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How a once-hot accounting fintech’s bet on AI led to bankruptcy

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2 years ago

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Bench Accounting, like many fintech startups, had ambitions to shake up a boring but important corner of finance — in this case, bookkeeping for small businesses. 

It racked up more than 10,000 clients in a little over a decade and seemed well on its way. Yet that wasn’t fast enough to make it the hot fintech it aspired to be when it raised over $100 million in venture financing. In a final push to improve its business, Bench turned to tech’s favorite new go-to: AI. It laid off staff and introduced new automation programs, including a bot named BenchGPT. 

It all culminated in nothing short of a disaster, punctuated by a troubled 2023 tax season when the company needed to request extensions for many of its clients, according to former employees. The next year was no better. As 2024 ended, Bench told clients it couldn’t handle their books. This January, the company filed for bankruptcy, hammering investors including Contour Venture Partners, Bain Capital Ventures and Inovia Capital. Its customers were temporarily left in limbo until an acquirer agreed to buy its assets and revive the business. 

“It’s literally days before year-end and I don’t know what my books look like,” former Bench client Sam Plester, chief executive officer and founder of Mission Brands Consulting in Madison, Wisconsin, said during an interview in December, adding that he had to pay a different firm to redo his books. 

Bench’s downfall is a cautionary tale for companies in a hurry to use AI to transform their business. The episode capped a year of ugly headlines for once-promising fintechs that were VC standouts — and are now learning that there’s virtually no margin for error when dealing with financial services. As the bankruptcy works its way through a Vancouver court, KSV Restructuring Inc., the trustee retained to oversee the proceedings, expects almost all investors to be wiped out. Bench’s most senior creditor, National Bank of Canada, is expected to get only a fraction of what it lent back, according to court filings. 

One serial acquirer saw Bench’s closure as an opportunity. Jesse Tinsley, co-founder and CEO of Employer.com, reached out to the Bench team on the day of the closure announcement to place his bid for the company’s assets. He won the deal and promised to honor all customer contracts by rehiring bookkeepers and taking a back-to-basics approach. “If you just look at the simple nuts and bolts of it, you can run this business well, especially if you don’t have the financial pressure of VC or private equity funding,” said Gary Levin, co-founder and chief strategy officer of Employer.com. The deal, terms of which weren’t disclosed, is expected to close this quarter pending court approval. 

This account of Bench’s challenges is based on interviews with more than a dozen current and former executives, employees and investors in the company who asked not to be named discussing its internal affairs, as well as documents provided by them.

Internal challenges

By late 2021, former Bench executives say the company was garnering $35 million in revenue and growing 40% annually. Yet, it still wasn’t profitable; its automation efforts required investment, and the small business segment is marked by notoriously high turnover rates, meaning it lost clients from closures. Bench wasn’t demonstrating the traits of a venture success story. It wasn’t a hypergrowth, high-margin software business, the type of metrics that hold the potential for a public stock listing.

Despite this, Ian Crosby, co-founder and former CEO of Bench, was in talks that year to receive an acquisition offer valued between $200 million and $300 million from business banking startup Brex, technology publication Newcomer reported. He used the offer as an opportunity to pitch his board on a new path forward: He would conduct another fundraise and use the money to take a bigger bet — an expansion into banking services. The board agreed and in June 2021 Bench announced it had raised $60 million of blended equity and debt financing in a round led by Contour Venture Partners with participation from Altos Ventures, Inovia Capital, Shopify and Bank of Montreal. 

With fresh cash in the bank, Bench tripled the size of its engineering, product and design team to build the next iteration of the business. It began burning through that cash — spending about $1.5 million per month at its peak, according to a former executive. A few months after the 2021 funding round closed, board members approached Crosby with concerns, according to people familiar with the discussions. Instead of straying too far from the core bookkeeping business by expanding into banking services, board members thought Bench should use the new funding to focus on achieving profitability. The board insisted the goal should be slashing one of the company’s biggest expenses: bookkeepers, the same people said. 

In the months following the June funding round, Crosby and board members clashed over whether to continue gradually automating processes, bet big on automation or move ahead with the expansion into banking services, according to former executives. On Dec. 1, 2021, Crosby was removed as the company’s CEO, according to people close to the discussions. He declined offers to stay on the board or take a different executive position and exited the company, they said. 

In August 2022, Bench Chief Financial Officer Jean-Philippe Durrios was promoted to CEO. By this point, a significant portion of the $30 million in series C equity funding had been spent, according to people familiar with the company’s operations. Durrios did not respond to requests for comment. 

AI rollout

Durrios’ tenure was defined by an intense focus on profitability, according to former executives. In the first two years under his leadership, Bench’s 613-person staff underwent multiple rounds of layoffs. By the time it filed for bankruptcy, Bench had 413 employees.  

In mid-2023, Durrios implemented a strategy designed to increase the efficiency of the bookkeepers by splitting them into specialized teams and arming them with AI tools. Under the new model, associates took over client communications despite no longer performing the bulk of the bookkeeping services themselves. The number of clients they were responsible for swelled from the 70 or so they handled completely, to roughly 200 for which they only fielded questions, according to former employees. Shortly after the reorganization, about 40 bookkeepers were laid off, a former executive said, adding strain to the implementation. 

Bench hired outsourcing firm HJS Accountants and promised that upcoming AI product launches would make everything run smoothly. One of these new programs was called BenchGPT, an internal tool for employees to ask questions about client needs. The tool proved to be unreliable, according to a former employee. Bench launched a similar chatbot tool for clients designed to help with expense categorization, but it was often inaccurate and its entries needed to be manually fixed, two employees said. HJS Accountants did not respond to a request for comment. 

As with most AI product launches, the tools gradually improved, but weren’t live in time to support the pared-down bookkeeping team for the 2023 tax season, according to former employees. For that year, Bench was unable to meet filing deadlines and requested extensions for a significant portion of its clients, the same people said. The company needed to rehire bookkeepers, adding additional financial pressure. 

Meanwhile, people familiar with the company’s operations say Bench was frequently facing cash shortages and leaned on bridge rounds of venture funding and debt to continue operating. During Durrios’ tenure, Bench paid off its debt from Bank of Montreal and obtained an increased credit line from National Bank of Canada, the same people said. 

Last fall, Durrios told the board that the business needed money again. They responded with additional funding and sent Adam Schlesinger from Inovia Capital to evaluate the state of the business. In October, Schlesinger was appointed to replace Durrios as CEO while the board searched for a buyer for Bench. However, Bench had breached terms attached to its line of credit, according to people who were present and asked not to be named discussing confidential information. 

On Dec. 27, Bench posted to its website that it was closed for business and recommended clients turn to a competitor, Kick. In January, Bench Accounting Inc. and 10Sheet Services Inc., which operated as a consolidated business, filed for bankruptcy with an accumulated deficit of $135 million, according to a report by the trustee, KSV. National Bank of Canada did not respond to requests for comment. Bank of Montreal declined to comment. 

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Accounting

AI-Driven Automation and Continuous Accounting Frameworks

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6 days 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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2 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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