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Accounting

Digits touts firm-specific AI models, new partner program

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AI-native general ledger solutions provider Digits announced the release of its AI Firm Models—available exclusively through the new Digits Accountant Partner Program—which are meant to adapt to accounting practices by learning continuously from client data, staff workflows, and firm-specific processes.

Digits CEO Jeff Seibert, in an email, described Firm Models more specifically as predictive machine learning models that learn from a firm’s work across all their clients in Digits and apply those patterns to streamline and automate future tasks. Built, trained, and run on Digits’ infrastructure, each model is uniquely created for and available exclusively to the firm it serves. They are not a new product offering or an add-on to a current product but, rather, an inextricable part of the Digits platform. 

Seibert said that partner firms train their models by onboarding their clients onto Digits and performing cleanup and monthly close work on the Digits ledger. As they take actions within Digits, the model learns immediately and is able to mimic their work as new transactions arrive across their clients. While this is conceptually similar to how Digits’ other models are trained, what’s different is the ability to isolate specific actions taken by the firm and its respective downstream clients to train a dedicated model particular to the firm’s own practices.

Digits booth

“You can think of the Digits AI architecture as a layer cake. At the top are company-level models. These train only on the financial transactions of each individual business or client. Once Digits has seen a transaction pattern for a specific client, it is extremely accurate at replicating that as new matching transactions come in,” said Seibert. 

Usually, when a transaction comes in that doesn’t match the previous pattern on the company-level model, it is passed on to Digits’ global model, which Seibert said has “vast coverage and very high accuracy,” but lacks the ability to capture the unique industry or geographic expertise that accounting firms bring to the table for their clients. The Firm Model is meant to address this. 

“By introducing this new tier of firm model, we offer partners what they’ve been asking us for. Their work on one client now automatically benefits all their other clients, imbuing their best practices across their client base without any manual rules to configure and manage,” he said. 

The Accountant Partner Program, through which firms can get these new models, offers ongoing training, support, and enablement for partner firms, both for their model, as well as their overall usage of Digits with their clients. Beyond the models, participants in the program will also be able to access streamlined client onboarding and centralized client activity with real-time visibility and staff access controls; flexible wholesale pricing that scales with client growth, plus free use of Digits for each firm’s own books; hands-on onboarding, client migration support, and a dedicated success team; and AI-native workflow training for staff at all levels, plus a Coaching Certification program for firm leaders. Also, Digits will work closely with partner firms on an ongoing basis to tune their models and drive accuracy improvements.

The firm model is available to firms of any size that serve at least 50 clients on Digits, with Seibert explaining that transaction volume ensures the model will have strong coverage and accuracy. He added that the model continues to expand and get smarter with every additional client added onto Digits, which makes the offering uniquely powerful for very large firms. For firms that serve multiple distinct sets of clients in different practice areas, Digits will also offer the option to train individual firm models for each practice area (of 50+ clients), so that the patterns and expertise don’t get diluted or confused across the breadth of the firm’s client base.

“We’re ushering in a new era of accounting,” said Seibert in a statement. “Our Accountant Partner Program gives firms direct access to the latest in AI technology—such as our new Firm Models—tools designed and built to automate the tedium, unlock deeper insights, and deliver on the promise of AI-native workflows.”

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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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Accounting

Automated Tax Compliance and Global Regulatory Harmonization in 2026

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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.

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