Inbound Payment Recoveries

A dedicated team currently manages the manual processing of approximately 100+ cases daily. This substantial volume underscores the importance Inbound Payment Recoveries process. This also involves multiple systems where data is validated to process the payments. The recoveries process was complex and meeting SLAs towards resolution and recoveries were difficult.

Business Challenges

• Data Entry Errors: Manual data entry is prone to human errors.
• Inefficiency: Manual processes are time-consuming.
• Payment Processing Delays: Delays in processing inbound payments, especially if they come from external sources.
• Fraud Detection and Prevention: The risk of fraudulent payments, where funds are mistakenly or maliciously transferred, requiring investigation and recovery efforts.
• High Volume of Payments: Managing and processing large volumes of inbound payments can strain resources and cause backlogs, making timely recovery challenging.

Solution Highlights

• Automated the extraction and validation: Payment details (e.g., account #, payment reference, amount) using UiPath's OCR and AI Fabric for intelligent data extraction from scanned documents and email attachments.
• Anomaly Detection: AI-powered automation to analyze payment patterns for anomalies, flagging potential fraudulent transactions. UiPath integrates with AI models (through AI Center or third-party AI systems) to automatically detect suspicious payments based on set criteria.
• Scalable Automation: UiPath bots work in parallel to process high volumes of inbound payments, reducing manual effort and improving processing speed. RPA can work 24/7 without breaks, enabling processing for high volumes.

Business Outcome

26k hours saved annually. Turnover time reduced to 3 days from 12 days and 92.4% success rate for orchestration runs across all processes.