Finance Automation Fails Without Financial Data Governance
The integration of financial data governance into finance automation improves efficiency and is crucial for ensuring the accuracy and integrity of financial data.
Guy Bar-Gil
April 21, 2025
11 min read
Table of contents:
- Understanding the Gaps in Finance Automation
- The Role of Financial Data Governance
- Industry-Specific Financial Data Governance Challenges
- 1. Compliance and Regulation
- 2. Volume vs. Complexity of Transactions
- 3. Integration With Source Systems
- 4 Consequences of Missing Financial Data Governance
- 1. Incomplete Data Scrutiny
- 2. Risk of Non-Compliance and Mistakes
- 3. Employee Attrition
- 4. Reduced Efficiency and Increased Costs
- Empowering Finance Teams With Financial Data Governance
- The Future of Finance Automation and Financial Data Governance
- The PCAOB's Recent Auditing Ruling
- Leveraging AI for Automated Financial Data Governance
One of the most significant limitations of finance automation tools in the realm of financial data governance is their lack of self-governance. While these tools are adept at automating processes such as invoice generation and pushing them into your ERP system, they fall short in verification and reconciliation.
» Leverage the benefits of AI with our financial data governance platform
Understanding the Gaps in Finance Automation
Consider this scenario: you have a thousand transactions in your billing system that need to be accurately transferred to your ERP. Finance automation tools are designed to produce these invoices and push them into the ERP, but they don’t check if the invoices were correctly synced or if they maintain their reconciled status over time.
What does this mean in practice?
If someone manually changes an invoice amount in the billing system or updates a contract amount in the CRM, these changes might not be reflected in the ERP or other systems. Finance automation tools typically perform their tasks just once—whether it’s pushing an invoice or a contract from one system to another—and don’t conduct ongoing checks or ensure that account reconciliation is maintained daily.
» Discover the importance of automated billing controls
This leads to several gaps:
- Data quality: Incorrect, incomplete, or duplicate data can create various problems, such as confusion, poor decision-making, and even compliance issues.
- Security risks: Lack of sufficient governance can increase the risk of unauthorized access, data breaches, and financial fraud.
- Operational inefficiencies: Data issues from poor governance could necessitate manual intervention, reducing the efficiency of company procedures and increasing costs.
- Mistrust: All of these issues could raise concerns among stakeholders about the quality and integrity of their financial data and your company's reporting.
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The Role of Financial Data Governance
Proactive financial data governance might sound like a complex concept, but at its core, it’s about ensuring the completeness, accuracy, and integrity of financial data across all systems.
While there might not be a single definition, focusing on these key aspects can provide a solid foundation for understanding its importance:
- Completeness refers to ensuring that no transactions are missing between systems. For instance, every invoice generated in the billing system should be accurately reflected in the ERP system, leaving no gaps where transactions are recorded in one system but not in another.
- Accuracy means that all transactions are present in the systems and contain the correct details. This includes accurate amounts, currencies, dates, and other relevant data.
- Integrity, or validity, involves ensuring that the data is consistent and authentic across systems. This means there should be no transactions in the ERP system that aren’t present in the billing system, and vice versa. It also means that no transactions are fabricated or deleted in one system without corresponding updates in the other.
Moreover, effective financial data governance can significantly reduce the risk of enterprise fraud. For instance, if someone attempts to create a fraudulent transaction, such as transferring money out of the company in an act of corporate embezzlement, it would be challenging to execute without leaving traces across multiple systems. An elaborate fraud scheme would involve creating fake vendors and invoices, which requires more effort compared to a simple unauthorized transfer.
» Still confused? Here's some more info about financial data governance
Financial Data Governance FAQs
What is financial data governance?
Financial governance refers to the way a company collects, manages, monitors, and controls financial information, including how they track financial transactions, compliance operations, and disclosures.
What is financial automation?
Financial automation is the utilization of software and other technology to automate financial tasks that have usually been performed manually, such as account reconciliations, financial statement preparation, and budgeting.
Will finance be automated by AI?
