Month: September 2016

Abstract:   This issue’s “Bank Wire” reports on the DOL’s new overtime requirements, which increase the salary level threshold for white-collar exempt employees and are expected to yield a large impact on financial institutions. It also discusses the FFIEC’s new cybersecurity guidance, which urges financial institutions to review their risk-management practices and controls for IT systems and wholesale payment networks, and recommends using multiple-layered security controls.

Bank Wire

Are you ready for the new DOL overtime rule?

New overtime requirements are expected to yield a large impact on financial institutions. The U.S. Department of Labor (DOL) recently finalized its overtime rule, doubling the salary threshold for exempt employees.

The final rule increases the salary level threshold for white-collar exempt employees from $455 to $913 per week, or $23,660 to $47,476 per year, starting December 1. Any employee making less than those amounts will likely be required to be paid overtime compensation.

The new rule also hikes the salary threshold for highly compensated employees (HCEs) from $100,000 per year to $134,004 per year. HCEs must receive at least the full standard salary amount — or $913 — per week on a salary or fee basis without regard to the payment of nondiscretionary bonuses and incentive payments. But such payments will count toward the total annual compensation requirement. The standard salary and HCE annual compensation levels will automatically update every three years.

Once the rule takes effect, employers will have several options for dealing with exempt employees who’re reclassified as nonexempt: 1) Raise their salaries above the new threshold, 2) pay them time-and-a-half for overtime, 3) limit them to 40 hours per week, or 4) some combination of the above.

Between now and December 1, assess the impact of the new rule on your workers and develop a plan for implementing it. Some questions to ask:

• What are the relative costs of increasing salaries to the new threshold vs. paying time-and-a-half for overtime?
• How will the rule affect employee morale? Will employees view loss of exempt status as a demotion?
• How will you deal with job titles in which some employees are exempt and some aren’t?
• How will the rule affect compensation arrangements that provide for a modest base salary but a generous bonus potential?

FFIEC issues new cybersecurity guidance

Financial institutions need to actively manage the risks associated with interbank messaging and wholesale payment networks. So warns a recent statement from the Federal Financial Institutions Examination Council (FFIEC), which reports that recent cyberattacks have targeted these banking functions. By attempting to originate unauthorized transactions, cybercriminals have shown a capability for compromising a financial institution’s wholesale payment networks and bypassing information security controls, the agency says.

The FFIEC urges financial institutions to review their risk-management practices and controls for information technology systems and wholesale payment networks. It also recommends using multiple-layered security controls to set up several lines of defense.

You can read the statement at https://www.ffiec.gov/cybersecurity.htm.

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Abstract:   Most bankers on the business-lending side of operations have a constant stream of customer financial statements passing over their desk (virtual or otherwise) for an evaluation of the borrowers’ creditworthiness. Thus, bankers need to possess enough knowledge about different types of business structures to shine the right spotlight on diverse financial statements. This article discusses the similarities between, and differences of, C corporation and S corporation financial statements.

 

Do you “speak” both S corporation and C corporation?

 

You likely have a constant stream of customer financial statements passing over your desk (virtual or otherwise) for an evaluation of the borrowers’ creditworthiness. But do you possess enough knowledge about different types of business structures to shine the right spotlight on their diverse financial statements?

Both “languages” have similarities

Both S and C corporations maintain books, records and bank accounts separately from those of their owners and follow state rules about annual directors’ meetings, fees and administrative filings. And both must pay and withhold payroll taxes for working owners in the business.

At first glance, it may be hard to tell which borrowers have elected S status. But there are a few telltale signs. Importantly, S corporations don’t incur corporate-level tax, so they can forgo reporting federal (and possibly state) income tax expense on their income statements. Also, S corporations generally don’t report prepaid income taxes, income taxes payable, or deferred income tax assets and liabilities on their balance sheets. Instead, S corporation owners pay tax at the personal level on their share of the corporation’s income and gains.

The reporting of dividends vs. distributions

Other financial reporting differences are more subtle. For instance, when C corporations pay dividends, they’re taxed twice: They pay tax at the corporate level when the company files its annual tax return, and the individual owners pay again when dividends and liquidation proceeds are taxed at the personal level.

When S corporations pay distributions — the name for dividends paid by S corporations — the payout is generally not subject to personal-level tax as long as the shares have positive tax “basis.” (S corporation basis is typically a function of capital contributions, earnings and distributions.)

So, in the equity section of an S corporation’s balance sheet, there may be a sizable negative line item for shareholder distributions. In fact, S corporation distributions are far more common than dividends for privately held C corporations.

There are two reasons for this: S corporation distributions aren’t subject to double taxation, so there’s no tax penalty for making distributions. And S corporations often distribute cash to owners to cover the owners’ shares of the personal income taxes attributable to the company’s income (although they’re not required to do so).

