Accountants often have to struggle with financial discrepancies and inconsistencies in reporting due to a lack of timely error detection and rectification. Find out how anomaly management helps identify anomalies early on and improve the financial close process.
As accounting standards and the need to comply with them evolve, an accurate and consistent financial close has become important. However, the process goes beyond preparing financial statements and auditing assistance. A robust financial close calls for identifying and diving deep into the root causes of anomalies or errors and ensuring there are no discrepancies in financial reporting.
However, most businesses fail to detect and rectify errors and omissions on time, thereby impacting compliance, auditing, decision-making, and more. Numerous reasons, like the complexity of sophisticated accounting systems, manual detection and correction of errors, and lack of real-time anomaly flagging contribute to errors and omissions in accounting.
The only way for businesses to solve this is to have a robust anomaly management infrastructure in place. It helps businesses analyze each transaction as it happens to identify potential errors and omissions (anomalies).
Here are four ways anomaly management helps businesses improve their financial close.
1. Early identification of anomalies
Anomaly management offers mechanisms that enable businesses to leverage early warning capability that improves the accuracy and speed of financial close and reconciliation. For instance, a business detects a missed recurring entry (prevention) or
a journal posted with an invalid combination of general ledger accounts (detection). This constant detection and flagging throughout the month enables timely correction.
An anomaly management software will help the business extract the data about GL transactions and GL balances from the ERP or a third-party system. Any business transaction that doesn’t conform to the historical patterns of anomalies is flagged as a potential anomaly. The system usually uses 12-18 months of historical data to identify patterns of transactions in the GL. Once an anomaly is detected, accountants will be notified.
2. Enable corrective action
Effective anomaly management not only helps businesses identify anomalies based on past transactions but also suggests corrective actions to be taken. For instance, if a GL account and cost center have been flagged off as an “unusual transaction,” the tool provides a list of potential corrective entries based on past combinations of GL accounts and cost centers seen in the past transactional data.
Leveraging advanced anomaly software can help businesses generate automated corrective suggestions for resolution and expedite the financial close process. Every detected anomaly can be either a ‘false’ anomaly (not an error or an omission) or a ‘true’ anomaly (definitely an error or omission). Businesses can take one of four possible actions to resolve the detected anomaly.
- ‘Accept’ if the transaction represents an invalid business transaction
- ‘Ignore’ if the transaction represents a valid business transaction
- ‘Create Task’ if the corrective action is to be assigned to another accountant
- ‘Close’ if the user has corrected the anomaly by themselves or someone else has corrected the error.
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3. Lightning-fast identification of mis-reported source data
Most sophisticated accounting software do not have out-of-the-box anomaly management to detect anomalies in real time. They have basic variance analysis features that view GL account level changes reactively. Without a robust anomaly management system, accountants will have to manually identify the reason for any potential errors and correct journal entries manually.
A fully automated anomaly software offers a customizable out-of-the-box dashboard to enable key stakeholders to get a bird’s eye view of potential misreporting in the source data. There are multiple out-of-the-box dashboard reports, which s help businesses take proactive actions on potential anomalies.
4. Automate rule discovery
To enhance anomaly management, businesses can automate rule discovery to identify data elements of interest. For example, an accountant can say that they are interested in a combination of legal entity, transaction type, amount, and department to identify potential anomalies. The automated rule discovery will churn through the data and come up with patterns and exceptions. This is a big efficiency gain, as the accountant does not need to define rules or business logic to identify exceptions.
Improve Financial Close With Anomaly Management Software
Anomalies are potential errors and omissions that can delay or result in rework during the month close process. However, most of the sophisticated accounting systems cannot handle the data overload and don’t have any feature of spotting anomalies, let alone rectifying them. Using an AI-powered Anomaly Software helps accounting professionals identify and rectify potential ‘Errors and Omissions’ throughout the financial period so that teams can avoid the month-end rush and ensure continuous close. Further, the AI algorithm continuously learns through a feedback loop, which in turn reduces false anomalies.