What is financial reporting automation?

With automated financial reporting, FP&A teams can automate tedious reporting tasks and prepare financial statements and reports in real-time. They can also automate workflows, create automatic audit trails and manage consolidation and verification. This process frees up team members to focus on more strategic initiatives like analysis and relationship building.

Executives are realizing the power of AI in finance and beginning to embrace the use of AI automation throughout their finance operations, such as in AI agents for finance and AI in FP&A.

A recent IBM Institute for Business Value research found that 68% of executives, including chief financial officers (CFOs), report experimenting with AI automation as digital assistants evolve into autonomous agents supporting self-service finance operations.

Separately, of the executives surveyed, 37% expect to implement touchless automation in predictive insights and 29% in financial analysis and reporting.

Putting AI to work in finance is changing the way FP&A teams operate. The technology is delivering major gains in accuracy, ease of use, efficiency and business strategy. This seismic shift is transforming the finance industry from being a reactive function to driving proactive change and decision-making for planning, budgeting and forecasting.

Teams automate financial reporting through AI-powered software that can integrate with an organization’s existing financial systems. Some existing systems are accounting software, Excel spreadsheets, FP&A software, financial data management tools and enterprise resource planning (ERP) systems.

The steps ahead lay out a general path for how financial reporting automation works:

1. Collect data: Automation software connects directly to existing finance and reporting tools to pull raw financial data into a single place. This step in the process eliminates the need for manual data entry.
2. Process data: Data processing and data validation occur through robotic process automation (RPA) and other automation tools that validate data and convert physical documents into digital text.
3. Generate analysis and insight: AI and machine learning (ML) analyze patterns and generate variance reports. These technologies can detect anomalies, fraud risks and trends that a human might not.
4. Report: The financial automation system compiles processed data into standard financial statements, including income and cash flow statements, balance sheets and custom reports. These statements can be formatted for specific forecasting needs and dashboards.
5. Review: After report generation, financial reports can be scheduled for automatic delivery to stakeholders. Alternatively, users can query the automated financial reporting software for real-time insights, track financial transactions and maintain audit trails for regulatory compliance.

Financial reporting automation extends well beyond simple repetitive tasks and workflows—it can transform many core areas of the reporting process.

Automation software helps FP&A teams prepare key financial statements with ease, reducing the risk of human error and shortening data collection time.

Automated reporting systems can pull financial information from integrated systems, improving accuracy and scalability. By creating financial statements quickly and accurately, this system drives more data-driven decision-making.

Financial reporting automation enables FP&A teams to generate management, shareholder equity and expense reports using real-time data. This strategy eliminates the manual process of data collection and the complexity of managing multiple data sources. Automation software reduces errors and enables more informed decision-making.

Automated reporting software also applies consistent formatting and accounting rules and generates custom reports for various stakeholders. By having the data all in one place, CFOs and business managers can have strategic discussions about financial performance because they’re all looking at the same metrics and figures.

Automation helps reconcile transactions and compare thousands of transactions from multiple sources. Account reconciliation is a manual task that is error-prone and can delay month-end closing procedures.

Automation tools that use machine learning (ML) can learn from historical transactions and adjust to mitigate future fraudulent activity.

Financial professionals must manage complex regulatory compliance standards and tax obligations. Automation can simplify the process for meeting reporting requirements and accounting standards, creating a single source of truth across systems.

Automation software also automatically generates reports that align with standards set by governing bodies, including the Government Accounting Standards Board (GASB).

By using optical character recognition (OCR) technology, systems capture data from various sources, eliminating the need for manual data entry. The software can pull data from sources like bank feeds, invoices and receipts.

One example of OCR is for expense management. A finance team can spend hours reviewing each report and verifying that the receipt matches the claim expense. With OCR, employees can simply take a photo of a receipt with their phone to extract and categorize the information.

Finance automation is a worthwhile investment for companies looking to transform their financial management processes and day-to-day operations. These are some of the main benefits:

• Improves accuracy: Automation software eliminates the need for human data entry, leading to more accurate calculations and fewer errors.
• Streamlines workflows: Workflow automation helps systems eliminate delays and reduces the need for manual handoffs.
• Maintains consistency: With financial reporting automation, FP&A teams can maintain consistency across all financial tasks through standardized processing and task automation.
• Improves control: Automation software helps FP&A teams maintain control by automatically flagging unusual activity or patterns and enforcing complete documentation on transactions.
• Enables flexible, scalable operations: Automated financial reporting tools can handle increases in transaction volume, allowing teams to move quickly and scale operations.

