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Data strategy needs data governance

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Ultimately, it all comes down to data. This is according to Chris Millet, a Baker Tilly director specializing in client engagement and managed services during a talk Thursday at the Finance and Accounting Technology Expo in New York City. While there are powerful technology solutions available to professionals today, especially AI-based ones, none will perform their best without strong data sources paired with a robust governance framework. This not only avoids risk but drives the organization’s strategic goals going forward. 

“We should be looking at our data as a strategic asset. It really allows us to transform our data into a competitive advantage for our organization, and really bring it into alignment with our overall business goals and strategy, and make sure that we’re looking at that data quality and governance, and really unlock that potential in a robust way,” he said. 

He emphasized the importance of centralizing disparate data sources as policy, as he believes it is only when we are able to look at all the data together that we are able to understand the full picture of what is happening in an organization. When information is stored across separate silos that don’t connect or communicate, it becomes difficult to trust the system, as there is no single source of truth. 

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“[If] none of my systems talk to each other, I can’t really understand what’s happening in this system versus what I am trying to accomplish overall and understanding my data. What is that single source of truth that I can really trust?” he said. 

Of course, even if one does manage to centralize one’s data sources, it does no good if the data itself is suspect. This is where governance comes in, and he said there are numerous solutions available to help. Regardless of which ones someone chooses, he said they should be able to automatically point out where data hygiene is less than perfect. 

“[It] can say, hey, you’ve got this many transactions that are missing this data point. You’ve got this many records that don’t have this piece of information that’s critical to your analysis. And so your tool should highlight those things and be able to direct you to where you need to fix your data, because it doesn’t matter what comes out on your dashboards or reports or AI [if it is] garbage in, garbage out,” he said. 

While there are many ways to approach data governance, the very first step should be defining data ownership, according to Millet. Ask who owns the data from what sources. Does the warehouse team own the operations data? Does the finance team own the finance data? Does the sales team own the customer relationship data? Who actually owns the governance around the data that’s going to be consumed down the line? This also includes defining which users have access to which data sets, not just the inputs and outputs. This gives a true sense of both where the data is coming from and who is consuming it. 

He also talked about how, regardless of what solutions are deployed, they should also highlight compliance gaps. 

“And I’m not just talking about external compliance needs. You have third parties out there that may have certain requirements of you around your data, but I’m talking just as much or more about your internal compliance to go along with your internal data strategies and policies, and then lastly, enhancing the data integrity. When we understand there might be something wrong, [we can] go ahead and improve that and iterate over time so the more I can use my tools to help me identify the exceptions to my rules, the better and better I should get, and the more I can trust that data long term,” he said. 

Millet added that organizations should make sure their data strategies and tools will scale as the organization grows. 

“We must be able to grow. This is not something we’re going to implement today, and then two years later, we’ve got to rip [it] out and do something else. It should be something that I can grow with over time, and be able to spread across multiple business systems,” he said. 

Finally, he stressed the importance of stakeholder engagement. Implementing the most sophisticated, powerful solutions will mean nothing if employees won’t use it. 

“If [you’ve ever switched] to a new system, whether it’s NetSuite or another system, we’ve probably all heard, ‘I don’t know what’s happening here, the reports aren’t right.’ Whatever the situation is, stakeholder engagement can only be there if they’re trusting what they’re seeing, and that the data strategy addresses that,” he said. 

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Accounting

SEC’s Semiannual Reporting Proposal Faces Investor Pushback: What CFOs Need to Know

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U.S. Securities and Exchange Commission (SEC)

A proposal from the U.S. Securities and Exchange Commission to potentially shift some public companies away from quarterly financial reporting toward a semiannual model is drawing significant pushback from investors, even as it continues moving through the regulatory process. The debate has direct implications for corporate finance teams, auditors, and the broader transparency of U.S. capital markets.

What the SEC Proposed

According to a summary published by accounting advisory firm Cohen & Co., the SEC issued a proposed rule on May 19, 2026, aimed at simplifying financial reporting requirements for many U.S. public companies. The proposal would potentially reduce the frequency of certain mandatory disclosures from quarterly to semiannual, a structural change that has not been made to core U.S. reporting requirements in decades.

The proposal follows an extended debate within U.S. policy circles, with proponents arguing that reduced reporting frequency could lower compliance costs and free up management time for longer-term strategic planning rather than quarter-to-quarter results management.

Why Investors Are Pushing Back

Comment letters submitted in response to the proposal have been extensive, and according to Cohen & Co.’s review of the public record, investors “appear to be largely opposed” to the shift, viewing frequent interim reporting as a core benefit of U.S. capital markets relative to other jurisdictions.

Accounting and law firms have taken a more measured position, generally urging any changes to remain aligned with the Financial Accounting Standards Board (FASB), whose existing disclosure requirements and guidance are built around a quarterly reporting cadence. A shift to semiannual reporting without corresponding changes to FASB guidance could create friction between SEC filing requirements and GAAP-based disclosure expectations.

Lessons From the U.K. Experience

The debate is not without precedent. The United Kingdom moved away from mandatory quarterly reporting for listed companies in 2014, returning to a semiannual disclosure requirement. According to Cohen & Co.’s analysis, that experience offers a cautionary data point: there was no measurable increase in capital expenditure or R&D investment following the change, while analyst coverage of affected companies declined as reliable interim information became less available — a particular risk for smaller and newly public companies that rely on analyst coverage to maintain investor visibility.

Practical Implications for Finance Teams

Beyond the debate over disclosure philosophy, the proposal carries practical complications. Many companies have debt covenants and credit agreements structured around quarterly financial delivery; a shift to semiannual reporting could require renegotiating those terms. Reduced reporting frequency would also extend the “window of market silence” between disclosures, a factor that governance and investor-relations teams would need to manage carefully to avoid information asymmetry.

Separately, and unrelated to the reporting-frequency debate, the SEC and FASB have continued finalizing more routine updates this year. New Accounting Standards Updates are taking effect for December 31, 2026, fiscal year-ends covering income tax disclosures, credit loss measurement, induced debt conversions, and stock compensation, according to Eide Bailly’s review of 2026 ASU activity. Additional guidance on paid-in-kind dividends and environmental credits is also on the near-term horizon.

What to Watch Next

The semiannual reporting proposal remains in the comment and review phase, and no final rule has been adopted as of this writing. Finance leaders should monitor the SEC’s regulatory agenda for further movement, while treating the current quarterly reporting requirement as the operative standard until any final rule is issued and an effective date is set.

Given the extent of investor opposition documented in the comment file, a full shift to mandatory semiannual reporting appears more likely to result in either a scaled-back compromise or continued study rather than swift adoption — though the SEC’s ultimate direction remains uncertain.

 

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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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