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Assessing credit losses in financial statement audits: A guide for auditors

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Credit losses represent a significant area of focus in financial statement audits. As economic conditions fluctuate and accounting standards evolve, auditors face increasing challenges in evaluating how organizations estimate and report credit losses, and in providing a comprehensive overview of credit loss assessment in financial statement audits. 

This article will explore the concept of credit losses, examine relevant regulatory frameworks, discuss vital challenges auditors encounter, and offer best practices for effectively auditing credit loss estimates. In addition, it will also describe key emerging trends and technologies shaping the future of credit loss auditing.

Credit losses occur when a borrower fails to repay a debt according to the initial agreement. These losses are typically reported as allowances for credit losses or loan loss provisions in financial statements. They represent the estimated amount of debt that may not be collected, reflecting the credit risk associated with a company’s financial assets.

For auditors, understanding how companies calculate and report credit losses is crucial. This process often involves complex estimates and judgments, as companies must forecast future economic conditions and borrower behavior. The shift toward more forward-looking models, such as the Current Expected Credit Loss model in the United States, has further increased the complexity of these estimates.

Auditors must evaluate whether these estimates are reasonable and supported by appropriate evidence, ensuring that financial statements accurately reflect the company’s credit risk exposure.

Regulatory framework and standards

Various standards and regulations govern the accounting for credit losses, which have undergone significant changes in recent years. In the United States, the Financial Accounting Standards Board introduced Accounting Standards Update 2016-13, which implemented the CECL model. Internationally, the International Accounting Standards Board has issued IFRS 9, which includes a similar expected credit loss model.

These standards require companies to recognize expected credit losses over the life of a financial asset rather than waiting for a loss event to occur. This forward-looking approach aims to provide financial statement users with more timely and relevant information about credit risk.

Auditors must stay current with these standards and any related interpretations or guidance issued by regulatory bodies. They must also understand how these standards apply to different types of financial assets and industries to effectively audit credit loss estimates.

Critical challenges in auditing credit losses

Auditing credit losses presents several challenges:

  • Complexity of models: Credit loss models often involve complex statistical techniques and numerous assumptions. Auditors must assess whether these models are appropriate and whether the assumptions used are reasonable.
  • Data quality and availability: The accuracy of credit loss estimates depends heavily on the quality and completeness of historical and current data. Auditors must evaluate the reliability of data sources and the processes used to collect and maintain this information.
  • Judgment and estimation uncertainty: Credit loss estimates involve significant judgment, particularly in forecasting future economic conditions. Auditors must evaluate the reasonableness of these judgments and ensure appropriate disclosure of estimation uncertainty.
  • Rapidly changing economic conditions: Economic volatility can quickly render historical data and assumptions obsolete. Auditors must consider how companies have incorporated recent economic trends and events into their estimates.
  • Internal controls: Assessing the effectiveness of internal controls over the credit loss estimation process is crucial but can be challenging due to the complexity and judgment involved.
  • Potential management bias: Given the subjective nature of credit loss estimates, there’s a risk of management bias. Auditors must remain skeptical and alert to potential manipulations of these estimates.

Best practices for auditors 

To effectively audit credit losses, auditors should consider the following best practices:

  • Develop a thorough understanding: Gain in-depth knowledge of the company’s business model, credit risk management practices and the specific credit loss estimation methodology.
  • Assess model appropriateness: Evaluate whether the credit loss model aligns with accounting standards and suits the company’s specific circumstances. When dealing with complex models, consider involving specialists.
  • Test key assumptions: Critically evaluate the reasonableness of key assumptions used in the credit loss model. This may involve comparing assumptions to industry benchmarks, historical data, and economic forecasts from reliable sources.
  • Perform sensitivity analyses: Assess how changes in key assumptions impact the credit loss estimate to understand the model’s sensitivity and identify potential areas of concern.
  • Evaluate data integrity: Test the completeness and accuracy of data used in the credit loss model. This includes both historical data and current information used to inform forward-looking estimates.
  • Review disclosures: Ensure financial statement disclosures adequately explain the credit loss estimation process, key assumptions and areas of uncertainty.
  • Assess internal controls: Thoroughly evaluate internal controls’ design and operating effectiveness over the credit loss estimation process.
  • Consider management bias: When selecting assumptions or data used in the estimation process, remain alert to potential indicators of management bias.
  • Document thoroughly: Maintain clear and comprehensive documentation of audit procedures performed, evidence obtained, and conclusions regarding credit loss estimates’ reasonableness.
  • Stay updated: Continuously monitor changes in accounting standards, regulatory guidance, and industry practices related to credit loss estimation and auditing.

