Your organisation’s financial records rely on accurate data and accurate data management. When it comes to unexplainable fluctuations, an auditor will perform analytical procedures to figure out what went wrong. However, if you can keep records straight, maintain version control and secure information, then you are inherently reducing your compliance risk.
A business’ financial health and its understanding are dependent on its information. So, automation tools and software systems can reduce the frequency of auditors having to perform analytical procedures.
Let’s take a look more in-depth into the process of analytical procedures, the purpose, the challenges you may face and some solutions.
What Are Analytical Procedures?
Analytical procedures are used during an audit of financial records to create evidence. Systematic records rely on historical data and past information to compare with the current period to pinpoint unexplainable fluctuations.
Purpose of Analytical Review
Analytical review is performed for three main reasons, which include:
Preliminary Analytical Review - Required by law, the initial analytical review provides the auditor with a general understanding of the business and the marketplace. This review helps the auditor understand how impactful misstatements can be and to develop an audit program.
Substantive Analytical Review - Here, the auditor assessing the difference between the expectation and actual outcome and determines the risk of misstatement. The auditor must define the tolerance level of divergence between actuals and what’s expected. Additionally, this relies on the auditor, trusting that the data provided is accurate and valid.
Final Analytical Review - Again, required by law, the final analytical review assesses that the overall analysis is consistent with the auditor’s expectations. The risk assessment will occur to see if more audit procedures are required.
Four Phases of Analytical Review
Analytical review happens in four general stages. The auditor performs the following:
Form an Expectation - The auditor grasps a broad understanding of the business and its industry. Then, he or she creates an independent expectation of financial statements. To do so, the auditor may rely on trade journals, budgets and forecasts, and financial statements from earlier periods.
Identify Differences - The comparison begins as the auditor identifies differences between what they expected and what your organisation reported. Should the dispute be more significant than the defined threshold for variance, then the auditor continues to step 3.
Investigate the Reason - By brainstorming, the auditor tries to explain the discrepancy. If it’s explainable, all is good. However, here is where data is critical. Bad data could lead to unexplainable and unintended differences between expectations and actuals. This can contribute to business compliance risk.
Evaluate the Differences - Auditors will look into contracts and invoices and other records to validate proof of what may cause differences in the numbers. This is part of the reason why keeping accurate and secure financial records and statements are so imperative.
Challenges Affecting Analytics Review
Disaggregation - Data may better serve an auditor if it is disaggregated, or separated into different periods, geographic locations, and so on. This could help the auditor recognise differences more quickly and could be more comfortable to explain variances on behalf of the organisation.
Data Reliability - Data must be trusted to be tried. Auditors generally feel more confident in studying data that cannot be manipulated by people. These days, software systems like SolveXia can help to solve the issue of trusted data because the system records every change specifically to provide audit trails.
Predictability - Predictability of data and an auditor’s expectations go hand in hand. To accurately predict hope, and the auditor must also have accurate data that is non-financial, such as the headcount of employees and units produced.
Types of Analytical Procedures
There are generally three buckets of analytical procedures, as outlined below.
Ratio Analysis - Analysis that compares financial with non-financial data. The comparison of day sales outstanding or current ratio (assets to liabilities) over several reporting periods. These data points should be relatively the same over time unless the organisation has experienced massive changes in its customer base, credit policy, inventory, accounts receivable, accounts payable, etc. respectively.
Trend Analysis - This type of analysis looks at patterns over time. For example, it could mean comparing the compensation expense report over several years, which should, in theory, rise steadily with inflation. If anomalies occur, it could be evidence of fraudulent payments to fake employees. Another type of trend analysis includes assessing bad debts.
Reasonableness Test - The development of a model to explain changes in accounts. This can be formed using financial or non-financial information. For example, an auditor may estimate the total annual compensation by multiplying the number of employees with average pay. When compared to the actual compensation, the numbers should be close. If not, your organisation must be able to show the difference through bonus pay, for example.
Each type of analysis is ranked in order of its perceived precision. So, depending on the chosen method, the auditor’s findings can be more or less precise.
Benefits of Automation for Analytical Procedures
Worrying about the accuracy of your financial records should not keep you up at night. Understandably, it may feel like you don’t have total control over what may or may not happen. But, technology can help solve inaccuracies and put back trust to relinquish control.
Automation software can prevent misstatements and reduce compliance risk. Here’s how it can help with analytical procedures and financial audits:
Enhance analytical quality: With substantive analytical methods, auditors are generally concerned about the accuracy of data. Automation technology reduces this concern as data is more easily validated, vetted, prepared and transferred throughout its lifecycle.
Variance investigation: An auditor may rely on tools to further investigate variances. Before the aid of technology, auditors may not have adequately looked into discrepancies. With automation technology, every step can have an audit trail, thereby allowing an auditor to review what happened in the process quickly.
Smaller sample size: Rather than having to provide extensive financial records and prepare statements to generate more massive sample sets, technology ensures the accuracy of smaller amounts of data so that risks and sample sizes remain small.
Minimise disruption: Imagine being able to share financial data in a matter of seconds with an auditor. This was once a lengthy process that was filled with files and papers. It disrupted businesses when an audit occurred. Now, with data automation, an audit can happen in less time and with a less negative impact on a business’ day to day functioning. Data requests can be carried out instantly with full support and approval flows.
Improve communications: The creation of visual representations of financial data is automatically created with software systems. Therefore, analytics can easily be created to help to provide insights for auditors to use as evidence for variances.
Enhance effectiveness: The use of data analytics provides better insight into an organisation and its industry for an auditor to use to formulate expectations. Additionally, by having access to data analytics, auditors can shorten the analytical process and perform checks more frequently. It also reduces the workload of internal compliance officers, so they can have more time improving systems rather than trying to catch up with oversight.
What Auditors Want From You
Auditors, first and foremost, want to trust you. This goes in line with being able to trust the information your organisation provides. They want you, like a CFO or leader within your financial department, to own the economic forecasts and budgets and also have a firm understanding of the business overall. More than ever, CFOs are expected to do more than manage accounting teams as the role of accounting teams in companies continues to shift from bookkeeping to serving as business consultants.
In reality, this means that having accurate and timely data can completely change the nature of how a business operates, as well as how audits happen. By leveraging big data and using automation software to create financial forecasts, models, budgets, analysis and reports, both auditors and CFOs have access to powerful, reliable and unbiased tools that can extend far beyond the audit window, and provide critical insights to the business while turbo-boosting your compliance efforts.