Key Takeaways
- Understand the challenges that lead to anomalies in accounting and the solutions to resolve them efficiently.
- Learn how to detect finance and accounting anomalies using both manual and AI-driven techniques.
- Discover how autonomous accounting is transforming the finance and accounting landscape for the office of the CFO.
Introduction
In the world of finance and accounting, accuracy and reliability are paramount.
Truth be told, businesses run on accurate financial records and informed decisions. While CFOs and CEOs take center stage in decision-making, finance and accounting professionals are the heroes behind the scenes that make it happen. From account reconciliation to the financial close, they uphold the integrity of financial statements that drive business success.
However, even the most skilled professionals encounter hurdles along the way. Anomalies, like hidden adversaries, can infiltrate the financial accounting process, casting doubt on the reliability of the numbers. So, what are anomalies? In accounting, anomalies are transactional errors and omissions. In simple terms, it is: “Odd transactions that should never happen in accounting but do happen”.
These anomalies, if left undetected, can have far-reaching consequences, jeopardizing financial statements and hindering decision-making.
In this ultimate guide, we will unravel the secrets of detecting and resolving financial anomalies, and shed light on anomaly management best practices. Moreover, we will dive deep into how modern technologies such as AI is digitally transforming the accounting landscape for the office of the CFO.
Chapter 1: Conquering the Challenges of Accounting Anomalies
Conquer anomalies with precision and insight, not desperation and uncertainty, for a resolute financial future.
In the ever-evolving world of accounting, maintaining financial accuracy is crucial for businesses of all sizes. But let’s be honest, it’s not a walk in the park. Accountants face their fair share of challenges when it comes to managing accounting anomalies. To triumph over these hurdles, accountants need to equip themselves with solid processes and strategies.
So, let’s delve into some of the major challenges and uncover some real-life solutions to counter them.
Challenge 1: The Complexity of Sophisticated Accounting Systems and Large Volumes of Data
Sophisticated accounting software has presented accountants with a double-edged sword. On one hand, these technological advancements enable streamlined processes and improved efficiency. On the other hand, they contribute to the complexity of accounting systems. Add the increasing amount of data organizations generate, and you’ve got yourself a real anomaly-spotting challenge.
Impact
This complexity and data overload often lead to errors and discrepancies. If left unchecked, these anomalies can wreak havoc on decision-making, compliance, and the bottom line.
Solution
– Establish validation checks: Create robust validation processes that ensure the integrity of your data. By setting rules and thresholds, you’ll catch any fishy transactions or figures and set things straight.
– Embrace cloud-based solutions: Armed with machine learning algorithms, cloud-based accounting systems can sift through vast data sets, spot irregularities, and boost accuracy levels.
Challenge 2: Human Limitations in Manually Detecting Errors and Omissions
Despite the remarkable capabilities of accounting professionals, the human mind is inherently fallible. Relying solely on manual detection methods can be a risky business, as tired eyes and biases can easily lead us astray.
Impact
By solely relying on manual processes, potential anomalies may go undetected, leading to accounting errors and financial discrepancies.
Solution
– Divide and conquer: Establish clear segregation of duties, ensuring that different individuals are involved in each step of the accounting process. This separation minimizes the risk of errors as well as helps in fraud detection in finance.
– Keep learning and evolving: Stay on top of your game by investing in regular training and professional development. By constantly sharpening your skills and knowledge, you’ll be better equipped to detect anomalies like a pro.
Challenge 3: Time Constraints and the Need for Real-Time Anomaly Detection
In the fast-paced business environment, time is of the essence. The days of periodic audits and leisurely reviews are long gone. In today’s fast-paced business world, anomaly detection needs to be lightning-fast and real-time.
Impact
Failing to detect anomalies promptly can lead to delayed decision-making, sluggish corrective actions, and a negative impact on the financial front.
Solution
– Embrace real-time monitoring: Upgrade your accounting software with real-time monitoring capabilities to keep a vigilant eye on your financial data, alerting you instantly when anomalies pop up.
