losses methodologies. FASB ASU 2017-04, Intangibles-Goodwill and Other (Topic 350): Simplifying the Test for Goodwill Impairment, Effective January 1, 2020, the Company adopted this standard, which simplifies the subsequent measurement of goodwill impairment by eliminating the requirement to calculate the implied fair value of goodwill (i.e., the current Step 2 of the goodwill impairment test) to measure a goodwill impairment charge. Under this ASU, the impairment test is simply the comparison of the fair value of a reporting unit with its carrying amount (the current Step 1), with the impairment charge being the deficit in fair value but not exceeding the total amount of goodwill allocated to that reporting unit. The simplified one-step impairment test applies to all reporting units (including those with zero or negative carrying amounts). An entity was to apply the amendments in this ASU on a prospective basis and was required to disclose the nature of and reason for the change in accounting principle upon transition. The Company’s goodwill arose from the purchase of an equipment leasing portfolio in 2016. The equipment leasing portfolio has grown since acquisition, and the Company has concluded no impairment has occurred. The outbreak of the novel coronavirus, also known as COVID-19 has resulted in orders for individuals to shelter-in place and restricted business activities. As a result, the operations and business results of the Company could be materially adversely affected. The extent to which the COVID-19 crisis may impact business activity or investment results will depend on future developments, which are highly uncertain and cannot be predicted, including new information which may emerge concerning the severity of the coronavirus and the actions required to contain the coronavirus or treat its impact, among others. This uncertainty may impact the accuracy of our significant estimates, which includes the allowance for credit losses, the allowance for credit losses related to off-balance sheet items, and the valuation of intangible assets including deferred tax assets, goodwill, and servicing assets.

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