Payer organisations face mounting pressures from rising claim complexity, administrative workload, and limited operational capacity. This session demonstrates how the unified application of artificial intelligence, machine learning, robotic process automation, and next-generation EDI platforms is transforming end-to-end claims processing with measurable gains in accuracy, speed, and efficiency.

Attendees will discover how machine learning models elevate claim classification and greatly enhance anomaly and pattern detection compared to traditional rule-based systems. By identifying coding inconsistencies, routing issues, and high-risk scenarios earlier in the workflow, modern learning techniques significantly reduce manual intervention and administrative burden.

The session also outlines how RPA accelerates repetitive tasks—such as eligibility checks, data validation, and claim routing—enabling reduced turnaround times, lower error rates, and improved throughput. Additionally, it highlights the role of intelligent EDI platforms like Informatica B2B, which automate large-scale X12 transaction parsing, enrichment, mapping, and compliance validation while supporting ongoing regulatory changes.

By integrating AI-driven insights, automation, and intelligent EDI orchestration, payers can shrink pended-claim volumes, enhance adjudication precision, and achieve sustainable operational transformation. This session provides both technical and business leaders with a practical blueprint for modernising claims workflows and confidently scaling for the future.