– Visualize and conquer: Embrace the power of data visualization tools. They allow you to analyze financial data at a glance, making it easier to spot trends, outliers, and potential anomalies.
Chapter 2: Unleashing Techniques for Anomaly Detection
Right techniques not only decode anomalies but also open untapped opportunities for sustainable growth.
The consequences of overlooking errors and omissions can be severe, including financial loss, legal trouble, damaged reputation, and loss of stakeholder trust. Ergo, it’s essential for accountants to follow the right anomaly detection techniques to decode anomalies and unlock financial clarity.
Good old-fashioned tried-and-tested methods have helped accountants detect anomalies for ages. But in the face of large data volumes, manual techniques fall short. This is where AI and Machine Learning come in. Depending on the size of data businesses are dealing with, both manual and AI-driven techniques can help you detect anomalies efficiently. Let’s look at these anomaly detection techniques in detail.
Manual Techniques for Errors and Omissions Detection
Even though automation and fancy technologies have revolutionized accounting, don’t dismiss the good old manual methods just yet. These traditional techniques involve good old data analysis, comparing data to historical records, and keeping an eye out for deviations, inconsistencies, and unusual patterns. Here are five techniques for manually finding accounting errors and omissions:
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Keep an audit trail: When it comes to accounting, keeping a detailed audit trail is essential. Document every step of the process, from initial data entry to the final reconciliation. This trail should include information about the source documents, adjustments made, and any discrepancies identified during the reconciliation process. By maintaining a comprehensive audit trail, you can easily trace back errors or omissions and ensure the accuracy of your financial records.
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Reconcile financial statements: Set a regular schedule to reconcile your accounts, including bank statements, general ledger entries, and other financial records. Compare these accounts with supporting documentation, such as invoices, receipts, and vendor statements. By reconciling these accounts on a timely basis, you can promptly identify any discrepancies and rectify them before they impact your financial statements.
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Cross-verify: Ensure data accuracy by cross-verifying information from various sources. For instance, compare sales figures from your accounting system with customer invoices and payment receipts. Similarly, cross-verify your bank statements with entries in the general ledger. This cross-verification process helps identify inconsistencies and potential errors or omissions.
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Analyze ratios and trends: Keep an eye on financial ratios and trends over time. Look out for unexpected or unexplainable fluctuations. Key ratios like liquidity, profitability, and solvency can give you a heads-up about any potential errors or omissions lurking in the data.
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Conduct internal audits: Don’t forget to carry out regular internal audits. These audits allow you to review accounting processes, controls, and financial transactions. By taking this proactive approach, you can identify any systemic issues or areas prone to errors and omissions.
AI-Driven Techniques for Error and Omissions Detection
With its incredible ability to process vast amounts of data and uncover patterns, AI-driven techniques have become invaluable in detecting errors and omissions in financial records. Here are three AI-driven techniques to identify accounting errors and omissions.
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Supervised Learning Techniques: Supervised learning techniques involve training an AI model on labeled data, where the model learns to classify or predict specific outcomes. In accounting, these techniques can be used to detect errors by analyzing historical data with known discrepancies.
Example: Suppose a company regularly reconciles its bank statements with internal financial records. By training a supervised learning model on past reconciliations, the model can learn patterns and identify potential errors in new reconciliations. For instance, if the model detects a discrepancy in the amount deposited, it can flag it for further investigation.
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Semi-Supervised Learning Techniques: Semi-supervised learning techniques leverage a combination of labeled and unlabeled data to train AI models. This approach is particularly useful when labeled data is limited, costly, or time-consuming to obtain. In accounting, these techniques can provide valuable insights when a limited amount of labeled data is available.
Example: Consider a scenario where a company is implementing a new reconciliation process. Initially, they may have a small set of labeled data containing known errors. By utilizing semi-supervised learning, the AI model can analyze the labeled data and learn patterns to detect similar errors in unlabeled data. This allows for the early identification of potential discrepancies and helps improve the accuracy of the reconciliation process.
