Connect with us

Accounting

Digits says its new AI agents can automate 95% of bookkeeping tasks

Published

1 year ago

on

Accounting platform Digits announced the launch of Digits Accounting Agents, which CEO Jeff Seibert said can — when running on its Autonomous General Ledger product — automate 95% of the entire bookkeeping workflow in a way that, according to tests the company performed, outperforms even human professionals in terms of accuracy and speed. 

Speaking during the Scaling New Heights conference in Orlando, Seibert heralded this development as true end-to-end automation with little to no need for human intervention or supervision beyond exception management and final approvals. The agents, he said, run 24/7 in the background, even “while you sleep,” to automatically do things like collect and reconcile bank statements; manage work papers; categorize, match and book transactions; book payroll; and clean up financial data, among other things. 

“The problem is there’s just too much manual work, and you have to balance between way too many apps to complete it. So an AI-native workflow is flipped. It’s actually a new mindset. It’s not time to close the books. The books are closed, and your close checklist is already almost complete, ready for your review and approval. So you can dedicate your time to advise and budget compliance. This is now possible thanks to technology, thanks to autonomous agents,” he said during his presentation. 

AI agent

In a follow-up interview, Seibert reiterated that the agents are capable of doing the vast majority of the bookkeeping workflow with virtually no need for human supervision. While humans can examine what the agents are doing at any given time, and view the data-driven insights they surface, it’s not strictly necessary: The bots can run completely independently. 

“It does 95% of it. You plug in your bank’s cards, payroll, almost everything is done. The things that the AI isn’t quite sure about, it surfaces for you in an inbox, and so you go in and categorize the remainder. Of course, if you’re doing advanced accruals, or project-based accounting or so on, you’ll still have to do those pieces, but we try to automate the 95% of the tedium that you’re just trying to do every month and save time,” he said. 

Digits emphasized the accuracy of their AI outputs. Regular users of large language models may be familiar with a concept called “AI hallucination,” which is a more artful term for “making things up wholesale,” but Seibert said that Digits’ autonomous Accounting Agents “never hallucinate” due to the nature of the product itself. 

He said that this is because the solution layers both LLMs and predictive models to do the work. The LLMs are not doing the calculations themselves, and in fact are specifically prevented from doing so. Instead it is the predictive models, trained on a massive amount of transaction data, that do the math. The role of the LLM is, instead, to orchestrate agent activity and communicate their results. 

“LLMs are generative. They hallucinate. Predictive models don’t, they can’t. They predict things like: Where should transactions go? We layer the two of them. So we use LLMs to orchestrate our agents. The agents have access to tools which are all predictive. And so when you look at Digits’ technology stack, we run 18 different models in production. Almost all of those are custom-trained prediction models, and then we use LLMs to orchestrate,” he said. 

He said during his presentation that the models are so accurate they not only outperform general models like ChatGPT and Claude by a significant degree, they also outperform human professionals. Digits pitted its agents against professionals from 12 outsourcing companies, with experience as CPAs ranging from a few years to over 30, to see who was faster and more accurate. He said that the humans were about 80% accurate versus 98% accuracy for the bots.

Meanwhile, in terms of speed, the humans took an average of 34 seconds per transaction, while the bots clocked in at 40 milliseconds per transaction. According to the Digits study, the transactions contained relatively fewer edge cases and incorporated a higher proportion of repeat transaction types compared to typical operational datasets. This composition contributed to an observable increase in accuracy rates across all evaluated systems, including both the Digits platform and the LLMs under assessment.

While he hesitated to call it a wholesale replacement for a professional accountant, he noted that it is a replacement in the case of the tedious tasks that accountants don’t like to do and that clients don’t necessarily value. 

“We do want it to take over the really low-value work that you’re just honestly wasting time on every month, and the clients don’t appreciate [because they just] assume the bookkeeping is accurate. They don’t appreciate all the time that takes to make it happen. And so we are trying to take over the tedium while leaving the meaningful work for you to really focus on,” he said. 

During his presentation, Seibert noted that the agents represent a third path that sidesteps the problems of both outsourcing and using LLMs. 

“It’s so painful to search for accountants with outsourcing. They need a lot of guidance, they make mistakes, and they don’t know the details or history of the business they’re working on … . GPT is exactly the same. You have to tell it what to do. It hallucinates frequently, and it doesn’t know that business at all. It’s just trained on general accounting knowledge from the Internet. Digits is completely different. Our agents know the accounting workflows. They run them 24/7, they’re based on predictive models, so they can’t hallucinate, and they have secure access to historical context with each business,” he said. 

When asked what’s next, he said Digits will be working on automating that remaining 5% of accounting tasks. This area represents use cases that are a little more tricky, such as splitting transactions, though he was confident in the future. 

“So we are constantly teaching the agents new skills, and so over the next few years, expect Digits to get better and better and better at getting rid of this tedium for you,” he said. 

Related Topics:
Continue Reading

Accounting

SEC’s Semiannual Reporting Proposal Faces Investor Pushback: What CFOs Need to Know

Published

1 day ago

on

August 25, 2026

By

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.

 

Continue Reading

Accounting

AI-Driven Automation and Continuous Accounting Frameworks

Published

2 weeks ago

on

August 15, 2026

By

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.

Continue Reading

Accounting

Global ESG Reporting Standards and Double Materiality Compliance

Published

2 weeks ago

on

August 9, 2026

By

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

Trending