While AI will likely be used more and more by finance teams and in financial data governance, it's unlikely to completely replace finance jobs. Instead, it should be thought of as a tool that can empower finance teams to perform more efficiently.
What is the difference between financial governance and compliance?
Financial governance provides the principles and standards for businesses to manage their financial activities, while financial compliance ensures that companies adhere to the local and global legal and regulatory requirements.
Industry-Specific Financial Data Governance Challenges
Financial data governance is crucial across all industries, but the challenges can vary significantly depending on the sector. Let’s break down some of these industry-specific challenges and how they impact financial data governance.
1. Compliance and Regulation
In highly regulated industries, such as healthcare or finance, the need for robust financial data governance is amplified. Companies in these sectors face intense scrutiny from regulators and auditors who demand strict adherence to compliance requirements.
This means that financial data governance solutions must not only manage and reconcile data effectively but also ensure that all data practices meet regulatory standards. The consequences of non-compliance can be severe, including hefty fines and legal repercussions, which makes a strong governance framework essential.
» Ensure financial integrity with SOX compliance
2. Volume vs. Complexity of Transactions
The nature of transactions varies greatly between industries, especially when comparing B2C (business-to-consumer) industries and B2B (business-to-business) industries, which affects financial data governance needs:
B2C Industries
Companies selling directly to consumers, such as software providers or app developers, often deal with a high volume of transactions.
For example, a B2C business might process millions of transactions monthly, each involving small amounts. The challenge here is reconciling these numerous transactions across different systems and ensuring that all payments are correctly collected and recorded.
Manual oversight is impractical, making automated solutions essential for maintaining accuracy and completeness.
B2B Industries
B2B companies that deal with enterprise clients typically handle fewer transactions, but these transactions are often more complex. A single transaction might involve:
- Detailed invoicing
- Varying payment terms
- Much higher costs
- Intricate billing schedules
These can make reconciliation more challenging. For instance, B2B transactions might include sales orders with specific billing schedules and multiple stages of approval.
Ensuring that each aspect of these complex transactions is accurately reflected and reconciled requires advanced governance solutions that can handle such detailed requirements.
» Did you know? Continuous auditing can help manage large volumes of data
3. Integration With Source Systems
The need for integration with source systems also varies by industry. Just like the volume and complexity of transactions, comparing B2B and B2C companies presents the greatest differences:
High-Volume B2C Businesses
These businesses often transfer large batches of transactions into their ERP systems, which can obscure transaction-level details.
Without direct integration into the billing and payment systems, companies may only see aggregated records in their ERP, missing out on the granular visibility needed to ensure accuracy across all transactions.
To address this, financial data governance solutions must integrate directly with these systems to provide detailed transaction-level visibility.
B2B Enterprise Companies
Managing complex billing schedules and intricate transaction details requires sophisticated models that can handle the intricacies of enterprise billing.
This might involve developing solutions that can infer billing cycles, verify invoice timings, and ensure compliance with contract terms.
Addressing these needs often involves creating custom solutions that cater to the specific complexities of enterprise transactions.
4 Consequences of Missing Financial Data Governance
1. Incomplete Data Scrutiny
Without integrating automation into financial data governance, finance teams are significantly hampered. With thousands (or even tens of thousands) of transactions each month—each containing numerous data points—manual inspection becomes impractical.
Human oversight is limited, and the ability to catch every detail diminishes as the volume of data increases. As a result, critical errors or discrepancies might go unnoticed, leading to potential compliance issues and inaccuracies in financial reporting.
2. Risk of Non-Compliance and Mistakes
The lack of automated financial data governance increases the risk of missing important compliance requirements and making financial mistakes. Inaccurate or incomplete data can lead to financial restatements, material weaknesses in financial statements, and potential regulatory fines.
For example, without robust governance, a company might inadvertently misstate revenue or fail to catch significant discrepancies, which can have severe legal and financial consequences.
3. Employee Attrition
Manual data scrutiny and reconciliation can be monotonous. If employees are tasked with reviewing tens of thousands of transactions monthly, it can lead to job dissatisfaction and high turnover rates. The repetitive nature of such tasks, coupled with the pressure to spot anomalies, is not only demoralizing but also unsustainable in the long run.