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Unsupervised Learning Techniques: Unsupervised learning techniques involve analyzing unlabeled data to discover hidden patterns and structures without predefined outcomes. These techniques can be beneficial in identifying previously unknown errors or omissions in accounting.
Example: Suppose a company’s financial close process involves multiple data sources and complex transactions. By applying unsupervised learning algorithms, the AI model can uncover anomalies or outliers in the data that may indicate errors or omissions. For instance, if a particular account consistently deviates from expected patterns, it can be flagged as a potential error for further investigation.
Depending on the volume of data, businesses can opt for either manual or AI-driven techniques for anomaly detection. Once, the anomalies are detected, the next step is to have a streamlined resolution process.
Chapter 3: Essential Steps Toward Anomaly Resolution
Amidst the turbulent waves of uncertainty, anomaly resolution stands as the lighthouse guiding businesses toward clarity and financial integrity.
Resolving errors and omissions in account reconciliation and financial close is an essential task for accountants to ensure accurate and reliable financial reporting. Let’s look at a step-by-step approach to investigate, and resolve anomalies in your financial statements effectively.
Step 1: Sort anomalies and review
The first step in resolving errors and omissions is to compile a worklist of detected anomalies for review. Take the time to meticulously sort through your findings, ensuring each anomaly is documented and properly categorized. Providing relevant details and context for each anomaly is essential for a comprehensive analysis.
Step 2: Investigation and root cause analysis
Once you have compiled your worklist, it’s time to delve into the investigation phase. Analyze the identified anomalies and evaluate their impact on the financial statements. Carefully trace back the transactions associated with these anomalies to understand the underlying causes.
During the investigation, ask yourself crucial questions. Were there any manual entries or system glitches that could have triggered the error? Is there a pattern or common factor linking these anomalies? This step is vital to pinpoint the root cause and prevent future occurrences.
Step 3: Corrective actions and adjustments
Having identified the root causes, it’s time to implement corrective actions and make the necessary adjustments to resolve the errors and omissions. Refer to your worklist and prioritize the anomalies based on their severity and potential impact on the financial statements.
Work closely with relevant stakeholders, such as department heads or IT personnel, to rectify any system or process issues contributing to the anomalies. Implement the required corrections promptly and efficiently to minimize any further discrepancies. Simultaneously, update the accounting records and reconcile the affected accounts to ensure accurate financial reporting. Ensure that any adjustments made are properly documented and communicated to the appropriate parties to maintain transparency and accountability.
Remember, thorough sorting and review, coupled with a diligent investigation and root cause analysis, form the foundation for successful anomaly resolution. Implementing the necessary corrective actions and adjustments is crucial to rectifying errors and maintaining the integrity of your financial records.
Chapter 4: Best Accounting Practices to Master Anomaly Management
Embrace the best accounting practices, master anomaly management, and forge a path to financial excellence.
To help you ensure accuracy and transparency in your financial records, we’ve compiled a list of best practices that will streamline your financial operations and enhance overall business performance.
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Train staff on data entry accuracy: Accurate data entry is the foundation of reliable financial reporting. By investing in training programs that emphasize the importance of precision and attention to detail, you can minimize errors and discrepancies, leading to more reliable financial statements.
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Don’t overload your employees: Overburdened employees are more prone to mistakes and burnout. Assigning appropriate workloads, setting realistic deadlines, and promoting a healthy work-life balance will not only enhance productivity but also reduce the likelihood of errors during the account reconciliation and financial close process.
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Build a flexible fintech stack: Accounting teams must modernize their fintech stack with technologies such as RPA & AI to automate tasks, minimize manual errors, and provide real-time visibility into financial data, enabling efficient and accurate decision-making.
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Implement internal controls: To safeguard your financial integrity, establish robust internal controls. Segregate duties, introduce approval processes, and implement checks and balances to prevent fraudulent activities and maintain the accuracy and reliability of your financial statements.