Emerging trends and technologies

The field of credit loss auditing is evolving rapidly, driven by technological advancements and changing regulatory landscapes. Emerging trends include:

  • Increased use of artificial intelligence and machine learning in credit loss modeling;
  • Greater emphasis on real-time data analysis and continuous auditing techniques;
  • Enhanced data analytics tools for identifying patterns and anomalies in large datasets;
  • Growing focus on climate-related risks and their potential impact on credit losses; and,
  • Increased regulatory scrutiny of credit loss estimates, particularly during economic uncertainty.

The impact of AI on auditing credit losses

Artificial intelligence is revolutionizing how credit losses are estimated and audited. Its ability to quickly process vast amounts of data and identify complex patterns is particularly valuable in this field. 

Here are some key areas where AI is making a significant impact:

1. Enhanced pattern recognition. AI algorithms can analyze historical data to identify subtle patterns indicating increased credit risk. For example, an AI system might detect that customers who make frequent small purchases followed by large purchases are more likely to default. This pattern might need to be more nuanced for traditional analysis methods to catch.

Example: An auditor reviewing a bank’s credit loss estimates could use AI to analyze the transaction patterns of thousands of credit card holders. The AI might identify a correlation between certain spending behaviors and the likelihood of default that the bank’s model hasn’t accounted for, prompting the auditor to question the completeness of the bank’s risk assessment.

2. Improved forecasting. AI models can incorporate a broader range of variables and data sources to improve the accuracy of credit loss forecasts. This includes nontraditional data such as social media posts, online behavior, or macroeconomic indicators.

Example: When auditing a mortgage lender’s expected credit losses, an AI system could analyze not just traditional factors like credit scores and income but also incorporate data on local real estate trends, employment statistics, and even climate change projections for coastal properties. The auditor could assess whether the lender’s forecasting model is sufficiently comprehensive.

3. Real-time risk assessment. AI systems can continuously update risk assessments as new data becomes available, allowing for more dynamic credit loss estimates.

Example: An auditor reviewing a company’s accounts receivable might use an AI tool that continuously monitors customer payment behaviors, news about customer companies, and industry trends. This could help the auditor assess whether the company’s credit loss allowances are updated frequently enough to reflect current risks.

4. Anomaly detection. AI can quickly identify unusual patterns or transactions that might indicate errors in credit loss calculations or potential fraud.

Example: When auditing an extensive portfolio of loans, an AI system could flag individual loans or groups with risk characteristics that don’t align with their assigned risk ratings. This could help auditors focus on areas where the credit loss estimates might need to be more accurate.

5. Automation of routine tasks. AI can automate many routine aspects of auditing credit losses, such as data gathering, reconciliations, and basic calculations. This allows auditors to focus more on complex judgments and risk assessments.

Example: An AI system could automatically gather loan data, calculate expected loss rates based on historical performance, and compare these to the client’s estimates. The auditor could then focus on evaluating the reasonableness of any differences and assessing the qualitative factors that might justify them.

6. Enhanced scenario analysis. AI can rapidly run multiple complex economic scenarios to stress-test credit loss models, providing auditors with a more comprehensive view of potential risks.

Example: When auditing a bank’s loan loss provisions, an AI system could quickly generate and analyze hundreds of potential economic scenarios, considering factors like interest rates, unemployment and GDP growth. This could help the auditor assess whether the bank’s scenario analysis is sufficiently robust and comprehensive.

While AI offers significant benefits, it’s important to note that it also introduces new challenges for auditors. These include ensuring the reliability and appropriateness of AI models, understanding the “black box” nature of some AI algorithms, and maintaining professional skepticism when working with AI-generated insights. Auditors must develop new skills to effectively leverage AI tools while still applying their professional judgment to the audit process.

Auditors should stay informed about these trends and consider how they might impact their audit approaches and methodologies.

Final word

Auditing credit losses remains a complex and challenging task. By staying informed, applying best practices, and leveraging emerging technologies, auditors can enhance the effectiveness and efficiency of their work, ultimately contributing to the reliability and transparency of financial reporting.

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Accounting

Tax Fraud Blotter: Big plans

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What becomes of the broken-hearted; the earth moved; Kreative accounting; and other highlights of recent tax cases.

Providence, Rhode Island: Four Florida residents have been convicted and sentenced for what authorities called one of the largest schemes to defraud CARES Act programs.

