How AI bot drives business for Bajaj Allianz Life Insurance, IT News, ET CIO
Over the past decade for insurance companies, it has been an era of basic systems. Many banks and insurance companies have spent millions on implementing or upgrading basic systems, basic policy administration systems, basic CRM, etc. From a systems architecture perspective, industries have invested in a system of records and workflow. At the industry level, this is a time when the focus is on AI for the insurance industry.
With the increase in communication at all levels, many organizations are diverging for automated and intelligent tools to speed up their response time and reduce their costs. Thus, AI-powered chatbots have achieved advanced functionality replacing repeated human tasks and contributing to the digital image of the organization.
For Bajaj Allianz Life Insurance, moving to analyze and serve each client differently is essential today. Goutam Datta – Chief Information & Digital Officer at Bajaj Allianz Life Insurance explains how the organization’s use of bots has shown huge results in enriching the customer experience.
In 2017, Bajaj Allianz Life Insurance introduced its AI-based BOING bot. Referring to the bot’s superiority over any other bot in the insurance industry, Datta believes that the bot’s emotional intelligence and understanding is one of its main advantages.
âOur WhatsApp based employee or customer bot is quite mature and can seamlessly interact with the customer. It responds to 36 types of service requests. Our bot’s differentiator is what stage of maturity it is in, from understanding questions to responding appropriately. So when you are dealing with a bot, you have to give the bot that intelligence so that not all questions need to be answered scientifically, they learn while they are being used. You might have had this self-learning experience using Alexa, âDatta said.
Starting in the pre-COVID era, the company introduced several AI-based chatbots that gained momentum and saw the rapid adoption of these bots. âWe are now among the top 5 or 6 private life insurers in the country. And we’ve seen businesses and customers respond favorably to our digital interventions, making around Rs 45 crore gross premium based on conversation and engagement with Bots since its launch, âhe said.
Adding further, Datta says that this is the first time that the company’s digital applications have seen a 250% increase in consumption in level one cities in terms of the demographics of stakeholders like agents, customers. , integrated circuits and partners, which use it via WhatsApp. and web platforms. The company also saw a 225% increase in level two cities from last year to this year.
Working on other AI initiatives, Datta also highlights the use of Humanoid, which is the ability to interact with the brand through Voice, the other great element of AI. The case in point is the voice bots used by the organization in its call center. Datta says, âA significant number of calls are handled by a humanoid which is nothing more than a voice bot and is driven by AI. These robots are trained to understand the context of customer calls, recognize the voice, whether male or female, and then best calibrate their responses to meet the customer’s request. Another area where we have implemented a fairly good degree of intelligence is fraud analysis. This allows us to know whether incoming business and new business are likely to be the subject of an early claim or not.
On the benefits of AI, Datta said, âBy standardizing processes through AI systems, the process becomes much more efficient and value-driven for both customers and the business,â as it increases interactions with consumers and renewal while creating the internal working model. more efficient and easier for the business.
AI – Data-Driven Obstacles and Benefits
As AI helps improve the customer experience and create digital brand value, the company also faces data challenges for AI-driven systems. Speaking of the same, Datta addresses data corruption as one of the hurdles for AI-driven systems.
He says, âIf you have complex and corrupted datasets, your understanding of the AI ââsystem would be just as complicated and corrupted. So it is important to pay attention to data. There are different facets of data as well as structured data. and semi-structured. It makes the data much richer and more mature. “
The second difficulty, according to Datta, is the unavailability of a custom solution that makes the process dependent on a generic solution that only fixes 90% of the problem. He says that the more data the AI ââsystem has, the better it is able to make better decisions. Thus, the AI ââinitiative and data analysis help the company to detect fraud.
Expanding on that, he says, “For each process, the data you ingest into the system is the most critical. When we put data into a system, the system analyzes it in various aspects. Let’s take the example of usage. AI in our fraud detection model. At Bajaj Allianz Life, we have a very mature fraud detection model through the data ingestion method in my AI system. The system reads customer data like demographics, education, financial background etc, and tells us a bit more up front about high propensity fraud patterns. So more data leads to better decision making for the bot. and so for the business. You push the new data set and based on that earlier understanding, this can give you a likelihood of fraud happening on each of the data entries. “
Today, companies are teeming with data solutions and are implementing AI-driven initiatives for better results and secure workflows. With the space open for the opportunity, Datta believes the possibilities for further improving AI for businesses and customers are immense and businesses will continue to invest feverishly in this direction.