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Check for differences between the budget and actual expenses: Regularly comparing your budgeted figures with actual expenses is an effective way to identify potential discrepancies and anomalies. Investigating and resolving these differences promptly will help you maintain accurate financial records and make informed adjustments to your budgeting and forecasting processes.
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Conduct a periodic professional review of accounts: Engaging an independent professional for a periodic review of your accounts adds an extra layer of assurance. This external perspective can identify any overlooked issues, provide valuable insights, and enhance the accuracy and credibility of your financial reporting.
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Adopt best accounting standards: Following recognized accounting standards ensures consistency, comparability, and transparency in financial reporting. Staying up to date with the latest regulations and standards, such as the Generally Accepted Accounting Principles (GAAP) or International Financial Reporting Standards (IFRS), helps you maintain compliance and earn the trust of stakeholders.
By implementing these best practices, you can streamline your financial processes, minimize errors, and enhance the reliability of your financial records.
Chapter 5: How to Choose the Right Anomaly Management Software?
The key to anomaly management success lies in selecting the right software.
Choosing the right anomaly management software is crucial for accurate and efficient financial operations. Here are the steps to help you make an informed decision.
Step 1: Identify Your Requirements
Before selecting any software, clearly define your requirements. Consider the following aspects:
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Financial Close Process: Assess your financial close process and identify the specific areas where you need assistance. Determine the key functionalities you require, such as journal entry management, account reconciliation, variance analysis, or task tracking.
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Integration: Check if the software integrates seamlessly with your existing financial systems, such as ERP or accounting software, to ensure smooth data flow.
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User Roles and Permissions: Determine the roles and permissions needed for different users within your organization. Decide whether you need granular control over access rights and user permissions.
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Reporting and Analytics: Consider the reporting and analytics capabilities you require to track and analyze financial close and reconciliation data. Determine if you need pre-built reports or the ability to create custom reports.
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Scalability: Assess whether the software can accommodate your future growth and handle increased transaction volumes.
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Budget: Define your budgetary constraints to narrow down your options.
Step 2: Research and Shortlist Options
Once you have defined your requirements, research the available software options. Consider the following sources:
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Online Research: Browse software review websites, financial forums, and vendor websites to gather information about various software solutions. Look for user reviews and ratings to gauge customer satisfaction.
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Recommendations: Seek recommendations from industry peers, colleagues, or finance professionals who have experience with financial close software.
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Vendor Evaluation: Compile a list of potential vendors based on your research and initial assessment.
Step 3: Evaluate Vendor Capabilities
Now, assess the capabilities and suitability of the shortlisted vendors. Consider the following factors:
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Functional Fit: Evaluate how well each software aligns with your identified requirements from Step 1. Review the software’s features and functionalities through product demonstrations or trial versions.
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Vendor Reputation: Investigate the vendor’s reputation, experience, and financial stability. Consider factors such as customer support, responsiveness, and the vendor’s track record in serving organizations similar to yours.
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Implementation and Support: Inquire about the implementation process, training, and ongoing support the vendor provides. Ensure they have a robust support system and can address any potential issues promptly.
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Security and Compliance: Assess the software’s security measures and compliance with industry regulations, such as GDPR or SOX. Verify if the vendor undergoes regular security audits.
Step 4: Request References and Case Studies
To gain insights into the software’s real-world performance, ask the vendor for references and case studies. Contact these references to discuss their experiences with the software and its impact on their financial close processes.
Step 5: Consider Total Cost of Ownership
While evaluating the anomaly management software, consider the total cost of ownership (TCO), including:
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Licensing and Subscription Fees: Understand the pricing structure, including upfront costs, recurring fees, and any additional charges for extra features or users.
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Implementation and Integration Costs: Assess any one-time costs associated with implementation, data migration, and integration with existing systems.
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Training and Support Costs: Inquire about training costs and ongoing support fees.
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Scalability and Upgrades: Consider any potential costs associated with scaling the software or upgrading to new versions in the future.
