Future Generali Life has a five-point agenda for technology transformation, informs CTO Byju Joseph

In 2017, a five pillar agenda was created based on the business – technology alignment. The agenda was named as ‘Drive towards the ambitions of 2020’. EC’s Abhishek Raval speaks with Byju Joseph, CTO, Future Generali India Life Insurance

What was the five point agenda decided upon at Future Generali India Life to bring about business transformation through technology?
In the last four years, the customer service has been automated to a large extent. This ensures guaranteed delivery of what the field team commits to the customer. The company has also undergone a massive operational rationalisation and digitisation, for our sales team to deliver whatever they commit on behalf of the company. A combination of technologies has been used to reduce the human touch points in order to serve the customer. In 2017, a five pillar agenda was created based on the business-technology alignment. The agenda was named as ‘Drive towards the ambitions of 2020.’

1. Automate and transform: To use every opportunity to automate for bringing transformation
2. Digitise the salesforce, customer and omni channel experience
3. Enable big data: Help the sales force to interact with the customer in an informed manner
4. Cyber security
5. Interaction with InsurTech companies for solving specific problems

Please tell us about your partnership with the startup companies.
The core theme behind partnering with startups is to disrupt the company from within in order to empower the company to deliver the customer with whatever is asked for, in a swift manner. We have partnered with a startup company in the area of automating and adding cognitive features in the customer touchpoints; for example, the startup helps the customer to get the fund value of his policy without any human interaction. This is done over a platform provided by Microsoft. They are strategically aligned with us in terms of the IT ecosystem, which is based on Azure.

The cognitive bot has Machine Learning (ML) and Natural Language Processing (NLP) capabilities, built on Microsoft Luis. These capabilities will be available on the website, mobile app, Facebook Messenger, Twitter, Cortana, Amazon Echo. In the first year, the target is to handle 10 per cent of the call centre workload. Another six per cent of call centre volume will be reduced by automating about 12-13 policy servicing needs. The objective is also to reduce the increased drop rate on the website. The email responses will also be sent by the bot, but for the initial months, a human will evaluate and edit them, post which, a return email will be sent. For example, a customer mail asking for fund value of the policy will be automatically replied after the bot, pulling information from the policy information system and the human checking it. The bot will also learn the changes made in the mail by the human and will redraft a similar queries in the future, with adequate application. The bot supports English, Hinglish and Hindi (written in English). The name of the virtual assistant is Robotic Enabled Virtual Assistant (Reva).

In the test run, we have found out 13 most common customer service requests, which can be solved without any human intervention: fund value, premium amount, renewal date, etc. These are the requests that come when the policy is close to expiry. During tax filing, customers ask for certificates, payment acknowledgment, unit statement, policy document, etc. Many companies charge for new policy document if it is lost; we give it for free in a soft copy form. Many customers also ask for loan against the policy value; the bot also enables renewal payment. Most of these are from the top 13 most asked queries and they have been successfully tested both on the ‘conversation’ and the ‘menu’ mode.

The Microsoft Bot platform is used for information dissemination to the customer service staff. This is available to the company’s internal staff. Soon, this service will be made available to the customers.

We have adopted an open approach, wherein the bot will follow certain company set processes to service the customers. This is because our Net Promoter Score has been consistently high compared to other life insurance players.

Which initiatives have you taken to strengthen your salesforce?
Overall, Future Generali has a strength of 12,000 partners sourcing business for the company. It includes agency, direct sales channel, bancassurance, etc. We have set up a omni channel platform for the sales force to service and sell the policies on their tabs. The omni channel experience is designed for ‘Assisted Mode’. The app on the tab is framed such that the sales executive can propose a need-based policy to the customer in front of him after considering all the necessary factors as per the regulation. It’s important to note: ‘Need based selling’, because mis-selling of insurance is a big issue facing the industry; technology allows right selling. In under 20 minutes, the policy document can be emailed, sent on WhatsApp or dispatched to the customer in an electronic format. Following the IRDAI guidelines, a physical copy is also couriered to the customer.

Moreover, the tab also enables customer servicing using the inbuilt biometric authentication features. The sales force has begun using these tabs from May 1, 2018. The complex products are sold through the assisted mode, while the simple-to-understand products are bought by the customers using the self-service mode – the customer is routed to the online channel or is asked to download the app and then fill in the fields. There are various reasons for keeping separate channels for assisted mode and non-assisted mode. The regulatory provisions, the pricing of the policy is different in a self-service mode because it is sans the sales commission already accounted in it.

We did the testing with the tabs for two months, in February and March. The results were encouraging: Four customer touchpoints and six process steps have been reduced (because of the paperless process); it’s a predictive model, the customer has the visibility on when will he get the policy, similar to the e-commerce model; the sales closing time has been reduced to 20 minutes; 70 per cent of the customers who bought the policy using the digital mode were satisfied. The eKYC helps us to eliminate the paper based processes altogether.

Please elaborate on the journey on data monetisation.
It has been five months since we began the journey of data monetisation. The idea is to come up with life insurance policy offers based on the huge retail data from Future Retail, another Future Group company. Compared to the retail data, the life insurance data is miniscule. The example of the offer can be the following: The customer buying products for a newborn baby can be a potential candidate for child policy or a family policy.

A big data infrastructure has been implemented containing the structured and unstructured data. The structured data includes the insurance data, and unstructured data has the customer emails, Net Promoter Score (NPS), conversations with agents, complaints filed etc.

We are using the data of future retail and have coined innovative promotional campaigns with it. E&Y is helping us execute this project. The persistency of data, the propensity to pay, the logistical regression is done to get the data outcome and then digital campaigns are run. The campaigns are fine tuned on a regular basis.