Income Insurance’s Chief Customer Officer shares CX strategy

Image courtesy of Patrick Tomasso.

Against a backdrop of a digital ecosystem that is getting larger by the day, businesses — regardless of industry — are expected to put a premium on seamless and personalised customer experience.

For insurers, such as Singapore’s Income Insurance, one of the key challenges is maximising their customer data to tailor-fit solutions for their customers, whether they choose to be engaged online or offline.

To cover all bases behind the company’s CX strategy, Frontier Enterprise spoke with Dhiren Amin, Chief Customer Officer at Income Insurance, where he unpacks the tools crucial to their digital success.

How does Income Insurance leverage technology to improve the customer experience and differentiate itself in the competitive Singapore insurance market? Can you provide examples of how these initiatives have impacted the company’s business performance or customer satisfaction metrics?

At Income Insurance, our purpose is to put people first, and that is our north star in everything we do. It influences our product development, channel development, and technology, all of which are tools in the service of this purpose. Our use of technology starts with having the right data and analytics, which aid us in better understanding our customers through harnessing data from our customer base. This informs our marketing technology capabilities and their upgrades in the pursuit of a robust, single view of customers (SVC). The SVC is crucial as it provides a comprehensive and holistic representation of each customer, and it enables us to derive insights to better understand customers.

Dhiren Amin, Chief Customer Officer, Income Insurance. Image courtesy of Income Insurance.

Our focus is on creating a simple, usable, and constantly evolving SVC that acts as a repository for customer data. We enable its usage across various business channels such as agents, branches (offline), and website/app purchases. The customer purchase journey toggles both online and offline across different categories of insurance. For instance, life and health have a higher focus on offline engagement, while online is more preferred for purchases and service. Conversely, travel has a much stronger online journey from consideration to purchase to servicing.

Hence the next big role for technology is enabling a seamless online-to-offline-to-online (O2O2O) experience for customers using the SVC we have and tools that enhance the customer journey. Our technology stack helps us achieve this, and we are upgrading our capabilities in this area to provide better personalisation and customer service for each customer based on their preferred platform of interaction.

For example, by using predictive analytics, we can potentially identify policyholders who are most likely to lapse their policy and proactively offer measures to keep them engaged. This can ensure customer satisfaction, policy retention rates, and ultimately drive business growth for us.

The Real Care survey found that most people prefer to make the effort to show care in-person to someone who matters. How does Income Insurance ensure that its use of technology enhances — rather than detracts from — the customer experience and builds deeper connections with its customers? Please share specific examples of how Income Insurance uses data and analytics to inform its outreach strategy and provide personalised experiences for its customers. How have these efforts impacted customer experiences or driven business results?

The Real Care survey further proves that Singaporeans feel care is care regardless of the platform, be it in-person or digital, and the perception of care differs across generations. Insights such as these can help us to develop more tailored solutions and services while balancing the use of technology for seamless engagement.

Currently, we leverage data and analytics to personalise the customer experience and offer tailored products and services to our customers. Below are some examples:

  • Behaviour-based solutions: Through data analytics, we assess the risk profile of individual customers and determine the appropriate level of coverage and pricing for them. By analysing data such as their age, health-related metrics, and even driving habits, we can offer behaviour-based products that meet the specific needs and preferences of each customer. An example is Milesurance, a pay-as-you-drive motor insurance where we are tapping on an innovative way to collect data more seamlessly, such as kilometres travelled, to provide more tailored offerings.
  • Predictive modelling: One example is our auto-underwriting engine for our IncomeShield business. Our reflexive underwriting capabilities ease the completion of medical questions by IncomeShield customers. For instance, if a customer declares a previous bone fracture, the engine will not ask if the condition is cancerous or non-cancerous. With this auto-underwriting engine, our customers have saved up to 80% of the time usually taken to answer health-related questions during the application process.

    Over the next five years, we can expect the growth in predictive underwriting models, where we analyse customer’s financial, lifestyle, and behavioural data, as well as demographic data, to derive more tailored and simplified underwriting questions. This will depend on the availability of big and clean data, as well as capabilities like AI, ML, and natural language processing, which Income Insurance is starting to review and build.
  • Audience segmentation: We use data analytics to segment our customer and audience base and identify patterns and trends in customers’ behaviour. We have identified four key segments at Income — young adults, independent adults, parents and seniors — and ensure that the products and services recommended to them are relevant to their life stage. For example, if a new parent were to look up parenting articles on our Income blog, we would then propose products for consideration knowing that they are new parents or parents-to-be.
  • Customised matching of advisors and customers: Data and analytics are also used for propensity modelling of leads, where we match financial advisors to potential leads based on the type of insurance they are looking for.

Could you speak about any challenges or opportunities that Income Insurance has faced in adopting new technologies like AI and ML? How have these technologies impacted interactions with customers and other stakeholders?

At Income Insurance, we are committed to reimagining insurance by constantly innovating and adopting new technologies like ML and AI to streamline our work processes. However, we also understand the importance of maintaining a human-centred approach and placing people first in all that we do.

Here are some examples of how we are using ML and AI at Income Insurance:

  • Claims assessment and processing: We leverage ML and AI to streamline our claims processing, including being the first insurer in Singapore to use deep learning (VISION AI) to assess windscreen damages for motor claims. With VISION AI, we can automate the damage assessment process, significantly reducing the risk of human error and saving on man-hours. We plan to expand the use of VISION AI for assessing other types of damages in the near future, such as those to other parts of the vehicle or even damaged luggage for travel claims.
  • Enhancing the customer experience: We are piloting a Voice of Customer program that uses AI, voice analytics technology, and sentiment analysis tools to measure and gauge the customer experience down to the episode and touchpoints. This will help us intervene in close-loop actions and ensure that we are providing excellent service to our customers.

One of our biggest challenges is syncing data from offline to online in real time and tapping into clean historical data to enable more accurate use of ML.

How have technology innovations helped Income Insurance attract new customers? Please provide examples, and explain how this initiative aligns with the company’s overall strategy and goals.

More than five years ago, we started working with digital solution provider ZA Tech. As part of this collaboration, we were able to leverage ZA Tech’s deep technological expertise and knowledge to create a highly scalable insurtech platform, which kickstarted our capabilities in working with ecosystem partners in Singapore.

Our proofs of concept across AI, blockchain, and automation technologies keep us ahead of the curve in our industry. By modularising insurance, we were able to reimagine insurance and create innovative propositions via microinsurance to target new customer segments.

For example, SNACK, our lifestyle-based stackable insurance and investment platform, allows users to contribute bite-sized premiums from as low as SG$0.30 as they go about their daily lives via lifestyle triggers such as taking public transport or watching a movie. This unique proposition has gained traction amongst digital-first consumers such as first jobbers and gig economy workers.