Step 6: Final Decision and Contract
Based on the evaluations and considerations from the previous steps, select the software that best meets your requirements and budget. Before finalizing the contract:
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Review Contract Terms: Carefully review the contract, including terms, conditions, and any service-level agreements (SLAs).
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Negotiation: If necessary, negotiate pricing, contract terms, or additional support provisions.
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Legal Review: If appropriate, involve your legal team to review the contract before signing.
Chapter 6: How HighRadius Transforms Anomaly Management Process
HighRadius’ AI-Powered Anomaly Management Software can resolve anomalies proactively throughout the financial period with alerts for all potential errors or omissions and achieve a smooth financial close.
Since accounting is pattern based we can use classification algorithms to group transactions and use that to identify errors and omissions. Let’s look at how exactly errors and omissions can be identified by HighRadius’ Anomaly management solution.
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Error: HighRadius’ Anomaly management solution will review all current month-posted GL Transactions and compare them to the history of similar GL Transactions to identify and flag any errors.
For example, A vendor invoice for Zoom license costs is incorrectly recorded under Office Expenses (GL Account 6270) instead of Software Expenses (GL Account 6215). This anomaly will easily be identified and flagged by our software.
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Omission: HighRadius’ Anomaly management solution will identify omissions by looking at the history of posted GL Transactions and not finding a similar transaction in the current close month.
For example, A rent expense that is usually recorded in the first week of every month has not been recorded in the ERP for the current month. This anomaly will easily be identified and flagged by our software.
There are 12 out-of-the-box Anomaly Types that the HighRadius’ anomaly management solution identifies based on GL Transaction data. 10 of these are categorized as Errors, while the other 2 are categorized as Omissions. The descriptions of these anomalies along with an example is available in the table below.
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Errors |
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# |
Anomaly Type |
Description |
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1 |
Error – Vendor & GL Account Mismatch |
A business transaction recorded in a specific GL account shows up with a Vendor detail that is historically not posted for that GL account For example, An expense with the vendor Zoom got posted to Office Expenses (GL account 6670). However, in the last 12 months, all expenses for Zoom were posted to the Gl Account for Software Licenses (GL account 6215) |
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2 |
Error – Legal Entity & GL Account Mismatch |
A GL Transaction recorded with a Legal Entity and GL account combination that has historically not been posted earlier. For example, 401 K-related transactions are captured for Apollo Industries USA in GL Account 2260. However, in the current period, there is an entry created with a combination of Legal entityApollo Industries Mexico and GL account 2260 which has not occurred in the past. |
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3 |
Error – Legal Entity & Department Mismatch |
A GL Transaction recorded in a GL account against a Legal Entity where an incorrect department has been entered in that entry For example, An expense has been recorded in GL account 5126 for Employee meal vouchers in the Legal entity Apollo Industries USA. However, the department mentioned in the entry is “Quality Assurance” which is unusual as this department is normally not used under the legal entity Apollo Industries USA but always underApollo Industries Mexico |
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4 |
Error – Unexpected Transaction Type |
A GL Transaction has been recorded in a GL Account with a Transaction Type that is not expected for that GL Account For example, The Asset type GL Account 1047 which is a Bank GL account for the Bank of America operating account always shows transaction type as Receipts or Payments or Journal. However, this is now showing a transaction posted with the transaction type as Invoice |
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5 |
Error – Unexpected GL Account Dr/Cr Balance |
The closing balance for a Liability GL account should usually have a Negative balance (Credit) and an Asset GL account should usually have a positive balance (Debit) at the end of a period. But in this type of anomaly, the asset account has a negative balance and a liability account has a positive balance. For example, GL Account 2050 which is an Accounts Payable GL Account for Credit card payables should have a Negative closing balance. However, this now shows up with a Net Positive balance at the end of the period. |
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6 |
Error – Unexpected Dr/Cr Transaction |
