Optimizing Revenue Cycle Management by Predicting Payments for eCommerce Company

Optimizing Revenue Cycle Management by Predicting Payments for eCommerce Company

What was the Challenge?

A renowned eCommerce company, was facing difficulties with payment processing and supervision. Their existing revenue cycle management (RCM) system was unable to meet payment timelines. They were dealing with frequent revenue leakages, delayed payments, and inefficient cash flow. This scenario negatively impacted customer engagement, payment success, business productivity, and overall revenue generation. As such, they approached Clarion Technologies to overcome various complex situations and challenges, such as:

• Fraudulent transactions
• Recurrent payment failures
• High product returns
• Critical chargeback issues
• Inaccurate payment prediction

Clarion’s Python-Based RCM Optimization Solution

To overcome such critical challenges and meet overarching business requirements, Clarion helped the client optimize their RCM system using Python. We utilized our Python development services to build a scalable RCM optimization solution for elevating payment success for their customers. Our Python developers and eCommerce AI experts provided 360-degree assistance to design, develop, and deploy a powerful payment prediction model for faultless transactions. This model was backed by powerful Python ML libraries and predictive analytics capabilities.

What was the Impact?

Clarion’s Python-based RCM optimization solution helped the client accelerate payment success. It offered better visibility across transactions, resolved potential frauds, and maximized business revenue. The company was able to reduce payment delays and improved cash flow efficacy. Some measurable business outcomes observed by our client are as follows:

• 98 percent accurate payment predictions
• 90 percent CSAT score given by customers
• 40 percent faster payment processing
• 30 percent increase in transaction success

Clarion combined the capabilities of Python, ML, and predictive analytics to optimize RCM, improve CX, and drive better financial outcomes for the eCommerce company.