4. Reduced Efficiency and Increased Costs
In the absence of automation, finance teams operate less efficiently. Analyzing and managing data manually is time-consuming and prone to errors. Automation not only enhances accuracy but also increases operational efficiency.
By leveraging AI and other automated tools, companies can streamline their data governance processes, reduce costs, and improve overall productivity. Automation tools can handle complex data analysis, freeing up human resources for more strategic tasks.
Real-World Examples of Governance Failures
- Currency configuration error: One company dealt with tens of thousands of transactions monthly, billing in 42 different currencies. A configuration bug in their ERP system led to incorrect currency conversions, such as transactions billed in Colombian pesos being recorded as U.S. dollars. This error caused a significant overstatement of revenue—about $15 million in just one quarter.
- Refund application issue: Another customer faced challenges with applying refunds to payments due to technical limitations in their billing system. This problem prevented proper syncing of refunds into their ERP, NetSuite. As a result, they were missing about $250,000 in refunds each month. The team spent between 10 to 12 hours monthly manually locating and syncing these refunds, illustrating how time-consuming and inefficient manual reconciliation can be.
Empowering Finance Teams With Financial Data Governance
Implementing a financial data governance platform can significantly enhance the efficiency and effectiveness of finance teams. Here’s how:
- Comprehensive data inspection: A financial data governance platform allows you to inspect 100% of your data efficiently. Instead of relying on manual oversight, the platform automates data scrutiny, ensuring that every transaction is checked for accuracy and compliance.
- Leveraging collective knowledge: One significant advantage of a governance platform is the ability to harness the collective knowledge of other organizations using the same system. If the platform supports a hundred companies, your organization benefits from the collective expertise and best practices of all those users. This means you can access a repository of established internal controls, work papers, and mature processes developed by industry leaders.
- Access to industry-specific best practices: If your financial processes resemble those of other companies in your industry, an automated financial data governance platform can automatically recognize these similarities and offer relevant controls and work papers. This ensures that you’re not only benefiting from general best practices but also from solutions that are specifically designed for your sector.
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The Future of Finance Automation and Financial Data Governance
Just as organizations practice segregation of duties to prevent fraud—where the individual creating or approving a bill isn't the same one authorizing its payment—the same principle applies to technology. You wouldn’t want the same system responsible for performing financial operations and data entry also responsible for auditing and checking that data.
This separation is essential to establish checks and balances. If a system handles both execution and validation, it might overlook its own errors. Finance automation is valuable because it streamlines operations and reduces the potential for human error, but it also generates a larger volume of data. As automation increases, the need for robust financial data governance becomes more pressing.
Typically, auditors must request files from companies, and the back-and-forth of generating and re-sending documents can be tedious. As financial data governance becomes more prominent in the future, internal auditors will be able to access necessary data in real-time, greatly reducing the need for repeated communication.
» Learn more about balance sheet reconciliation
The PCAOB's Recent Auditing Ruling
A recent ruling from the SEC's (Securities and Exchange Commission) body, the PCAOB (Public Company Accounting Oversight Board), has introduced additional scrutiny for mid-market companies. Previously, enterprise companies were held to higher auditing standards than smaller or newly public firms. However, under the new regulations, all companies will face similar levels of scrutiny.
This shift underscores the growing importance of having comprehensive financial data governance as auditors will require more data to be more thorough in their reviews. Financial auditing and data governance are likely to see more widespread use of AI-powered tools to help companies keep up with the increasing demand for data quality and stricter regulations.
» Discover how AI and new regulations are transforming financial auditing
Leveraging AI for Automated Financial Data Governance
The integration of financial data governance into finance automation improves efficiency and is crucial for ensuring the accuracy and integrity of financial data. As finance teams continue to adopt more sophisticated automation tools, the need for robust data governance will only grow, making it an essential component of any modern finance operation. AI-powered tools like Safebooks AI can help you maintain the quality of your data at scale while leveraging the benefits of automation.
» Ready to take control of your financial governance? Book a demo with us today
