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Accounting

Auditing and AI: from binders to bots

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If you’ve been in the profession long enough, you probably remember the sound of a binder snapping shut at the end of an audit. Maybe you had shelves lined with thick audit manuals, filled with sticky notes and highlighter ink. Or maybe you were among the early adopters who swapped filing cabinets for digital folders and cheered when you could cram an entire client file into a computer.

Audit has always been a profession steeped in precision and consistency, but when it comes to how we manage knowledge, the tools haven’t always kept up.

That’s starting to change in a big way.

A problem shared is not halved

Today’s audit environment is more complex than ever. Regulatory changes move quickly, clients expect more transparency, and the volume of documentation required keeps growing. But many firms are still managing this complexity with tools that haven’t evolved much since the early 2000s.

Audit manuals, policies, and procedure documents are often voluminous and unwieldy, traditionally maintained as extensive Microsoft Word files. This fragmentation can result in difficulty for audit teams to confirm whether they are working with the most current version of a document.

This isn’t just inefficient. It’s risky. When guidance is hard to find, auditors may rely on memory, outdated files, or even internet searches. Teams are relying on informal processes to keep up to date with the latest changes to regulations and standards. In an environment where accuracy and consistency are everything, that’s a problem.

AI and the temptation of the instant answer

Meanwhile, artificial intelligence is knocking on the profession’s door. Tools like ChatGPT and other generative AI systems are being used in work daily. They’re fast, persuasive, and surprisingly capable at generating comprehensive responses.

But they’re not perfect. Ask ChatGPT how to audit cash disbursements, and it might give you a decent answer, or it might make something up that sounds right, but is in fact false information. That’s called a “hallucination,” and in audit, it can have crucial consequences.

Still, it’s easy to see the appeal. When you’re up against a deadline, digging through a 300-page manual is no one’s first choice. If a tool promises a shortcut, even a risky one, people will use it, whether authorized to or not. And firms are keen to capitalize on the technology, with a KPMG report revealing 4 out of 10 companies are already reporting greater employee productivity and efficiency.

So the question isn’t whether AI will be part of the audit toolkit. It’s how we can make sure it actually helps instead of making things worse.

The real shift: from documents to data

The key to accurate and more efficient AI is integrating knowledge graphs.  Knowledge graphs are machine-readable data representations that mimic human knowledge, and bridge the gap to a safer, more reliable GenAI. In accounting, knowledge graphs can model complex concepts (e.g., debits, credits, assets) so software can “understand” financial reports the way humans do. When a digital financial report has tagged the accounting concepts using a naming convention from a standard such as US GAAP/XBRL, a financial report becomes a truly machine-readable accounting object. This shift requires rethinking content management, from documents to data.

Furthermore, if that same naming convention is used in, for example, the tagging of external guidance materials such as FASB Codification, and the tagging of internal guidance such as audit manuals the knowledge graph automatically extends into all that material too. This strengthens AI’s capabilities by providing context that will help to produce better results via techniques such as RAG.

Some firms are beginning to rethink how audit knowledge is created, stored, and shared, not as static documents, but as structured, connected pieces of information. Instead of treating a manual as one long file, they’re breaking it into smaller, tagged components: procedures, policies, checklists, explanations. These can be reused, updated, and embedded directly into the tools auditors use every day.

A good analogy is the difference between having a printed map and using a GPS. The map is static. You must interpret it, cross-reference it, and hope it’s still current. The GPS, on the other hand, knows where you are, pulls in real-time data, and guides you step by step. That’s what audit content can become in a truly modern system.

Why it matters for the profession

This shift isn’t just about technology. It’s about strengthening trust in the audit process both for the auditors doing the work and the stakeholders relying on the results.

With a modular, data-driven approach, audit guidance becomes easier to maintain and faster to update. Changes to standards can be reflected instantly across all related materials. There’s a clear audit trail. Teams know they’re always working with the latest version. And when AI enters the picture, it’s working off a reliable foundation—not a patchwork of half-forgotten PDFs.

Even more importantly, this approach creates space for auditors to do what they’re trained to do: apply professional judgment. When guidance is clear, consistent, and easy to access less time is spent hunting for answers and more time is spent analyzing and advising.

Same role, new tech

It’s easy to forget how much the profession has already changed. At Propylon, we’ve worked with audit and accounting firms for over 25 years. We’ve gone from ticking boxes on paper to working in cloud-based platforms. From calculators to Excel. From literal files to digital ones.

But each of those shifts wasn’t just about efficiency; it was about unlocking new levels of insight and professionalism.

Today’s transformation is no different. As audit enters this next phase, the firms that thrive will be the ones who treat knowledge not as something to store, but as something to structure, connect, and use in smarter ways.

Audit has always been about getting the details right. But now, getting the process right may be just as important.

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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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