The defendants defrauded various federally funded programs of more than $4.8 million, and each of the defendants pleaded guilty to charges of conspiracy to commit wire fraud and aggravated identity theft. The schemes involved obtaining and using stolen ID information to submit fraudulent applications to multiple state unemployment agencies, including the Rhode Island Department of Labor and Training, and to submit fraudulent Economic Injury Disaster Loans and Paycheck Protection Program loan applications. The defendants also submitted fraudulent applications in the names of other persons to federal and state agencies to obtain tax refunds, stimulus payments, and disaster relief funds and loans.

The scheme involved using the stolen information to open bank accounts to receive, deposit and transfer fraudulently obtained government benefits and payments and to obtain debit cards to withdraw the money.

Sentenced were Florida residents Tony Mertile, of Miramar, identified in court documents as the leader of the conspiracy, to six years in prison; Junior Mertile, of Pembroke Pines, sentenced to 54 months; Allen Bien-Aime, of Lehigh Acres, to four years; and James Legerme, of Sunrise, to four years. All four were also sentenced to three years of supervised release to follow their prison terms.

The government moved to forfeit a total of $4,857,191, or $1,214,294.75 apiece, proceeds of the conspiracy. The defendants have also forfeited hundreds of thousands of dollars’ worth of Rolex watches and assorted jewelry and more than $1.1 million in cash. Each defendant is also liable for $4,456,927.36 in restitution to defrauded agencies and financial intuitions.

Raleigh, North Carolina: Michon Griffin, 46, who engaged as a money mule (a.k.a. middleman) in an international romance scheme, has been sentenced to two years in prison and three years of supervised release after pleading guilty to conspiracy to commit money laundering and to making false statements on her 1040.

Between 2021 to 2023, Griffin received more than $2 million from the scheme that she deposited into fictitious bank accounts that she controlled. She converted the money to virtual currency and wired the funds to overseas accounts controlled by her co-conspirators in Nigeria.

Griffin received some $300,000 from the romance fraud, which she did not report as income on her 1040 for 2021.

She was also ordered to pay $109,119 in restitution to the IRS.

Las Vegas: Tax preparer Keisy Altagracia Sosa has pleaded guilty to preparing false income tax returns.

Sosa has operated the tax prep business National Tax Service, and from 2016 to 2021 prepared and filed false federal returns for clients. These returns included falsely claimed dependents, and fictitious Schedule A and Schedule C expenses such as sales taxes paid and unreimbursed employee expenses.

Sosa continued to prepare false returns even after the IRS notified her that her returns appeared inaccurate and informed her that she may not be meeting due diligence requirements. 

Sosa caused at least $550,000 in tax loss to the IRS.

Sentencing is June 11. She faces up to three years in prison, as well as a period of supervised release and monetary penalties. 

Hands-in-jail-Blotter

Elk Mound, Wisconsin: Business owner Deena M. Hintz, of Eau Claire, Wisconsin, has been sentenced to a year in prison for failure to pay employment taxes.

Hintz, who pleaded guilty in December, owned and operated Jade Excavation and Trucking for nearly 10 years and at times had up to 15 employees. From 2017 to 2021, Hintz deducted more than $400,000 in federal employment taxes from employees’ pay and, instead of paying those taxes to the government, kept the money.

She was also ordered to pay $482,185.46 in restitution.

Littleton, Colorado: Tax preparer Thuan Bui, 60, has been sentenced to three years in prison and a year of supervised release and ordered to pay a $50,000 fine after pleading guilty to one count of aiding or assisting in preparation of false documents.

From about 2016 to 2021, Bui operated a tax prep business under several names, lying to clients that he was a CPA. On hundreds of returns, Bui overstated or fabricated expenses on Schedules C.

Philadelphia: Resident Joseph LaForte has been sentenced to 15 and a half years in prison for defrauding investors, conspiring to defraud the IRS, filing false tax returns, employment tax fraud, wire fraud, obstruction and other charges.

LaForte defrauded investors using a fraudulent investment vehicle known as Par Funding. Along with conspirators, he caused a loss to investors of more than $288 million.

He and conspirators diverted some $20 million in taxable income from Par Funding to another entity controlled by LaForte and nominally owned by another, then filed returns that did not report this income; he also received more than $9 million in kickbacks from a customer of Par Funding and did not report this income to the IRS. He paid off-the-books, cash wages to some employees, failing to report these wages to the IRS and not paying employment taxes.