A Credit entry has been recorded in a GL Account whereas this account always has only Debit entries recorded historically For example, GL Account 7005 is the interest expense related GL account. The GL Account 7002 is an income account that tracks all the interest income. A new entry has been posted to the GL account 7005 as a Credit entry instead of being recorded as an income in GL account 7002 with a Debit entry. This implies an Income-related transaction (Credit) has been posted into an Expense related GL Account (Debit)which is an anomaly. |
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7 |
Error – Unexpected GL Account Combination |
An incorrect GL account has been used to record a GL Transaction For example, An Expense for a team dinner-related costs has been posted incorrectly to an Advertising& Marketing Expense: User Conference (GL account 6620) instead of the Office Expense – COGS: Company Events (GL Account 5307) |
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8 |
Error – GL Account & Department Mismatch |
A transaction recorded in a GL account has been created with an incorrect department (cost center) detail For example, An expense has been posted in the Marketing Expense GL Account 5615 against costs incurred for marketing sponsorships. The cost center/department has been incorrectly recorded as “Product” instead of “Marketing” in the transaction. |
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9 |
Errors – Recurring Time Deviations |
A transaction that was usually recorded between a specific date range every month, is shown to be recorded outside the expected date range For example, A recurring Bill payment to Workday is usually posted under the GL Account 2005 by the 1st of every month against subscription fees. However, for the current month, it is recorded on the 29th of April instead. |
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10 |
Error – Vendor Multiple Expense Account |
Typically each vendor is engaged to supply a particular good or service. As a result, each vendor is expected to be booked against only 1 Income statement GL account (1 to 1 mapping). In case this mapping is not followed, it may be a potential anomaly. For example, An invoice from Amazon is booked to “the GL account 6305 for Office Supplies” and another invoice from the same vendor Amazon is booked to “the GL Account 5800 for Professional Services” |
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Omissions |
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# |
Anomaly Type |
Description |
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1 |
Omission – Accrual Reversals Missed |
Accruals (Liability to be paid) posted for one month are typically reversed the following month before updated accrual values are posted again in the next month. This anomaly occurs when the step of reversing the accrual has not been completed by the said date. For example, A vendor accrual calculated forunpaid invoices YTD February and posted to the GL Account 2100 for Other Accrued Liability has not been reversed in the month of March. Ideally, this entry should have been reversed before the revisedVendor accrual for YTD Marchis calculated and posted. |
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2 |
Omissions – Recurring Missed |
This is an omission where a financial transaction was expected to be recorded but has not been recorded in the current period For example, A rent expense that is usually recorded under the GL account GL Account 5700 for Rent & Lease Expense between the 3rd to the 7th of each month. However, this has not been recorded at all for the entire current month |
HighRadius’ Anomaly Management Solution analyzes each business transaction as it happens to identify all of these potential errors and omissions (Anomalies). A high-level overview of the modules in our Anomaly Management Product is
Anomaly Detection – The software analyzes the GL line items and GL Balances extracted from ERP. The transaction is flagged as an anomaly if it meets the criteria/rules listed above. Once it’s flagged as an Anomaly, it’s made available as a worklist for the Accountant to act on it.
Anomaly Resolution – Every detected anomaly can either be a False Anomaly (not an error/omission) or a True Anomaly (indeed an error/omission). Accountants can take one of three possible actions on the detected anomaly to resolve it. They can
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‘Ignore’ if the transaction represents a valid business transaction
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‘Create Task’ if the corrective action is to be assigned to another accountant
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‘Close’ if the user has corrected the anomaly by themselves or someone else has corrected the error
Chapter 7: How Is HighRadius Bringing Change to the Accounting World
We live in a 24/7 economy, where executives expect accountants to close the books on Day 1. This puts the accounting teams in a very unfair situation. At HighRadius, we are working on a disruptive approach to continuous accounting.
The HighRadius Autonomous Accounting Product Suite is one of the three product suites under the HighRadius Autonomous Finance platform for the office of the CFO.
The Autonomous Accounting product suite has three products that could help you manage your end-to-end record-to-report process. These are –
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Financial Close – A single-close project management software that helps you achieve end-to-end financial close automation with close task and project templates, automated workflow, and accounting anomaly detection.
