The general insurance industry is transaction-heavy! In the quest to provide customers with protection across a wide variety of products (cars, two wheelers, commercial vehicles, health, crops, homes, property, et al), the industry issues millions of policies, including many at low ticket sizes and processes thousands of claims. And, it is in this context, that Robotic Process Automation (RPA) helps the industry transform its processes by bringing in operational efficiency and stability. RPA is a digitisation tool that imitates human actions such as clicks, searches, browsing of pages, pasting of content etc. along with enhanced capabilities such as exception handling with the help of Artificial Intelligence. As the business keeps growing, and volumes pick up as a result, it is imperative for the industry to innovate constantly and look for solutions at scale which provide an edge in the marketplace. Hence, at Bajaj Allianz General Insurance, as one of the largest and highly digitized players, we have leveraged RPA to streamline various process that eventually helped us enhance customer experience. Below are some of the use cases wherein RPA has come to the fore in our landscape.
Speed in policy issuance
Policy issuance is one of the most critical processes in the insurance value chain as it affects customers, partners and employees alike. This process involves a lot of human activities across functions such as handling paper-based proposals & handwritten forms, oﬄine processing involving dependencies on and interventions from various teams which were handled through emails & phone calls. Ad hoc inwards after oﬃce hours, holidays, huge group ﬂeet proposals etc. created sudden pressure on employees as they were required to extend their shifts in order to cater to these requirements and maintain good turnaround time. In order to address this issue, we introduced ‘Raftaar’ (which means ‘speed’ in English) – an RPA based bot for policy issuance. Raftaar turned out to be a game changer; our per policy transaction time has improved drastically with a whopping 60% reduction in policy issuance processing time.
Automation of processing hub data distribution
Thousands of insurance policies are received every month, necessitating a good amount of efforts from the staff dedicated to this activity. These employees used to allocate work manually to the processing hubs. The allocation task involved prepping up of unstructured data and using feature engineered data to process further. The effort is quite taxing and recurring in nature as the input database gets updated dynamically! With the aid of RPA, we automated the task of manual cleansing and allocating & the results have been amazing – the data is error free and we have seen quantification benefits as well. RPA has also helped us in terms of workload balancing and optimum utilization of resources thus increasing efficiency. When the lockdown was suddenly thrust upon us, and colleagues had to move to the work from home environment overnight, we were able to move without a glitch because the bot performed the role of the team leader by seamlessly allocating cases to the now scattered workforce, resulting in quick clearance and a wow experience for customers / partners / sales channels.
Data mismatch is a major concern when one deals with multiple sources of information. The end to end process of (a) comparing critical fields from the data received from internal teams for policy booking with the data downloaded from various portal, (b) identifying the mismatch in data and (c) processing the information is tedious and calls for great attention to detail. Our RPA enabled system has not only automated the entire process with zero errors, but also ensured timely communication to relevant stakeholders with a good summary and enhancement in the quality of output.
Automation of crop insurance
The crop insurance policy issuance process is connected to the crop insurance quality check process. The resulting dataset from the quality check process is pushed to the policy issuance module for issuing policies and tagging payments. The RPA based bot issues policies sequentially after validations are scrutinized. A summary of all issued policies is auto emailed to the team and archived for reference.
When we moved to a digital way of working, our switch was without a glitch. And this is only the beginning. When we developed a comprehensive heat map of our landscape, we figured out a plethora of processes which are amenable to RPA. As we transform the landscape, the day is not far off when most of our unit managers can emulate our current leads who say that their team members comprise X humans and Y bots!! The lethal effect of the man-machine combo is what the last few months have taught us, and we will continue to leverage this winning combo in the days to come.
Authored by KV Dipu, Head – Operations & Customer Service, Bajaj Allianz General Insurance