According to PwC, traditional financial reporting methods have become time-consuming and cumbersome as they typically involve analyzing an organization’s hundreds and thousands of transactions, individually, to form conclusions. However, with data analytics, auditors are now able to streamline the analysis of an organization’s massive document trove, ensuring a higher degree of accuracy and reduction in the chances of overlooking errors.
Data analytics translate data into insights that enable finance teams to unlock new value. It can also help in identifying and tracking anomalies and outliers, which could indicate potential problems or the existence of fraud and need to be further examined.
Challenges in Financial Reporting
Many organizations struggle when it comes to effective financial reporting. Whether it is manual processing, semi-automated workflows, or having thousands of control points, the complexities make it very difficult to monitor transactions. This leads to error-filled financial reporting, which may put the financial health of the entire organization at risk. Let’s explore some of the common struggles that audit and finance teams are facing today:
1. Delays and Errors
Due to the highly complex nature of international accounting principles and ever-changing rules and guidelines, finance teams often struggle to keep up, leading to delays and errors. In organizations that rely on traditional financial reporting processes, the likelihood of errors further increases.
2. Multiple operating units
Many organizations have multiple operating units in different locations with separate regulations, reporting processes, languages, and currencies. The size and diversity of such units create huge problems when it comes to compiling and assessing the transactions of the entire organization.
3. Outdated Technology
As technology evolves constantly, so are the accounting processes. They are becoming automated and are providing real-time visibility into transactions and analytics. However, the speed at which the accounting software are being designed and maintained has not been able to catch up. Legacy systems pose significant challenges to financial reporting.
How Data Analytics can help Financial Reporting
1. Improving Processes
Organizations with thousands of potential financial process control points find it difficult to monitor each of them.
Data analytics can be used to improve the efficiency of the internal financial control environment by providing insights that can help determine which financial processes are most material. This enables the finance team to focus on the right process controls, which in turn, enhances confidence in the organization’s financial process control environment and reporting capabilities.
2. Continuous Monitoring Analysis
Continuous monitoring analytics can be used for an ongoing examination of all transactions and data to assess control effectiveness and capture risks regularly. If the issues are detected earlier, then they can be corrected earlier, thereby reducing the cost of errors and omissions. Therefore, it is important to make the best use of data to identify and address control issues ahead of schedule and follow up on the results.
3. Diversified data and forecasts
You can use non-financial data analysis and forecasts to ensure that the financial results are as accurate as possible. The finance control team should maintain communication with key personnel in verticals like Sales, Customer Services, and HR. Insights on company-wide operations such as new product launches or compensation plans, along with analytical reviews before book closures can be used to ensure that the financial reporting is accurate.
4. Peer Group Metrics Analysis
Analysis of peer group and benchmarking metrics, such as ROA, ROI, EBITDA, inventory turnover, etc. is a great way to validate financial results. This analysis not only provides key strategic data but also helps identify inaccurate or fraudulent financial reporting if the metrics are not in line.
Regulators use these metrics to compare an organization’s financial results with those of their peers and the industry in general to identify focus areas for audit and risk.
Conclusion
Data analytics boosts confidence in financial reporting, mitigates risks and improves the finance function’s credibility. Combining big data with business intelligence and financial dashboard reporting makes it easier to spot inconsistencies and trends across data.
An organization’s financial performance is impacted by several factors and at times some of them may remain hidden. With data analytics, you can analyze humongous amounts of data across different sources, get deeper insights, and make highly accurate forecasts.
Further Insights:
- How Augmented Data Management Improves The Productivity Of Your Data Science Team
- 5 Definitive Use Cases For Advanced Analytics In The Banking Industry
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