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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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Accounting

AI-Driven Automation and Continuous Accounting Frameworks

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The accounting profession is undergoing a fundamental structural transition as enterprise finance departments shift from periodic month-end closes toward automated continuous accounting models. By integrating specialized machine learning algorithms directly into enterprise resource planning (ERP) platforms, chief accounting officers are transforming financial reporting from a retrospective exercise into a real-time operational asset.

The Shift from Periodic Close to Continuous Financial Reporting
Traditional accounting workflows heavily relied on manual data reconciliation, spreadsheet calculations, and multi-week closing cycles at the end of each fiscal period. In contrast, continuous accounting frameworks utilize automated software agents to process, validate, and post transactional data in real time as business activities occur.

Automated bank reconciliation tools cross-reference incoming bank feeds, invoice records, and purchase orders automatically. By resolving transactional variances instantly throughout the month, corporate accounting teams eliminate the traditional workload spikes associated with quarterly and annual closes.

Machine Learning in Audit Trails and Anomaly Detection
Advanced natural language processing (NLP) and machine learning tools are redefining internal audit and financial control environments. Automated systems analyze 100% of general ledger entries, identifying anomalous transactions, duplicate payments, and unauthorized journal entries in real time.

Rather than relying on random statistical sampling, corporate internal auditors can focus their attention on high-risk flags automatically surfaced by algorithmic monitoring platforms. This continuous risk assessment strengthens internal controls over financial reporting (ICFR) and significantly reduces fraud risk.

Evolving Roles for Accounting Professionals
As routine data entry and manual reconciliation tasks become fully automated, the skill set required for accounting professionals is shifting toward data analysis, system design, and strategic business advisory.
– Systems Governance: Accountants are increasingly responsible for monitoring algorithmic accuracy and managing data integration pipelines.
– Business Partnership: Finance professionals leverage real-time financial dashboards to advise operational leaders on margin management and working capital allocation.
– Regulatory Compliance Management: Accounting teams utilize automated platforms to ensure compliance with dynamic tax codes and international accounting standards.

Core Implementation Recommendations
1. Deploy Automated Reconciliation Tools: Integrate continuous transaction processing modules into existing enterprise ERP architectures.
2. Establish Algorithmic Governance Controls: Implement strict internal testing protocols to ensure automated accounting rules comply with GAAP/IFRS standards.
3. Reskill Accounting Teams: Invest in training finance staff on data analytics, workflow automation, and predictive financial modeling.

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Accounting

Global ESG Reporting Standards and Double Materiality Compliance

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Corporate accounting departments face expanding reporting expectations as international sustainability disclosure standards achieve regulatory enforcement across major global jurisdictions. Chief Accounting Officers (CAOs) and corporate controllers are establishing rigorous internal accounting controls to treat Environmental, Social, and Governance (ESG) metrics with the same data precision, auditability, and governance as traditional financial statements.

Regulatory Harmonization Under Global Sustainability Frameworks
The implementation of standardized sustainability reporting frameworks—notably rules established by international sustainability accounting boards—has created unified expectations for public and large private enterprises. Corporations must report standardized metrics covering greenhouse gas emissions (Scope 1, 2, and material Scope 3), energy utilization, workforce demographics, and supply chain governance.

In Europe and other participating international jurisdictions, double materiality principles are mandatory. Under double materiality, organizations must report both how external sustainability risks impact corporate financial performance, and how internal corporate operations affect surrounding environmental and social structures.

Integrating Sustainability Metrics into Core ERP Systems
To provide auditable non-financial data, enterprise organizations are integrating specialized carbon accounting and ESG management platforms directly into core ERP systems. Automated data collectors capture energy utility invoices, logistics fuel consumption metrics, and vendor compliance records in real time.

Establishing automated, traceable data pipelines ensures that non-financial reporting is supported by clear audit trails. This structured approach allows external financial auditors to provide reasonable assurance on sustainability disclosures during annual corporate reporting cycles.

Financial Impacts and Capital Market Disclosure
Accurate ESG reporting directly influences corporate cost of capital and institutional credit ratings. Commercial lenders and institutional asset managers systematically incorporate sustainability metrics into risk pricing models. Companies that demonstrate transparent, verifiable progress in operational energy efficiency and climate risk mitigation benefit from expanded access to green bond markets and lower debt pricing.

Action Steps for Accounting Leadership
1. Implement Double Materiality Frameworks: Conduct comprehensive assessments to identify material financial and operational sustainability metrics.
2. Build Auditable Non-Financial Data Pipelines: Automate ESG data collection within core accounting software to ensure data integrity.
3. Align Sustainability with Annual Financial Filings: Prepare non-financial disclosures concurrently with financial statements to satisfy regulatory audit expectations.

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Accounting

Modernizing Internal Controls: Machine Learning and Continuous Monitoring in Auditing

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Internal audit departments and corporate risk managers are modernizing internal control frameworks by shifting from periodic sampling techniques to continuous monitoring and machine learning analytics. As operational data volumes increase across enterprise organizations, automated control testing ensures financial integrity, prevents corporate fraud, and streamlines annual audit engagements.

The Limitation of Periodic Audit Sampling
Historically, internal and external auditors evaluated internal controls by reviewing random samples of financial transactions—often analyzing less than five percent of total ledger entries. In complex enterprise environments, periodic sampling methods carry inherent risks of overlooking localized financial misstatements, unauthorized disbursements, or operational control breakdowns.

In 2026, progressive internal audit functions are utilizing automated continuous monitoring platforms that evaluate one hundred percent of financial transactions in real time. Continuous control auditing systems continuously monitor general ledger entries, procurement approvals, and expense reimbursements across all operating subsidiaries.

AI-Powered Fraud Detection and Anomaly Identification
Machine learning models trained on historical corporate financial data excel at identifying subtle transactional anomalies that indicate potential fraud or operational error. Automated systems instantly flag duplicate invoice payments, unapproved vendor creation, unusual journal entry timing, and unauthorized override of authority thresholds.

When an anomaly is detected, the automated auditing platform generates an instant risk alert, allowing internal audit teams to investigate root causes immediately. Early detection prevents minor operational errors from escalating into material weaknesses in financial reporting.

Streamlining External Audit Preparation
Continuous internal control monitoring delivers significant benefits during annual external financial audits. External audit firms can review continuous audit logs and automated control testing documentation, reducing the time required for manual field testing.

This integrated approach lowers overall audit compliance fees, reduces administrative burdens on corporate accounting staff, and provides senior management and audit committees with real-time visibility into the organization’s overall risk profile.

Core Implementation Guidelines
1. Transition to 100% Data Testing: Replace legacy sampling methods with automated continuous audit monitoring systems.
2. Deploy Anomaly Detection Algorithms: Implement machine learning models to identify unauthorized transactions and operational control overrides.
3. Align Internal and External Audit Workflows: Coordinate continuous control testing protocols with external auditors to optimize annual compliance cycles.

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