The federal tax loss exceeds $8 million. He also caused $1.6 million in state tax loss to the Pennsylvania Department of Revenue by falsely reporting that he and his wife were residents of Florida from 2013 through 2019 when they lived in Pennsylvania.

Hampton Roads, Virginia: Two area residents have pleaded guilty to their roles in a refund scheme involving pandemic relief credits.

Between October 2022 and May 2023, Kendra Michelle Eley of Norfolk, Virginia, filed eight 941s for Kreative Designs by Kendra LLC using the EIN assigned to another company, Kendra Cleans Maid Service. These forms covered four tax periods in 2020 and four in 2021. On each of the forms, Eley falsely reported wages paid and federal tax withholdings for 18 purported employees, knowing there were no such employees.

For the four forms filed for 2021, Eley claimed false sick and family leave credits and Employee Retention Credits, totaling some $975,000. In December 2022, the IRS issued two refund checks payable to the cleaning company totaling $649,050.

That same month, Eley and Rejohn Isaiah Whitehead, of Portsmouth, Virginia, opened a business checking account in the name of Kendra Cleans; signatories on the account were Eley and Whitehead. The two falsely represented the nature and extent of the business, including that it had 16 employees and that the average pay of each was $2,000. Eley funded the account by depositing one of the refund checks in the amount of $389,640. In January 2023, Eley wrote Whitehead two checks from the account totaling $60,000.

Whitehead’s sentencing is June 26 and Eley’s is July 9. They each face up to 10 years in prison.

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Accountants tackle tariff increases after ‘Liberation Day’

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President Trump’s imposition of steep tariffs on countries around the world is likely to drive demand for accounting experts and consultants to help companies adjust and forecast the ever-changing percentages and terms.

On April 2, which Trump dubbed “Liberation Day,” he announced a raft of reciprocal tariffs of varying percentages on trading partners across the globe and signed an executive order to put the import taxes into effect. Finance executives have been gaming out how to respond to the potential tariffs that Trump has been threatening to impose since before he was re-elected, far exceeding those he actually levied during his first term.

“A lot of CFOs are thinking they are going to pass along the tariffs to their customer base, and about another half are thinking we’re going to absorb it and be more creative in other ways we can save money inside our company,” said Tom Hood, executive vice president for business engagement and growth at the AICPA & CIMA. 

The AICPA & CIMA’s most recent quarterly economic outlook survey in early March polled a group of business executives who are also CPAs and found that 85% said tariffs were creating uncertainty in their business plans, while 14% of the business execs saw potential positive impacts for their business from the prospect of tariffs as increased cost of competing products would benefit them, and 59% saw potential negative impacts to their businesses from the prospect of tariffs. This in turn has led to a dimming outlook on the economy among the executives polled.

“CFOs in our community are telling us that, effectively, they’re looking at this a lot like what happened over COVID with a big disruption out of nowhere,” said Hood. “This one, they could see it coming. But the point is they had to immediately pivot into forecasting and projection with basically forward-looking financial analysis to help their companies, CEOs, etc., plan for what could be coming next. This is true for firms who are advising clients. They might be hired to do the planning in an outsourced way, if the company doesn’t have the finance talent inside to do that.”

The tariffs are not set in stone, and other countries are likely to continue to negotiate them with the U.S., as Canada and Mexico have been doing in recent months.

“The one thing that I think we can all count on is a certain amount of uncertainty in this process, at least for the next several months,” said Charles Clevenger, a principal at UHY Consulting who specializes in supply chain and procurement strategy. “It’s hard to tell if it’s going to go beyond that or not, but it certainly feels that way.”

Accountants will need to make sure their companies and clients stay compliant with whatever conditions are imposed by the U.S. and its trading partners. “This is a more complex tariff environment than most companies have experienced in the past, or that seems to be where we’re headed, and so ensuring compliance is really important,” said Clevenger.

Big Four firms are advising caution among their clients.

“Our point of view is we’re advising all of our clients to do a few things right out of the gate,” said Martin Fiore, EY Americas deputy vice chair of tax, during a webinar Thursday. “Model and analyze the trade flows. Look at your supply chain structures. Understand those and execute scenario planning on supply chain structures that could evolve in new environments. That is really important: the ability for companies to address the questions they’re getting from their C-suite, from their stakeholders, is critical. Every company is in a different spot according to the discussions we’ve had. We just are really emphasizing, with all the uncertainty, know your structure, know your position, have modeling put in place, so as we go through the next rounds of discussions over many months, you have an understanding of your structure.”

