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Data shows there is room for both advisory and compliance for CPA firms

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2 years ago

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Accountants need not necessarily abandon compliance work for advisory, as recent data shows that the most successful firms maintain a robust presence in both areas. 

This is according to a report authored by professionals at the Center for Accounting Transformation, CPA Trendlines, Avalara and Brigham Young University, which is based on survey responses from 213 accountants at firms of varying size. What they found was that it is perfectly possible for a firm to be successful without necessarily specializing in advisory or, indeed, specializing at all. 

Practitioners were asked to rate, on a scale of 1-10, how successful they felt their firm was. They were also asked to rate their balance between compliance and advisory work, with 1 being “we do only compliance work” and 10 being “we do only advisory work.” They then looked at where the most successful firms stood on this compliance-advisory scale. 

What they found was that the most successful firms, while leaning slightly more towards advisory over compliance, generally maintained a good balance between the two. 

Advisory-Compliance-Chart1

Those who were “highly successful” were rated 5.67 in terms of their balance between compliance and advisory. This number goes down the less successful one’s firm is, but not dramatically so, indicating that while a less advisory-focused firm might not be as successful, the gap is not as large as one might initially think. 

Donny Shimamoto, the head of the Center for Accounting Transformation and one of the study’s authors, said what this shows is that firms can choose either advisory, compliance or some mix between the two. And, speaking from his own experience, the success of one can feed directly into the other. 

“For example, my firm is pure advisory and we have been around for over 20 years already. What we’ve found though is that we need to ensure that our clients have someone performing the compliance work for them well. Without the strong base in compliance—which provides the reliability of the numbers for analysis—our advisory work may not provide the right recommendations because we are basing them on flawed base information,” he said. 

A similar dynamic was observed when considering specialist versus generalist firms. Poll respondents were asked to rate, on a 1-10 scale, their degree of “vertical” specialization (the degree to which a firm focuses on a specific industry or sector, with 10 being they only work with clients in that area) and “horizontal” specialization (the degree to which a firm focuses on a specific service offering like R&D tax credits, with 10 being they only offer services in this particular area). What they found was that while both successful and highly successful firms, while possessing some degree of specialization, were not especially specialized in one area or another. However there does seem to be some benefit towards at least some specialization, as the unsuccessful firms were also the least specialized. 

Advisory-Compliance-Chart2

Still, this difference is not that great. Hyper-specialized firms on the vertical scale scored an average success rating of 8.11; firms that aren’t specialized at all, meanwhile, saw an average success rating of 7.5. There were similar results regarding horizontal specialization: the most specialized firms reported a success score of 8.45; the least specialized ones reported success scores of 7.61. While the differences are certainly relevant, the report noted they’re not especially dramatic. 

There was one area where specialization made a big difference, though, and that was in employee satisfaction. The data found that those who were at firms that would be considered specialized, either in terms of service offerings or industrial sector, tended to have happier people who would be more likely to recommend the firm as a good place to work. However, the data also showed there can be too much of a good thing, as those who were at hyper-specialized firms were less happy. 

“Hyper-specialized, I think, may be too narrowly focused and may not provide people with the variety of work that helps keep the work interesting. Many hyper-specialized also tend to be smaller firms, so there may also be challenges with the work environment and not as many people to spread the work among,” said Shimamoto. 

Still, he also recognized that even if firms don’t necessarily have to jump into advisory, many have already done so and more will likely do so in the future. Even if a firm can find success focusing mainly on compliance-related work, he said they will still not be able to ignore advisory completely, especially as automation of routine tasks becomes more common. 

“As compliance becomes more automated, I suspect we will see a trend toward about 20% compliance (that is highly automated) and then 80% advisory (that is automation-enabled). Firms that want to remain compliance-focused, will need to ensure that they are fully leveraging automation to keep that work sustainable. Or they will need to ensure they are partnering with an advisory-focused firm so that together they are coordinating the transformation for clients and its impacts on the compliance work,” he said. 

While intuitively one might consider profit to be the primary metric of success, the study said that firm leaders have different goals and priorities when it comes to their businesses and so also have different measures of what makes them successful. Profit is certainly a factor, but it is not the only one. So, when considering how successful they are, accounting firm leaders also considered: 

  • Continuous learning and improvement of people;
  • continuous improvement of processes; 
  • being ahead of other firms in technology usage;
  • being team-oriented versus individually-focused;
  • having a distinct culture and set of values that guides how a firm works and the decisions it makes;
  • exceeding client expectations; having a positive impact on client success;
  • growing faster than other similarly sized firms; and 
  • being able to operate successfully well into the future. 

“We also knew that profit should not be the only measure of success, especially in the accounting profession where money is not necessarily a primary motivator. Thus we chose indicators that might show that one firm is more successful than other firms,” said Shimamoto. 
Still, while profit is only one part of the equation, its impact can be quite material. But due to the hesitance of certain firms to share their specific profit figures, Shimamoto said it is difficult to pin down exactly what kinds of practices are more lucrative.

However, he said anecdotally he has heard advisory work and specialized work is generally more profitable because people can charge a premium for the knowledge. With his own firm, advisory work is much more profitable than the usual 30% rule of thumb that is used for professional services.

Accounting Today will be hosting a webcast on Oct. 31 to discuss the survey data in more detail. People can register here.

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Accounting

AI-Driven Automation and Continuous Accounting Frameworks

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1 week ago

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August 15, 2026

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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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2 weeks ago

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August 9, 2026

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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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3 weeks ago

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August 5, 2026

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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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