Byju Joseph is Chief Technology Officer at Future Generali India Life Insurance Company. He has nearly two decades of experience in the technology world, doing the hard work of bringing innovation to customer service such as first WhatsApp based customer service in the industry and an AI based bot with touchless customer self-service. He describes himself as, ‘I love to build emerging tech; Coding is my passion’. Lately he has been expanding the tech team with emerging skills (Python, ReactJS, Apache Kafka, DevOps & Cloud architect) at the company.
Every day, Operations team deals with overflowing amounts of monotonous clerical jobs which result in serious time sinks, In the course of handling day-to-day insurance operations like member enrollment, Certificate of policy issuance and servicing, etc., we are flooded with overwhelming levels o f routine, repetitive and operational tasks. Robotic Process Automation (RPA) at Future Generali empower operation in building a high-growth responsive business while optimizing cost. The project implemented emulates transactional, administrative tasks which are repetitive, rules-based and require no decision making or strategizing. Member enrolment processing in group insurance business is at the heart of every insurance company with customer experience and speed are critical in issuing policy on time. There were numerous issues like Manual/inconsistent processing and also customers sending data in various formats causing hiccups with the processes. Accommodating changes in requires constant staff training which often leads to human biases in member enrolment processing which can lead to delays, customer dissatisfaction and lack of visibility. Operation 2.0 - Automation and Process Optimization for Group Business – launched last year was a project wherein RPA bots took in unstructured data from excel, forms, extract structured data and process enrolment based on pre-defined rules. This took care of all major issues with manual processing of Member enrolment and verification rules. The project resulted in automating 89% of manual process for enrolling members besides achieving same day processing capability compared to 7 days earlier. The 5 systems were integrated using RPA Project to meet the outcome. It achieved 60% of Automation using Ui-Path, 79% automation with ML and 79% Quality improvement. The decreased cycle time from 1 day to 30 minutes increased the turnaround time. There was also improved clarity of communication.