Scenario planning will be especially important amid all the unpredictability for companies large and small. “They’re going to be looking at all the different countries they might have supply chains in,” said Hood. “And then even the smaller midsized companies that might not be big, giant global companies, they might be supplying things to a big global company, and if they’re in part of that supply chain, they’ll be impacted through this whole cycle as well.”

Accountants will have to factor the extra tariffs and import taxes into their costs and help their clients decide whether to pass on the costs to customers, while also keeping an eye out for pricing among their competitors and suppliers.

“It’s just like accounting for any goods that you’re purchasing,” said Hood. “They often have tariffs and taxes built into them at different levels. I think the difference is these could be bigger and they could be more uncertain, because we’re not even sure they’re going to stick until you see the response by the other countries and the way this is absorbed through the market. I think we’re going through this period of deeper uncertainty. Even though they’re announced, we know that the administration has a tendency to negotiate, so I’m sure we’re going to see this thing evolve, probably in the next 30 days or whatever. The other thing our CFOs are reminding us of is that the stock market is not the economy.”

Amid the market fluctuations, companies and their accountants will need to watch closely as the rules and tariff rates fluctuate and ensure they are complying with the trading rules. “Do we have country of origin specified properly?” said Clevenger. “Are we completing the right paperwork? When there are questions, are we being responsive? Are we close to our broker? Are we monitoring our customs entries and all the basic things that we need to do? That’s more important now than it has been in the past because of this increase in complexity.”

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How to use opportunity zone tax credits in the ‘Heartland’

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A tax credit for investments in low-income areas could spur long-term job creation in overlooked parts of the country — with the right changes to its rules, according to a new book.

The capital gains deferral and exclusions available through the “opportunity zones” credit represent one of the few areas of the Tax Cuts and Jobs Act of 2017 that drew support from both Republicans and Democrats. The impact of the credit, though, has proven murky in terms of boosting jobs and economic growth in the roughly 7,800 Census tracts qualifying based on their rates of poverty or median family incomes. 

Altering the criteria to focus the investments on “less traditional real estate and more innovation infrastructure” and ensuring they reach more places outside of New York and California could “refine the where and the what” of the credit, said Nicholas Lalla, the author of “Reinventing the Heartland: How One City’s Inclusive Approach to Innovation and Growth Can Revive the American Dream” (Harper Horizon). A senior fellow at an economic think tank called Heartland Forward and the founder of Tulsa Innovation Labs, Lalla launched the book last month. For financial advisors and their clients, the key takeaway from the book stems from “taking a civic minded view of investment” in untapped markets across the country, he said in an interview.

“I don’t want to sound naive. I know that investors leveraging opportunity zones want to make money and reduce their tax liability, but I would encourage them to do a few additional things,” Lalla said. “There are communities that need investment, that need regional and national partners to support them, and their participation can pay dividends.”

READ MORE: Unlock opportunities for tax incentives in opportunity zones

A call to action

In the book, Lalla writes about how the Innovation Labs received $200 million in fundraising through public and private investments for projects like a startup unmanned aerial vehicle testing site in the Osage Nation called the Skyway36 Droneport and Technology Innovation Center. Such collaborations carry special relevance in an area like Tulsa, Oklahoma, which has a history marked by the wealth ramifications of the Tulsa Race Massacre of 1921 and the government’s forced relocation of Native American tribes in the Trail of Tears, Lalla notes.

“This book is a call to action for the United States to address one of society’s defining challenges: expanding opportunity by harnessing the tech industry and ensuring gains spread across demographics and geographies,” he writes. “The middle matters, the center must hold, and Heartland cities need to reinvent themselves to thrive in the innovation age. That enormous project starts at the local level, through place-based economic development, which can make an impact far faster than changing the patterns of financial markets or corporate behavior. And inclusive growth in tech must start with the reinvention of Heartland cities. That requires cities — civic ecosystems, not merely municipal governments — to undertake two changes in parallel. The first is transitioning their legacy economies to tech-based ones, and the second is shifting from a growth mindset to an inclusive-growth mindset. To accomplish both admittedly ambitious endeavors, cities must challenge local economic development orthodoxy and readjust their entire civic ecosystems for this generational project.”

READ MORE: Relief granted to opportunity zone investors

Researching the shortcomings

And that’s where an “opportunity zones 2.0” program could play an important role in supporting local tech startups, turning midsized cities into innovation engines and collaborating with philanthropic organizations or the federal, state and local governments, according to Lalla. 

