Prediction of Health Claims Denial for Revenue Cycle Management Firm

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Created algorithm that process claims data before sending it to the payer and flags each claim for its probability of denial from payer


  • Processed huge data of claims through the intelligent ML algorithm by random forest method and classified the claim into three categories: Fully Paid, Fully Denied, Partially Denied. 
  • For the category of full denial and partial denial, the appropriate CARC (Claim Adjustment Reason Codes) were predicted to allow the users to understand the reasons for denial. 
  • Our algorithm can interpret the denial codes and automate the  process to correct the claims and submit to the payers

Key Features

  • Claim EDI processing 
  • Detection of denial claims
  • Automation of denial correction
  • Prediction of denial reasons
  • Supervised learning
Key Metrics

Reduction in claim denial

Saved 50k+ dollars by avoiding rework on denied claims


Accuracy level on denial prediction

200+ hours of man effort reduced per month

Technology Stack