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Account Reconciliation – A software that helps accounting teams optimize account reconciliation by identifying and resolving variances for General Ledger Accounts through configurable matching rules and algorithms.
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Anomaly Management – a software that will flag transaction errors and omissions in real-time and take action continuously instead of waiting for the end of the month.
The Autonomous Accounting Suite will help you transform your accounting process by enabling faster close cycles, error-free reconciliation, and proactive anomaly management with just one platform.
Chapter 8: Building a Business Case for Anomaly Management Automation
Embarking on a digital transformation journey can be quite challenging, especially when it comes to transforming your accounting processes. Accounting processes are complex and pose numerous challenges. Before diving into digital transformation, it’s crucial to understand the complexity, and challenges, and how to address them effectively.
At HighRadus, we specialize in assisting CFOs and finance experts in their digital transformation efforts. With over 800+ successful digital transformation projects under our belt, we have helped businesses of all sizes revolutionize their accounting and finance landscape. If you’re seeking to move away from manual accounting and harness the power of software to streamline and automate your accounting and anomaly management processes, we’ve got you covered.
Let’s take a closer look at how a typical manual accounting process functions within a business and explore how automation can enhance efficiency, while also providing insights into the return on investment (ROI) of digital transformation.
How a Typical Accounting Process Looks Like in a Business
In a typical manual accounting process, the following steps are involved:
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Transaction Posting: AP and AR analysts manually enter transactions into the ERP system during the quarter, which can lead to errors and omissions.
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Data Extraction: At the end of the quarter, the accounting teams manually extract data from the ERP and other systems they use.
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Data Consolidation: They consolidate all the information in Excel, performing laborious computations to prepare financial statements and reports.
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Manual Reconciliation: As part of the consolidation process, the accounting teams perform manual reconciliation by comparing and matching different sets of data to identify any discrepancies or inconsistencies.
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Approval Process: Once the consolidated file is prepared, it is sent for manual approval.
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Closing Journal Entry Posting: After receiving the necessary approval, the accounting teams manually post month-end journal entries into the ERP system. These journal entries are used to record adjustments, accruals, or other necessary transactions that affect the financial statements.
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Post-Quarter Reconciliation: Following the end of the quarter, additional reconciliation work is done to identify any errors or omissions that may have been missed earlier.
This manual accounting process can be time-consuming, prone to human error, and less efficient compared to an automated accounting process. Many businesses today have transitioned to more advanced accounting software and technologies to streamline these processes and minimize the risks associated with manual data entry and calculations.
How the Accounting Process Would Look Like after Leveraging HighRadius Software
After implementing HighRadius’s software, the following changes in the process can be observed:
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Anomaly Detection by AI: the software utilizes artificial intelligence to detect anomalies and errors in financial data, minimizing the chances of inaccuracies.
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Continuous Automated Data Pull: Data is automatically extracted from the ERP system and third-party systems in real time, eliminating the need for manual data entry and ensuring up-to-date information.
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Workflow & Dashboards: The software provides workflows and dashboards to manage the accounting process. This will streamline the flow of tasks and provide a centralized view of the financial data for efficient monitoring.
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Automation of Reconciliation and Financial Close: Tasks related to account reconciliation and financial close are automated. This includes reconciling balances, identifying discrepancies, performing calculations, reducing manual effort, and improving accuracy.
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Approval Workflows: Workflows are set up to automate the approval process. The system routes financial statements, reports, or other relevant documents to the appropriate individuals for review and approval, ensuring a streamlined and auditable process.
Benefits of Implementing HighRadius Software
What Will Be the ROI of Investing in HighRadius Anomaly Management Software
Based on our experience, we have seen an average of 2 employees spend 10% of their time on anomaly management. Considering the average salary of an Accounting Manager to be $90,000, the ROI in terms of automation and saving would be as follows:
- Automation on R2R Tasks: 53.8%*
- Average Savings/year: $11,610*
*Results are average improvements taken from a sample of businesses after adopting HighRadius Software.
Here’s a more detailed insight on the savings:
