Infinx Healthcare COO Srinivas Manda on AI-driven RCM solutions

The revenue cycle management (RCM) industry streamlines financial processes in healthcare, handling billing, coding, and reimbursement. As healthcare grows more complex, efficient RCM solutions are essential for managing costs and improving operations. Infinx Healthcare, which operates in multiple countries including India, the Philippines and the US, is focused on improving RCM in healthcare by using AI and automation to improve processes and reduce inefficiencies.

In a conversation with TechCircle, Srinivas Manda, COO, discussed Infinx’s expansion plans, including a new R&D centre in Bangalore and a delivery centre in Madurai. Manda also talks about the company’s use of AI to address challenges in RCM. Edited Excerpts:

How is your company’s operations spread out and where does India figure in that?

We have over 7,200 dedicated and outstanding staff members across the globe, and we’re still growing. Our global footprint includes key locations in India, the Philippines, and the United States. In India, we have operations in Mumbai, Hyderabad, Bangalore, and most recently, Madurai. In total, we run eight delivery centres. Bangalore is particularly important for us because it serves as the hub for research and development, focusing on innovation and advanced product development.

In the Philippines, our presence is concentrated in Manila, where we focus on voice and contact centre operations. Meanwhile, in the United States, we have teams dedicated to sales, customer success, and product development. Together, these regions represent our global presence and priorities.

Our R&D centre in Bangalore, inaugurated in July, plays a crucial role in our innovation efforts. The team there focuses on AI-driven solutions, working on predictive analytics, claims optimisation, and decision-making tools. They also develop cloud-based RCM platforms, creating scalable, secure, and efficient systems that integrate seamlessly with health systems.

As for Madurai, our decision to establish a centre there came after evaluating multiple cities. Madurai stood out for several reasons. It has a strong talent pool, thanks to reputable institutions like Madurai Kamaraj University. Government support in the form of incentives for business growth was another key factor, along with the cost advantage of real estate compared to larger metropolitan areas.

What is driving your RCM solutions and how do you tackle healthcare providers’ challenges?

At Infinx, we’re transforming RCM by integrating advanced technology to simplify complex processes. For example, we’ve automated prior authorisation using AI to predict requirements, submit data, and flag missing information, which reduces time and errors.

Our denial management solution uses AI to detect patterns, prevent denials, and improve reimbursements. We combine automation for repetitive tasks with skilled professionals for high-level decision-making, which we call the “human-in-the-loop” model. All our solutions are built on a secure cloud platform, ensuring scalability and easy integration with providers’ systems. We also offer modular automation so providers can address specific challenges like eligibility checks or credentialing without overhauling their entire system.

The results speak for themselves. For example, a national radiology group reduced its aged accounts receivable by 60% and improved collections by 28% in just two months, thanks to AI, automation, and data-driven insights.

Now, as for how AI fits into our solutions—AI is central to transforming RCM. It helps us tackle complex challenges with machine learning and cognitive automation. Our AI-powered prior authorisation solution adapts to changing payer policies, predicts authorisations, identifies missing data, and automates follow-ups, cutting delays and errors while improving approval timelines and patient access.

Our accounts receivable and denial management platform uses AI to analyse claims data, detect patterns, and adjust proactively, optimising claim submissions and improving reimbursement rates.

Finally, our workforce management module coordinates automation with human intervention. Bots handle routine tasks, while specialists tackle complex cases. This approach maximises efficiency, reduces costs, and scales resources based on case volumes, ultimately helping healthcare providers improve financial and clinical outcomes.

How is your company using predictive analytics and AI to optimise claim processing, improve patient access, and ensure accuracy?

Traditionally, accounts receivable (AR) management has been reactive, focusing on chasing overdue payments. However, predictive analytics is changing the game by using historical data and machine learning to forecast payment trends, identify potential issues, and prioritise follow-ups.

For example, Infinx’s AR tools can predict the likelihood of claims being denied or delayed due to payer behaviour, coding errors, or incomplete documentation. This allows teams to address potential issues before claims are submitted, preventing future revenue roadblocks.

Additionally, payment pattern analysis helps predict when a claim will likely be paid or if it’s at risk of non-payment. This enables more effective resource allocation, focusing on high-risk accounts and avoiding wasted time on those likely to resolve on their own.

By uncovering broader trends, like identifying payers or services that cause delays, predictive analytics guides process improvements and payer negotiations, shifting AR management from reactive to proactive.

How do you see the future of the healthcare RCM market, particularly in India, and what trends are shaping the industry?

Artificial intelligence (AI) automates repetitive tasks such as claim processing, scheduling, and documentation, allowing healthcare professionals to focus more on patient care. AI-powered diagnostic tools, especially in radiology, are enhancing accuracy and enabling earlier disease detection. Virtual assistants and chatbots are improving patient care by helping with health management, appointment scheduling, and medication reminders. Additionally, telemedicine is expanding access to specialists, particularly in remote areas, while AI is accelerating drug discovery, reducing the time needed to bring new treatments to market.

In the RCM space, AI is driving significant change. It’s automating prior authorisation processes and adapting to dynamic payer policies, reducing approval times and errors. AI’s predictive capabilities are proactively addressing denial management, improving first-pass acceptance. It’s also improving patient financial engagement by providing real-time cost estimates and enhancing collections. In workforce management, AI predicts staffing needs, optimises resource allocation, and prevents burnout.

At Infinx, we are prioritising the enhancement of AI and automation capabilities, ensuring our platform integrates seamlessly with different health systems and payer technologies to create a unified revenue cycle ecosystem.

While technology and automation are key, we remain committed to the human element. Our goal is not to replace people but to enhance their ability to perform their jobs. We are fostering human-AI collaboration to create tools that support professionals and make their work easier. As we grow, scalability and security are also top priorities. Our platform is designed to support both small practices and large health systems, with data security at the forefront, built on a secure cloud infrastructure that meets HIPAA standards.