To further complicate matters, S corporations may use different strategies from year to year to extract cash from the business. For example, the owners might use shareholder loans in year 1, pay higher bonuses in year 2, and take quarterly distributions in year 3. Such variety makes it difficult for lenders to compare an S corporation’s performance over time — or to that of borrowers that operate as C corporations.

Owner motivation varies when setting salaries

C corporations may be tempted to pay owners above-market salaries to get cash out of the business and avoid the double taxation that comes with dividends. Conversely, S corporations tend to do the reverse: They may try to maximize tax-free distributions and pay owners below-market salaries to minimize payroll taxes.

The IRS is on the lookout for corporations that compensate owners too much (or too little) for their day-to-day contributions. Regardless of entity type, an owner’s compensation should be commensurate with his or her skills, experience and involvement in the business.

If the IRS audits an owner’s compensation, it might impair the borrower’s ability to service debt. For example, to the extent that an S corporation shareholder’s compensation doesn’t reflect the market value of the services he or she provides, the IRS may reclassify a portion of earnings as unpaid wages. Then the company will owe additional employment tax, interest and penalties on the reclassified wages.

Understanding the ins and outs

Both S and C corporation business structures offer certain advantages and shortcomings for their owners. It’s your job to make sure you know the nuances of both entity types before you give their loan requests your stamp of approval.

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Abstract:   As federal banking regulators intensify their scrutiny of Bank Secrecy Act and Anti-Money Laundering compliance, community banks need to become more proactive in combating money laundering. One potential tool worth considering is data visualization software. This article examines recent compliance requirements and how to effectively incorporate data visualization software into a bank’s antifraud lines of defense.

Data visualization helps banks combat money laundering

 

As federal banking regulators intensify their scrutiny of Bank Secrecy Act and Anti-Money Laundering compliance, community banks need to become more proactive in combating money laundering. One potential tool worth considering is data visualization software.

Increased emphasis on BSA/AML

Several recent developments reflect the federal banking agencies’ increasing concern about Bank Secrecy Act and Anti-Money Laundering (BSA/AML) compliance efforts:

• In July, the Financial Crimes Enforcement Network (FinCEN) introduced new customer due diligence (CDD) rules that require institutions to incorporate beneficial ownership identification requirements into existing CDD policies and procedures.
• In its Spring 2016 Semiannual Risk Perspective, the Office of the Comptroller of the Currency (OCC) alerted banks to increasing BSA/AML risks associated with technological developments and new product offerings in the banking industry.
• In recent months, regulators have been scrutinizing automated monitoring systems used by banks to detect suspicious activity to ensure that they’re configured properly.

And don’t assume that regulators are limiting their heightened scrutiny to larger banks. The OCC’s report noted that some large banks are restricting certain customers’ activities or closing their accounts because of BSA/AML concerns. Displacement of these customers, the report warned, “may result in higher-risk customers moving to smaller and less sophisticated banks . . . that potentially have less experience managing the associated BSA/AML risks.”

Banks that fail to take reasonable steps to detect and prevent money laundering activity risk not only government fines, but negative publicity and reputational risk.

Seeing the big picture

Data visualization software — also known as visual analytics — can be a powerful AML tool. Traditional AML software products and methods do a good job of detecting known AML issues. But data visualization software, which is commonly used as an antifraud weapon, excels at spotting new or unknown AML activity.

As criminal activity becomes more sophisticated and more difficult to detect, traditional AML software or methods may no longer be enough. Data visualization software creates visual representations of data. These representations may take many different forms, from pie charts and bar graphs to scatterplots, decision trees and geospatial maps. Visualization helps banks identify suspicious patterns, relationships, trends or anomalies that are difficult to spot using traditional tools alone. It’s particularly useful in identifying new or emerging risks before they do lasting damage.

Criminal enterprises that wish to launder money typically use multiple entities and multiple bank accounts, both domestic and foreign. Using data visualization software, banks can map out the flow of funds across various accounts, identifying relationships between accounts and the entities associated with them. Data visualization can reveal clusters of interrelated entities that would be difficult and time-consuming to spot using traditional methods.

These clusters or other relationships don’t necessarily indicate criminal activity. But they help focus a bank’s AML efforts by pinpointing suspicious activities that warrant further investigation.

Get your data in order

Perhaps the biggest challenge in taking advantage of data visualization software and other automated AML tools is the fact that, at many institutions, information is scattered among many separate systems. For data visualization to do its job, the first step is to collect and integrate this information into a single database. Once this is done, data visualization software can help your bank detect potential AML issues more quickly and effectively.