Finance automation has tremendous benefits. However, there are still some challenges worth mentioning. It’s important for a company to understand potential problems that might come up and prepare leadership for when they occur:

• High up-front costs: Automation software requires a significant up-front investment, including things like software licenses, hardware, system experts and other ongoing costs.

• Complex technology: While automation tools are meant to integrate with legacy systems, it doesn’t mean it will be a simple process. Launching the software might demand extensive technical expertise.

• Compliance needs: Modern software requires keeping up with regulations and system updates. IT teams must devote resources to monitoring these compliance requirements, implementing access controls and maintaining audit trails.

• Employee resistance: Automation can be threatening to employees and can cause disarray when it’s clear that the purpose is to reduce costs.

The benefits of automated financial reporting will range depending on the type of automation software being used. However, there are core capabilities that all options should provide that streamline financial processes and lead to more strategic decision-making.

Financial reporting automation tools connect to source systems and stream data as it changes. Finance teams see transactions, balances and performance metrics in real-time, not after batch processing. The immediacy of automation software improves accuracy and reduces manual reconciliation.

By integrating data across enterprise resource planning (ERP), customer resource management (CRM) and third-party platforms, organizations maintain a single, trusted view of their financial operations.

Customizable dashboards and templates present finance teams with the metrics that matter most to each role.

Finance teams can tailor views to track key performance indicators (KPIs), trends and exceptions at a glance. Users can filter and drill down on data through a user-friendly interface without needing an abundance of technical expertise. This flexibility improves insight and aligns teams around shared goals.

Financial reporting automation can scale as a business grows. The platform handles increasing transaction volumes, new entities and expanded geographies without performance loss.

Organizations can add users and data sources while maintaining governance and control. This scalability protects long-term investments and supports innovation without requiring a system overhaul.

Automated financial reporting tools integrate easily with existing systems through application programming interfaces (APIs) and rebuilt connectors. Organizations can connect ERP, payroll, procurement and banking platforms with minimal disruption.

Fast integration addresses challenges and cuts down on implementation time, lowering IT efforts and accelerating time to value.

Finance leaders need to stay on the cutting edge and be proactive when implementing the right automation tools for their company. The elements presented ahead are examples of best practices to guide organizations as they implement financial reporting automation.

1. Set clear goals: Start by defining what financial reporting automation must deliver to the organization. Identify priority reports, required accuracy levels and compliance needs. Align goals with business outcomes, such as faster close cycles or improved forecasting. By setting clear objectives, finance teams have guidance on scope and metrics for success.
2. Prioritize data integrity: Build an automation tool on accurate, consistent and well-governed data. Standardize data definitions and validate sources to build a strong data structure for the automated system. Strong data integrity improves trust in reports and audit readiness while enabling stronger decision-making across the entire organization.
3. Include multiple stakeholders: Engage across multiple business functions, including finance, IT, compliance and business leaders. Each group brings critical insights into requirements and dependencies. Through collaboration, system design improves and tasks such as financial modeling and financial forecasting don’t need to be reworked. Collaboration improves system design, allowing organizations to build better processes and avoid reworking tasks like financial modeling and forecasting. Involving stakeholders can also ensure that automated reports meet operational and regulatory needs.
4. Focus on training and upskilling: Provide finance teams with the skills to use and manage automated reporting tools. This best practice is especially important as generative AI in finance becomes more prevalent. Provide role-based training on dashboards and workflows, and enlist a change management team when the resources allow. Upskilling reduces resistance to change and maximizes return on investment.
5. Implementing in stages: Adopt a phased approach to reduce complexity and risks. Start with high-impact and low-complexity reports. After there is nominal success, expand to advanced use cases. This method allows finance teams to validate results and refine processes before scaling across the entire organization.
6. Monitor progress: Track performance against defined goals set during the initial implementation stage. Measure accuracy, cycle time, user adoption and exception rates. Continuous monitoring helps FP&A teams identify issues early and confirm that automation delivers expected benefits.
7. Iterate and optimize: Treat financial reporting automation as an evolving capability that can be changed and modified at any time. Review processes regularly and evaluate feedback with stakeholders to make improvements when necessary. Continuously seek optimization opportunities to improve efficiency and strive for more valuable reporting outcomes.