Connect with us

Accounting

AI skepticism grows among compliance professionals

Published

on

Compliance professionals working to prevent financial crimes are losing their faith in AI to solve more problems than it causes, as recent survey data has found a significant drop in those saying the technology has positively impacted their programs between 2023 and 2024. 

This is one of the findings of a survey issued by financial and risk management solutions provider Kroll in its most recent Financial Crime Report. The report found that, as adoption of AI and machine learning advances, only 20% of respondents now exploring these tools report a “very positive impact” on their financial crime compliance frameworks. In contrast, the 2023 survey found 37% said the same thing. Dan Rice, managing director of cyber risk at Kroll, said that professionals found that the current set of solutions simply was not up to the task required of them. 

“A lot of promises were made in 2023, and have not come to pass. The short answer is that AI was never going to solve the problems it was sold to solve. Many financial institutions and large companies have data problems, and if the data isn’t great, the AI tends not to work well. There were many leaps in logic that suggested AI would fix the data problems and, consequently, many of our other problems. However, that’s not the case and won’t be the case. There’s still a lot of hard work below the surface needed to get this right. Many companies rushed into implementation of AI without proper planning, and now the focus is on developing the right strategy, governance and documentation to ensure compliance,” he said in an email.

At the same time, 71% of respondents expect financial crime risks to increase this year, yet only 23% believe their organization’s compliance program is “very effective.” This is at least partially due to lack of technology investment, as only 30% say their organization’s financial crime compliance program is sufficient in these respects, or weak governance, as only 29% strongly agree that their organization has a robust governance infrastructure for overseeing financial crime. 

AI plays a large role in this perception of risk, as 61% cited the increased use of AI by criminals as a leading catalyst for risk exposure in the coming year, outdone only by general cybersecurity risks at 68% (which also is increasingly driven by AI). Overall, there seems to be a divide in whether AI ultimately is more boon or burden. While 57% believe AI developments will benefit their financial crime compliance programs, while 49% agree AI poses a significant risk to compliance. 

The drop in those who say AI has made a very positive impact stands in contrast to other surveys which show AI enthusiasm growing generally. For instance, a recent survey from practice management solutions provider Karbon showed that the proportion of those excited about AI went from 41% to 63% for firm owners and 26% to 40% among individual contributors and staff in technology, operations and administrative positions. Meanwhile, a report from Wolters Kluwer shows rising AI implementations, growing 34% in just one year. And late last year, an EY poll found AI trust doing a 180, going from 85% saying generative AI will not drive increased effectiveness and efficiency over the next three years in 2023, to 87% saying it will just one year later. 

This difference could come down to who was polled. Kroll surveyed 600+ worldwide respondents that included CEOs, chief compliance officers, general counsel, chief risk officers and other financial crime compliance professionals. Half work in the financial services industry and the remainder are from other regulated industries, including accountancy, insurance, real estate, and legal services. Poll respondents came from the U.S. and UK, Western Europe (France, Germany, Ireland, Italy, Spain and Switzerland), Scandinavia (Norway and Sweden), Asia Pacific (Australia, India and Japan), Hong Kong, Singapore and the Middle East/Africa (United Arab Emirates and South Africa), as well as offshore financial centers—the British Virgin Islands, Cayman Islands and Jersey. 

Continue Reading

Accounting

Global ESG Reporting Standards and Double Materiality Compliance

Published

on

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.

Continue Reading

Accounting

Modernizing Internal Controls: Machine Learning and Continuous Monitoring in Auditing

Published

on

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.

Continue Reading

Accounting

Automated Tax Compliance and Global Regulatory Harmonization in 2026

Published

on

Corporate tax accounting departments are navigating an era of unprecedented regulatory complexity as global tax harmonization frameworks take full effect alongside real-time digital tax reporting mandates. Tax directors and accounting teams are adopting cloud-based tax compliance automation tools to manage multi-jurisdictional tax liabilities and satisfy stringent reporting rules across international jurisdictions.

Implementation of Global Minimum Tax Provisions
The implementation of international tax reform agreements—notably the Pillar Two global minimum tax framework—has reshaped multinational corporate tax planning. Multinational enterprises with consolidated revenues exceeding established thresholds must ensure an effective tax rate of at least 15% across every jurisdiction in which they operate.

Accounting teams are implementing specialized tax calculation modules integrated directly into enterprise resource planning (ERP) platforms. These automated tools calculate effective tax rates per country, identify top-up tax liabilities, and generate standardized compliance documentation required by national tax authorities.

Real-Time Digital Invoicing and E-Reporting Mandates
Tax authorities across Europe, Latin America, and Asia-Pacific have enacted mandatory electronic invoicing (e-invoicing) and continuous transaction controls (CTC). Under these systems, corporate transaction data must be submitted electronically to government portals in real time at the point of sale or invoice issuance.

This shift toward continuous digital tax reporting eliminates traditional annual tax audits in favor of ongoing automated compliance monitoring. Accounting departments are upgrading invoicing software to ensure seamless XML data formatting, digital signature authentication, and real-time validation against tax authority databases.

Automation and Data Analytics in Corporate Tax Strategy
To keep pace with dynamic tax legislation, tax departments are transitioning from reactive compliance teams to proactive strategic advisors. Machine learning algorithms analyze corporate transactional data to identify tax credits, research and development (R&D) incentives, and cross-border transfer pricing adjustments.

By automating routine tax return filings and calculations, corporate tax directors can focus on long-term capital structuring, evaluating the tax implications of corporate mergers, and optimizing international supply chain networks.

Strategic Priorities for Tax Executives
1. ERP System Upgrades: Ensure enterprise software is capable of generating real-time, granular tax data required for global minimum tax compliance.
2. E-Invoicing Integration: Implement scalable e-invoicing platforms to satisfy regional continuous transaction control regulations.
3. Strategic Tax Analytics: Utilize predictive tax modeling tools to evaluate structural changes in corporate operations and cross-border trade.

Continue Reading

Trending