In the first three years of the credit alone, investors poured $48 billion in assets into the “qualified opportunity funds” that get the deferral and exclusions for certain capital gains, according to a 2023 study by the Treasury Department. However, those assets flowed disproportionately to large metropolitan areas: Almost 86% of the designated Census tracts were in cities, and 95% of the ones receiving investments were in a sizable metropolis. 

Other research suggested that opportunity-zone investments in metropolitan areas generated a 3% to 4.5% jump in employment, compared to a flat rate in rural places, according to an analysis by the nonpartisan, nonprofit Tax Foundation.

“It creates a strong incentive for taxpayers to make investments that will appreciate greatly in market value,” Tax Foundation President Emeritus Scott Hodge wrote in the analysis, “Opportunity Zones ‘Make a Good Return Greater,’ but Not for Poor Residents” shortly after the Treasury study. 

“This may be the fatal flaw in opportunity zones,” he wrote. “It explains why most of the investments have been in real estate — which tends to appreciate faster than other investments — and in Census tracts that were already improving before being designated as opportunity zones.”

So far, three other research studies have concluded that the investments made little to no impact on commercial development, no clear marks on housing prices, employment and business formation and a notable boost in multifamily and other residential property, according to a presentation last September at a Brookings Institution event by Naomi Feldman, an associate professor of economics at the Hebrew University of Jerusalem who has studied opportunity zones. 

The credit “deviates a lot from previous policies” that were much more prescriptive, Feldman said.

“It didn’t want the government to have a lot of oversay over what was going on, where the investment was going, the type of investments and things like that,” she said. “It offered uncapped tax incentives for private individual investors to invest unrealized capital gains. So this was the big innovation of OZs. It was taking the stock of unrealized capital gains that wealthy individuals, or even less wealthy individuals, had sitting, and they could roll it over into these funds that could then be invested in these opportunity zones. And there were a lot of tax breaks that came with that.”

READ MORE: 3 oil and gas investments that bring big tax savings

A ‘place-based’ strategy

The shifts that Lalla is calling for in the policy “could either be narrowing criteria for what qualifies as an opportunity zone or creating force multipliers that further incentivize investments in more places,” he said. In other words, investors may consider ideas for, say, semiconductor plants, workforce training facilities or data centers across the Midwest and in rural areas throughout the country rather than trying to build more luxury residential properties in New York and Los Angeles.

While President Donald Trump has certainly favored that type of economic development over his career in real estate, entertainment and politics, those properties could tap into other tax incentives. And a refreshed approach to opportunity zones could speak to the “real innovation and talent potential in midsized cities throughout the Heartland,” enabling a policy that experts like Lalla describe as “place-based,” he said. With any policies that mention the words “diversity, equity and inclusion” in the slightest under threat during the second Trump administration, that location-based lens to inclusion remains an area of bipartisan agreement, according to Lalla.

“We can’t have cities across the country isolated from tech and innovation,” he said. “When you take a geographic lens to economic inclusion, to economic mobility, to economic prosperity, you are including communities like Tulsa, Oklahoma. You’re including communities throughout Appalachia, throughout the Midwest that have been isolated over the past 20 years.”

READ MORE: Can ESG come back from the dead?

Hope for the future?

In the book, Lalla compares the similar goals of opportunity zones to those of earlier policies under President Joe Biden’s administration like the Inflation Reduction Act, the CHIPS and Science Act, the American Rescue Plan and the Infrastructure Investment and Jobs Act.

“Together, these bills provided hundreds of millions of dollars in grant money for a more diverse group of cities and regions to invest in innovation infrastructure and ecosystems,” Lalla writes. “Although it will take years for these investments to bear fruit, they mark an encouraging change in federal economic development policy. I am cautiously optimistic that the incoming Trump administration will continue this trend, which has disproportionately helped the Heartland. For example, Trump’s opportunity zone program in his first term, which offered tax incentives to invest in distressed parts of the country, should be adapted and scaled to support innovation ecosystems in the Heartland. For the first time in generations, the government is taking a place-based approach to economic development, intentionally seeking to fund projects in communities historically disconnected from the nation’s innovation system and in essential industries. They’re doing so through a decidedly regional approach.”

Advisors and clients thinking together about aligning investment portfolios to their principles and local economies can get involved with those efforts — regardless of their political views, Lalla said.

“This really is a bipartisan issue. Opportunity zones won wide bipartisan approval,” he said. “Heartland cities can flourish and can do so in a complicated political environment.”

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