en.Wedoany.com Reported - EXL and Lifemed have partnered to launch an AI-powered revenue cycle management solution that uses deep learning to analyze historical data from healthcare institutions, enabling real-time pre-adjudication and automated claims processing. This helps clients achieve a net revenue increase of 10% to 25%, reduce accounts receivable days by over 30%, and lower employee workload by more than 80%.
The payment process for healthcare providers has long faced challenges such as frequent policy changes, complex contracts, and diverse payment methods. Traditional rule-based systems are no longer capable of handling the current data volume and evolving requirements, leading many institutions to struggle with manual corrections, delayed payments, rising administrative costs, and shrinking margins. This collaboration aims to transform revenue cycle management from reactive error correction to proactive prevention through AI-driven automation.
Trevor Jares, Vice President of Integrated Revenue Management Solutions at EXL, stated that by integrating intelligence, automation, and real-time insights, the solution promotes a next-generation management approach from claims submission to adjudication. Darian Rodriguez, Executive Vice President of Revenue Cycle Automation at Lifemed, noted that leveraging the real-time pre-adjudication capabilities of the Deepclaim neural network AI accelerates the adoption of more efficient revenue cycle workflows, helping healthcare institutions achieve proactive prevention rather than reactive correction.
Lifemed is a healthcare technology company whose flagship platform, Deepclaim, utilizes proprietary deep learning neural networks to analyze provider-specific historical data, automatically performing compliance checks, optimizing billing codes, and managing denials and appeals before claims submission. EXL is a global data and AI company serving industries including insurance, healthcare, and banking, headquartered in New York with approximately 67,000 employees worldwide.
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