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Quality management standards: Time is running out!

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Has your firm started work on implementing the new quality management standards? If you haven’t already started, it may be challenging getting it done by the Dec. 15, 2025, deadline for having a quality management system in place. 

That may seem like a long way off, with plenty of time to update your existing quality control document. Many firms are underestimating the level of effort required, and seem to think that simply changing the wording from “document” to “system” will be sufficient. However, that just isn’t the case. 

What’s the difference between a QCD and a QMS?

The biggest — and most obvious — difference is that the QCD was a document while the QMS is a system. The defining point of QMS is the “S” for system. Your firm needs to develop a system to ensure that the output meets the standards of quality. 

The reality is that the quality control document often sat on a shelf to be dusted off every three years for peer review. When working with firms on their QMS, we start by talking through their QCD with leaders who are often surprised by the differences between what the document says the firm does versus what is actually happening at the firm. Trying to comply by switching the name from QCD to QMS and folding in a few things, like adding snippets about technology and IP resources to the human resources section of the QCD, simply won’t work. Your firm’s QMS must also include accountabilities and tracking measures that are lacking in a QCD.

Quality objectives in a QMS

The new standards require firms to establish quality objectives around each of eight components, which you can read about in the standard. Because every firm is different, this isn’t just a boilerplate document that can be slightly edited. Each firm’s objectives and the path to achieving those objectives will be different. 

At AccountAbility Plus, we recommend using the long-standing SMART approach to establishing quality objectives for each of the eight components.

  • Specific: Objectives are stated in clear and specific terms to ensure that every team member is on the same page. For example, “As a firm we will not do PCAOB A&A work.” 
  • Measurable: Objectives must be measurable. Has this objective been completed? How will feedback be assessed? What will be the standard for acceptable feedback?
  • Attainable: These objectives must also be attainable within the firm’s capacity, with adequate resources, competencies, and methodologies to ensure they can be achieved.
  • Relevant: Quality objectives must be relevant to the firm’s strategic goals. They must align with the quality standards of the profession and the firm and ensure that regulatory requirements are met.
  • Time-oriented: Each objective must also be time-oriented with a clear and unambiguous date for achievement. Firms must also determine the timing of responses to risks depending on the severity.

A firm risk assessment process in a QMS

In the old QCD standards, it wasn’t clear how you were supposed to respond when you had a quality issue. QCDs could also be vague about the timeframes for evaluating and responding to risks, using words such as “periodically” and “timely,” which are left up to interpretation of each person in the firm. 

In contrast, your firm’s QMS must be actionable and must include a risk assessment process to be implemented by your firm. This process is used to identify risk events that could occur based on the firm’s quality objectives, and must include a process for tracking and documenting when you have risk events. You also need to determine the specific timing of your response to risk events by carrying out a root cause analysis to determine the remediation plan.

For a minor risk event, like issuing financials with a typo, or a staff member being short of CPE, but they don’t do Yellow Book audits, you can likely bundle these risks and respond to them once or twice a year. 

However, if this staff person does governmental audits for which Yellow Book CPE is required, the response needs to be much quicker. You need to determine what went wrong in your system and fix it to ensure that team members don’t miss their Yellow Book CPE in the future. 

Severe risk events — like issuing the wrong opinion or finding out the firm is not independent after the report has been issued — will require immediate attention to gather facts, determine the impact, and develop a response. 

Root cause analysis and the ‘Five Whys’ approach

When a risk event occurs, you need to determine why it happened by doing a root cause analysis, then you need to remediate the problem. 

For example, let’s say you have to reissue a financial statement. Sometimes the reason for reissuance isn’t a big deal, such as a typo that doesn’t affect the numbers or the opinion or anything significant, but you still need to reissue the financials to correct the minor error. Since this is a minor risk, you would track how many times it happened and at least once a year perform a root cause analysis. 

To perform a root cause analysis, we teach firms to use the ‘Five Whys’ approach. You start by asking what happened, and then repeatedly ask why that happened. By the time you get to the fifth why, you should find the root cause for the problem. Using our example of the typo, you start by asking what happened. Why did this typo happen? Then you keep asking why until you get to the root cause. 

You also need to consider how pervasive each risk event is. If it only occurred once or twice during the year, you’ll want to make sure your proofing system is robust enough to minimize the risk of typos. However, it’s not worth spending a significant amount of time and money to absolutely eliminate all risk of typos. However, if you’re reissuing financials to fix typos dozens of times a year, then there’s clearly something wrong with your proofing process. Using the Five Whys method, you should be able to determine the root cause and figure out how to mitigate this from happening as often. 

On the other hand, if you need to reissue financials due to a material misstatement, this is clearly a more severe risk event. You’ll need to immediately perform the root cause analysis as to why it happened and determine next steps to remediate the issue.

This standard was designed to be scalable, and firms should take advantage of this to right-size their response to risk events.

Don’t delay — start now

Ideally, you have already started this time-consuming and mandatory process. Your firm needs to consider each of the eight components and determine quality objectives that are both SMART and reflective of your firm’s characteristics. 

Several of the firms that we’ve been working with over the last year will be ready to start piloting their new QMS early in 2025. They’ll have the chance to see what’s working and what’s not working so they can make any necessary adjustments before the effective date. 

For firms that are truly committed to quality, this is more of a cost burden than a value add, although it’s never a bad idea to make enhancements that will improve quality. You may find some process improvements along the way that improve more than just quality. 

Dec. 15, 2025, will be here sooner than you think — start today, not tomorrow. 

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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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