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Robotic Process Automation – A holistic approach to operations in Healthcare Insurance

Rajesh Agarwal - SVP & Head - Process Engineering Cell (RPA Expert)

Robotic Process Automation (RPA) has gained significant momentum, and is imparting strong impetus to businesses. It has a ‘T-shaped’ depth spanning horizontally and vertically. Not only does it emulate repetitive and transactional administrative tasks, which are rule-based but is also applicable across all industry sectors. The insurance sector has undergone a vast transformation due to this technology. RPA has had a major impact on the back-office operations, such as Customer Onboarding, Policy Issuances, Customer Servicing, Claims, Revenue Cycle Management, etc. However, the technology needs to be properly implemented to ensure a scalable, responsive, and automated workforce that is quintessential in the digital market. The automated workforce or the RPA units called iBots have played a strong role in handling the frequent crests and troughs in the workflow of the Insurance sector. The RPA proofs-of-concept by themselves help reduce 40-80% of processing time while providing value-adds in terms of quality outputs. At the same time, the logs that are generated are helpful for auditing and risk management on an on-going basis. Organizations are already re-investing the financial efficiencies reaped through RPA in scaling their businesses.

Robotic Process Automation – A strategic approach to operations in Healthcare Insurance

However, not all processes can be slotted for RPA. In order to experience a good success rate of RPA implementation, the enterprise needs to adopt a holistic approach. From a strategic perspective, they need to conduct a proper due diligence of the tasks that can be identified for RPA. The tasks that are repetitive, rules-based, and manually intensive and the tasks, which classify as low complexity and high volume, are ideal for RPA implementation. Today, organizations are using Advanced Robotics, which deploys Machine Learning and Artificial Learning. With this, even tasks with high complexity and high volume are becoming good candidates for RPA along with a helping hand from technology, such as Optical Character Recognition,  and  Process realignment. Now, tasks such as Pre-Adjudication, Policy Administration, and Claim Management in Healthcare Insurance sector are immensely benefitting due to RPA. Technology advancement is also allowing bundling of RPA implementation with Payer Analytics, Provider Analytics, and Dashboards so that Payers experience benefits across the value chain.  

Benefits:

  1. Simplification of Operations: Facilitates automation of complex processes in the Healthcare Insurance domain, which is replete with high volumes of transactional and paper-based data
  2. Speedy Execution: Facilitates an integrated deployment with a focus on moving towards an agile environment 
  3. Efficiency of Scale and Savings: Results in cost savings in the range of 40-70% with a scope of high scalability of operations in Healthcare Insurance
  4. Fast roll-out: A Severity matrix ranking the candidates for processes automation helps to speed the RPA roll-out in the organization
  5. Agile Environment: Facilitates speedy delivery of proofs-of-concepts in the range of 2 days to 2 weeks depending on the complexity of the process
  6. Higher Order of Automation: Enables moving from cognitive assessment to cognitive execution through the amalgamation of RPA, Analytics, and Case Management
  7. Smart Execution: Enables smart delivery of tasks with a combined Services and Product-based approach to suit the Healthcare Insurance vertical
  8. High Degree of Collaboration: Integrated approach between Information Technology and Operational Technology divisions allows movement towards  a highly collaborative workforce 
  9. Analytics Framework: Provides analytics based monitoring mechanisms, which maintain a central control on the iBots, their realignment to changing applications, and their performance, making the RPA ecosystem more robust
  10. Strong Governance: Helps the Governance teams to facilitate, control, and audit the RPA operations in real-time and play an active role in measuring the RPA impact in terms of speed, TAT, and savings
  11. Cognitive Technology based self evolution: A robust blue print of the dissemination of the technology through the enterprise allows to gradually develop the knowledge-base from individual sources of truth for evolution of self-learning iBots through pattern analysis

 

Technology disruption waves sway the markets from time to time. An enterprise needs to define a strong vision accompanied by a detailed blue-print of the RPA implementation. Strong governance, right vision, and correct implementation approach is quintessential in a holistic yet strategic leverage of RPA and other intelligent automation technologies on the anvil.