At its heart, insurance is about protecting people – but when dealing with thousands of people and countless variables, the insurer’s most valuable tool is data. Whether they are data analysts or data scientists, information professionals play a major role in determining an insurer’s future policies and products.
We spoke to Darren, a former short-term assignee in AXA Singapore’s Data & Innovation (D&I) team and Jayden, a current member of the team to understand their roles in the company.
One of the key roles of data is to help management make better, faster decisions. The Life Actuarial Database and Life Transactional Database, for example, help to create a one-stop source of reference and verification for AXA.
Darren and Jayden, along with other members of the D&I team, were responsible for the creation of the databases.
“From these databases, we aim to improve efficiency within the company by streamlining the majority of the reports (e.g. daily sales report). Potentially, we could save more than 500 man-days in a year,” they said.
Data development has also improved the daily sales report, to give management an edge. Darren said, “We recently pushed the daily sales report to production, giving our management an automated dashboard on the amount of sales we bring on a daily basis. This dashboard can be used to understand our sales trends, and help management make better, more informed decisions.”
Insurers are inundated with customer calls and requests. From policy queries and claims processing to simple feedback, insurers deal with thousands of interactions on a daily basis. It’s all part-and-parcel of being a people-oriented business.
This is primarily handled by Financial Advisers, customer service representatives, or call centre operators but it is also an area where data teams can potentially play a crucial role.
Jayden and his team, for example, worked to improve customer experience through data analytics. “During the recent Data and Innovation Hackathon, my team worked on Customer Feedback Transformation topic. We used sentiment analysis and topic modelling on customer feedback data, which let us create a dashboard to (hypothetically) analyse customer satisfaction and better serve our customers.”
According to Darren, the algorithm behind this Hackathon project enables differentiating between positive and negative feedback, and identify which part of the business the feedback is referring to.
Broadly speaking, sentiment analysis is the analysis of data to determine the emotional tone behind a series of words, such as identifying anger or satisfaction. Topic modelling helps to make sense of large quantities of data, such as from thousands of customer feedback responses or social media posts.
Jayden explains that data plays a key role in all areas, from customer experience to marketing: “In terms of data analytics, you can find it present in many aspects of your daily life. Whenever you visit an ecommerce site repeatedly, you get various product recommendations. On social media sites, you get suggestions ranging from friends to news topics. This even happens offline. You may have received a promotional letter to purchase new add-ons for your current phone plan. Often, this is the result of data analytics.”
Darren and Jayden joined the D&I team from different backgrounds. Darren was previously from the Life Actuarial team, while Jayden started in the Retail Product and Pricing team.
“Being from the Life Actuarial team, I worked with Data frequently. This developed my interest in data. In 2018, I joined the D&I team on a 6 months short-term assignment to learn and improve my data programming skills,” said Darren.
Jayden joined the data team to upgrade his technical skills, as part of a long-term career move. “Coming from an Economics background, I was interested to explore and learn the domain of predictive data analytics within an organisation. At the same time, I saw this as an opportunity to improve my technical skills, which is vital at this early stage of my career.”
Since joining the D&I team Jayden has picked up various key data skills that range from data cleaning to data analytics and machine learning. He has also learned two programming languages, SAS and Python.
Darren also learnt SAS programming, and the two have improved project management and communication skills, as well as domain knowledge in insurance.
It helps that today, there are abundant resources for those looking to move into data. Besides in-house mentors and team support, numerous learning sources are available to ease the transition.
Darren says he definitely learnt a lot from the people on the team, by working on his projects and also by reading SAS books from the library and watching YouTube videos on weekends.
Jayden’s approach was broadly similar: “I read up on SAS and Python programming from various sources including books to online resources such as Coursera and YouTube. To better understand data science topics, I learnt from others on Kaggle, an online community for Data Science projects and competitions.
Within the team, I had experienced mentors who helped me with my questions. In addition, the daily work I do gives me a hands-on opportunity to synthesise the concepts I have picked up.”
With data identified as the next wave of innovation in insurance, now is the right time for anyone in the industry to familiarise themselves with it. At the very least, it pays to understand how data will impact your work in terms of underwriting, customer interaction and overall business management.