Connect with us

Accounting

Protect your firm from first-party and third-party cyber exposures

Published

1 year ago

on

In today’s digital landscape, it is no surprise that there appears to be a new cybersecurity story in the news every week, from attacks on major infrastructure to small companies being held for ransom. The risk of cyber threats continues to grow for CPA firms, along with other professional services firms, as all are considered prime targets for cybercriminals given the wealth of sensitive client data, financial information, and/or legal documents they maintain. 

Don’t be lulled into a false sense of comfort that your firm (or your clients) are too small or too large to be attacked. Camico is seeing an uptick in the number of cyber-related claims impacting CPA firms of all sizes and, unfortunately, the severity of these cyber crimes and ransomware attacks have grown in recent years. 

Some of the more frequent categories of loss for CPA firms related to cyber claims include:

  • Social engineering; 
  • Funds transfer fraud;
  • Theft of data;
  • Loss of laptop or data stick
  • Unauthorized use of networks;
  • Failure to protect client confidential information shared with a third-party service provider;
  • Computer system cloud hack;
  • Lost profits related to cyber events; and,
  • Ransom attacks.

Identifying key cyber risks and best practices to mitigate risk exposures is important to safeguard confidential information, maintain client trust and ensure your firm’s continuity. One of the important concepts people must be aware of when evaluating their cybersecurity exposures is the difference between first-party risks and third-party risks. First-party risks are damages and losses you incur from a cyberattack or security breach of your firm, whereas third-party risks often arise when a hacker has penetrated the firm’s (or client’s) computer system causing damages to a client or other third party as a result of the cyber incident for which the firm may be blamed in whole or in part.

As you would expect, first-party cyber exposures have become increasingly problematic for CPA firms as cyber criminals are targeting CPA firms and tax professionals with greater frequency because of the abundance of client data found on CPA firms’ computers. If they are successful in gaining access to a firm’s information infrastructure, there can be costly measures that need to be taken by the firm such as hiring IT forensic experts to determine the extent of the breach, consulting with attorneys who specialize in data breach laws and notification obligations, and providing credit monitoring to those impacted by the breach. 

What may be surprising to some CPAs, however, is the increase in third-party cyber exposures that are impacting firms. These situations often arise when a client has been hacked, and the hacker has penetrated the client’s computer system and, once inside, causes all manner of losses for which the CPA firm may be blamed. Unfortunately, many of these incidents tend to be high-dollar claims against the CPA firm. These claims typically include allegations that the firm failed to detect red flags associated with communications executed by the hacker, falling below the standard of care by initiating wire transfers (later determined to be fraudulent) without “proper” client authorization, failure to “warn and advise” clients of the potential risks/threats of cyber attacks, and the list goes on. 

Consider this real-life scenario: a client of the CPA firm was hacked, and the hacker penetrated and commandeered the client’s email account. The hacker emailed several requests to the CPA firm to wire funds to a new account — a classic “man in the middle” attack. After receiving each request, a CPA firm staff member emailed the client to verify the wire transfer instructions. As the hacker had full control of the client’s email account, the hacker was able to respond back to the CPA firm to verify the payments to the hacker’s overseas bank account. 

Such outcomes have become all too common. With the increased number of claims related to fraudulent wire transfers, the best risk management practice in the absence of any written protocols to the contrary is to verbally confirm all wire transfer requests with the client and not rely on email or voicemail confirmations. 

Unfortunately, technological advances have permitted sophisticated scammers to create AI versions not only of people’s voices, but also realistic avatars of scam targets so that you can’t trust your ears or your eyes on virtual calls (e.g., Microsoft Teams). Ideally, you and your client will have a code word and/or phrase to confirm the authenticity of the person you are speaking to.
 
Cyber insurance protects against financial losses related to data breaches or other covered cyber events. Cyber insurance coverage is basically divided along two lines: 

  • First-party, which refers to losses directly suffered by the policyholder (or insured) firm in response to a firm’s data breach or other covered cyber event, and
  • Third-party, which refers to damages alleged by clients or other third parties that the negligence of the CPA firm contributed in whole or in part to the third party’s cyber-related loss.

It is possible that a single cyber incident may give rise to both damage suffered by the firm (first-party losses) and damages allegedly suffered by others that blame the firm (third-party losses). The relationship between the first and third parties can be formed in many ways. It can be contractual (for example, engagement letters), built through tort law, common law or other ways. CPA firm clients are third parties, and others may become a third party based on the nature of an incident. Clients may have insurance of their own, making them a first party with their own cyber insurance carrier. 

First-party insurance typically covers the direct costs of actions needed after a firm has had a data breach, extortion, ransomware attack or other hacker malfeasance against the firm. Third-party cyber-liability insurance, on the other hand, covers the costs of dealing with the claims of other parties that seek to hold your firm at least partially responsible for damages that they have incurred because of a cyber incident. Sometimes, the line between first-party damage and third-party damage becomes blurred — especially if a firm and its client have both been breached, and forensic analysis cannot conclusively establish either the sequence of events leading up to the breach and/or how the breach occurred.

Understanding the difference between first-party and third-party risks is essential when seeking cyber insurance. Ideally, every CPA firm should have some degree of insurance coverage for both first-party and third-party risks as the CPA firm faces exposure to many accusations and lawsuits in the event of a compromise or data breach impacting its clients’ data. For example, everyone faces risks of inadvertently forwarding a malware-infected email message that subsequently wreaks havoc after being opened by a recipient, or of their computers and networks being breached and subsequently exploited by hackers to serve as launching pads from which to target others. 

Relying on only one type of cyber insurance that may be limited to either first- or third-party coverage may leave businesses exposed to significant financial and legal risks. Whereas investing in both first-party and third-party cyber insurance ensures greater protection against today’s growing cyber threats. 

Related Topics:
Continue Reading

Accounting

AI-Driven Automation and Continuous Accounting Frameworks

Published

1 week 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

Accounting

Modernizing Internal Controls: Machine Learning and Continuous Monitoring in Auditing

Published

3 weeks ago

on

August 5, 2026

By

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

Trending