Proactively Resolve 80% of Anomalies with AI Agents
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Resolve 80% of Anomalies Seamlessly
Enhance anomaly detection precision by continuously training the AI engine based on user input and feedback loops.
Gain complete visibility into all marked anomalies with insights on severity, category, and financial impact.
Enable end-to-end data flow with native ERP and non-ERP integrations for real-time anomaly monitoring.
Standardized reporting ensures transparency in review, approval, and resolution of every detected anomaly.
HighRadius stands out as a challenger by delivering practical, results-driven AI for Record-to-Report (R2R) processes. With over 200 LiveCube agents automating 60 %+ of close tasks and real-time anomaly detection powered by 15+ machine learning models, the platform drives continuous close with guaranteed business outcomes—moving beyond AI hype. HighRadius aims to achieve 90% automation by 2027 as it evolves toward full autonomy.
Learn how HighRadius is helping global enterprises automate, accelerate, and lead the future of financial close and consolidation.
Download the ReportData-to-insights automation, built for scale—no constant human supervision needed.
Learn how finance teams are using AI to catch omissions and anomalies early, before they disrupt the close.
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Explore proven strategies to reduce close errors, detect anomalies early, and improve reporting accuracy.
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Discover how leading teams use automation to accelerate close cycles, reduce anomalies, and ensure audit-ready books.
Download GuideEnhanced fraud prevention
Automated anomaly detection software helps identify fraudulent activities with enhanced efficiency, allowing businesses to implement better fraud prevention policies.
Improved financial accuracy
Since automated anomaly detection systems leverage AI/ML-based algorithms to detect errors and omissions, organizations can ensure that their financial statements are free of any errors.
Increased efficiency
Automating the anomaly detection process reduces manual labor, enabling accounting teams to focus on more strategic tasks that require human insights. Further, automated anomaly detection helps enhance efficiency of accounting workflows by improving accuracy during reconciliation.
Better compliance
Effective anomaly detection ultimately reduces misstatements and aids in fraud and risk management, this in turn, allows businesses to ensure regulatory compliance and maintain financial integrity.
HighRadius' automated anomaly management solution is ERP-agnostic, seamlessly integrating with any ERP system to ensure efficient, streamlined financial processes.
Traditional methods rely on manual reviews and retrospective audits. HighRadius AI agents proactively detect, categorize, and resolve anomalies in real time—before they impact your books.
AI agents analyze 12–18 months of GL history to detect missed, duplicate, or misclassified entries—improving accuracy with every cycle.
Automatically classify anomalies by type and risk level, suggest corrective actions, and route for review—no manual oversight required.
From anomaly detection to resolution tracking and audit logging, every exception is managed autonomously across your ERP landscape.
Used by global finance teams to resolve 80% of anomalies, close books faster, and maintain 100% financial reporting integrity.
Growing enterprises require scalable solutions to streamline the anomaly detection process. With our anomaly detection solution, say goodbye to manual anomaly detection and resolution and leverage AI/ML-powered workflows to achieve enhanced financial integrity.
Leveraged advanced AI/ML-powered technology for accurate anomaly detection and resolution.
Easily integrates with existing financial systems and ERP to ensure smooth, uninterrupted data flow.
Leveraged advanced AI for effective fraud detection and prevention.
Reduces manual effort, allowing teams to focus on strategic tasks.
Automated anomaly detection leverages technologies such as AI and ML to automatically detect errors, identify unusual patterns, and uncover discrepancies in financial data. Automatic detection of errors and omissions allows businesses to take preventive measures and prepare accurate financial statements.
As businesses grow automated anomaly detection tools become essential owing to the large data volume they need to manage. Manual methods of anomaly detection lack scalability and are unable to effectively detect errors and omissions, especially as transaction volume increases. Therefore, in today’s data-driven world, it’s crucial for businesses to adopt automation for anomaly detection in order to mitigate risks, prevent fraud, enhance compliance, and ensure accurate financial reporting.
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Financial fraud is an ever-present threat for businesses, one that can only be mitigated and managed properly with automation . Using manual, error-prone methods for fraud detection and prevention can often result in hefty fines and legal action, in addition to damaging the credibility of an organization.
Advanced automated anomaly detection solutions, such as HighRadius automated anomaly detection software, however, help businesses achieve 100% transparency with AI insights to improve fraud detection and prevention. Powered by AI/ML, these tools are able to continuously learn through the data it is fed which enhances their efficiency and with time they can proactively detect different categories of anomalies while reducing false positives.
Automated anomaly detection tools empower organizations to prevent financial frauds by providing capabilities such as:
Selecting the right anomaly detection software is extremely important for businesses aiming to achieve precise and simplified financial reporting,while ensuring adherence to regulatory requirements.The first step in selecting the right software is identifying the problems your current system and processes are not able to solve. The more specific the problem identification, the better decisions you can take when it comes to choosing the right solution for your business.
The correct anomaly detection solution will be able to streamline data extraction and integration to automate key processes, in addition to having a user-friendly interface. Some key aspects to look for while selecting anomaly detection software are:
Ensure that the software is compatible with your existing systems like ERPs and CRM for seamless data flow.
Verify that the software offers robust data protection measures and complies with relevant regulatory requirements.
Choose a software that provides immediate access to all transactions
For enhanced ease of adoption, the software should have an intuitive and easy to understand interface that facilitates quick adoption.
The software should offer clear visibility and accountability across various process levels.
Opt for a software that centralizes data across all company units for consistency and ease of access.
Automate reconciliations, eliminate exceptions faster, and deliver audit-ready financials with agentic AI for accounting.
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Automated anomaly detection offers benefits such as enhanced financial accuracy, audit and compliance readiness, and improved anomaly identification and resolution. With automated anomaly detection, it’s easy for accountants to review large datasets for any errors and accelerate the financial close process.
In addition, automating the anomaly detection process results in cost savings for businesses by detecting errors and omissions early, allowing proactive resolution. There are fewer financial and regulatory repercussions for companies due to early detection and resolution of anomalies.
Businesses should adopt automated anomaly detection for increasing financial reporting accuracy, enhancing risk mitigation and fraud prevention, and enabling real-time monitoring of financial information. Automated anomaly detection also ensures that businesses are always audit- and compliance-ready.
These softwares are capable of analyzing large datasets and identifying any anomalies in real-time. Businesses can also save costs through early anomaly detection and improve strategic financial decision-making.
Automatic anomaly detection leverages technologies like artificial intelligence and machine learning to analyze datasets and detect patterns based on historical data. When the system detects deviations from the norm, it flags them as an anomaly for the accountant to check.
With advanced data integration capabilities, the software collects data and then leverages pattern recognition and anomaly detection algorithms to identify erroneous transactions or omitted transactions.
AI analyzes patterns, performs behavioral analysis to learn normal behavior, and detects occurrences that stray from the norm in financial data. To achieve this, an AI-powered anomaly detection system extracts data from various sources, analyzes it, and leverages anomaly detection techniques to flag errors and omissions in financial data.