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Abstract:   In a dramatic change to bank accounting guidelines, the FASB recently finalized its long-awaited CECL model for estimating credit losses. This article highlights the most important elements of the new model, including its forward-looking approach (which involves its treatment of covered and PCD assets, as well as its position on estimating losses and accounting for AFS securities) and its impact on community banks. A sidebar explains when banks must adopt the CECL model.

Accounting for credit losses

Get ready for CECL

In a dramatic change to bank accounting guidelines, the Financial Accounting Standards Board (FASB) recently finalized its long-awaited Current Expected Credit Loss (CECL) model for estimating credit losses. The new standard — Accounting Standards Update (ASU) No. 2016-13 — applies to all organizations. But financial institutions will be affected the most.

Although CECL’s impact will depend on a particular institution’s facts and circumstances, it will cause many banks to increase their allowances for loan and lease losses (ALLL), affecting both earnings and capital.

Forward-looking approach

Currently, banks measure credit impairment based on incurred losses. Under CECL, they’ll adopt a forward-looking approach, recognizing an immediate allowance for all expected credit losses over the asset’s life.

The FASB believes that the incurred-loss model, which delays recognition of credit losses until they become probable, provides information that’s “too little, too late.” CECL addresses this problem by requiring organizations to record credit losses that are expected, but don’t yet meet the “probable” threshold. It also sets a single impairment model for all financial assets carried at amortized cost, in contrast to the multiple models used today.

Here are some highlights of the new standard, which doesn’t take effect for several years (see “When must you adopt CECL?”):

Covered assets. CECL will apply to 1) financial assets measured at amortized cost, including loans, held-to-maturity debt securities, trade and reinsurance receivables and net investments in leases, and 2) certain off-balance-sheet credit exposures, such as loan commitments and financial guarantees.

Estimating losses. The allowance for credit losses will be the difference between financial assets’ amortized cost basis and the net amount expected to be collected. To estimate expected losses, banks will consider a broader range of data than they do under current standards, including not only historical and current information, but also “reasonable and supportable forecasts that affect the collectability of the reported amount.”

Potential impact. Some experts, including the Comptroller of the Currency, predict that CECL will increase banks’ loan loss reserves by 30% to 50%. Other estimates are lower, but ultimately the impact on a particular institution will depend on a variety of factors, including historical experience, current conditions and market forecasts.

Accounting for AFS securities. The new standard will change the way credit losses are measured for available-for-sale (AFS) debt securities, requiring banks to use an allowance for credit losses. Unlike the current practice of writing down individual securities for other-than-temporary impairment, the new approach will allow banks to recognize subsequent reversals in credit loss estimates in current income. In addition, the credit losses on AFS debt securities will be limited to the amount by which fair value falls short of amortized cost.

Treatment of PCD assets. To simplify the accounting for purchased credit-deteriorated (PCD) assets, the ASU requires institutions to recognize an initial allowance for credit losses. Thereafter, such assets will be treated similarly to other financial assets measured at amortized cost.

Impact on community banks

In the years after CECL was first proposed, many community banks expressed concern about its potential complexity and the need to implement sophisticated modeling techniques. A recent joint statement by federal banking agencies should help ease these concerns. According to the statement, CECL will be scalable to institutions of all sizes. And it doesn’t prescribe specific estimation methods — rather, institutions should apply judgment in developing methods that are appropriate and practical.

The agencies “do not expect smaller and less complex institutions will need to implement complex modeling techniques.” Rather, they expect that these institutions will be able to meet CECL’s requirements by building on existing systems and methods for estimating credit losses. For example, a bank that uses historical loss rate methods would need to adjust its inputs to estimate remaining lifetime credit losses.

The statement also points out that CECL contemplates pooling assets with similar risk characteristics when estimating expected credit losses. In most cases, smaller banks will be able to continue using established practices for segmenting their portfolios.

Be prepared

CECL’s effective date is several years away. Nevertheless, banks should begin preparing soon to develop institution-appropriate credit loss models, evaluate the potential impact on capital, and identify any necessary system changes or additional data collection requirements.

 

 

Sidebar: When must you adopt CECL?

Here’s a summary of the new standard’s effective dates:

Organization type	Takes effect for:	Interim periods affected
SEC filers	Fiscal years beginning after 12/15/19	In 2020
Other PBEs* (non-SEC filers)	Fiscal years beginning after 12/15/20	In 2021
Private companies	Fiscal years beginning after 12/15/20	Beginning after 12/15/21

*Public business entities

Early application is permitted by all entities for fiscal years beginning after December 15, 2018, including interim periods within those fiscal years. For loans and other financial assets carried at amortized cost, banks will recognize a cumulative-effect adjustment on their balance sheets as of the beginning of the first reporting period in which CECL is effective.

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