SheetSway is an all-in-one audit software designed to streamline the audit process, automate tasks, and improve collaboration between auditors and clients.
SheetSway’s Al Audit software uses machine learning algorithms to streamline the auditing process by classifying each account into its proper category, identifying potential risks and issues for a more accurate and reliable audit, and generating insights into a company’s financial performance. The software can also automate the analysis of large amounts of financial data, reducing time and resources required for the process. Additionally, it can identify anomalies and trends that may indicate potential issues and ensure compliance with accounting standards and regulations. Overall, Al in audit software improves efficiency, accuracy, and compliance in the auditing process, resulting in better outcomes for accounting firms and their clients.
The audit software will receive a trial balance containing all accounts and their balances as input. The Al component will use machine learning algorithms like natural language processing and decision trees to classify each account into its respective group (eg, assets, non-current assets, PPE). The auditor can then review and approve these classifications.
After classifying accounts, the software will link each account to its corresponding lead sheet using a database of lead sheets. This mapping helps the software identify which account belongs to which lead sheet, a crucial step in the financial audit process.
The software will analyze the trial balance and general ledger to calculate materiality using statistical methods like regression analysis and variance analysis. This materiality threshold helps the software focus on specific items during the audit.
The software will convert financial statements, figures, and notes from PDF files into a simple summary using OCR to text and processed through A
The software will automatically generate a query list based on the materiality threshold and send an email to the accounting firm. The email will include the query list and a drafted email requesting clarification. The Al component will use natural language processing to draft the email, and the software will have a customizable email template.
Upon receiving correspondence, the software will extract and classify PDFs to each query using OCR technology. The Al component will classify documents based on their content, and the extracted data will be stored in a structured database for further analysis.
The software can perform various financial audit tests (such as bank reconciliations, VAT reconciliations, and sales testing) using OCR and Al. The software will compare extracted data to expected values and flag discrepancies for the auditor’s review. The Al component can also use predictive modeling to identify irregularities in financial data.
The software will include a data analysis module that analyzes financial data for irregularities. The Al component will use machine learning algorithms like clustering and anomaly detection to identify unusual patterns. The software can also provide visualizations of financial data to help auditors detect trends or anomalies.
The software will have a dashboard where clients can answer relevant questions and upload PDFs. The customizable dashboard provides a centralized location for clients to interact with the software and can be tailored to the audit firm’s needs.
Automatic generation of financial statements, confirmation letters and other supporting audit letters.
A4, Triq San Giljan, San Gwann, Malta
Phone: +356 99 147 136
Email: info@sheetsway.com
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