Aviva Quantum, Aviva’s Global Data Science Practice has been making a lot of development with a focus on customer analytics, risk analytics, claim analytics, and more. Leading the Asia hub as head of Aviva Quantum is Anshu Raj who is responsible for building and developing data science expertise in Aviva Asia. Having worked in the field for more than 12 years, Raj says that he started his career in the insurance space and quickly found a passion for analytics, and there has been no looking back ever since.
Throughout his career, Raj has achieved milestones such as formulating data strategy and spearheading the setup of state-of-the-art data science infrastructure. However, he’s extremely proud of his role in the creation and development of Aviva Quantum Asia Hub.
Anshu Raj, Aviva Quantum
“I was able to create a world-class Data Science function coupled with cutting edge tech stack to deploy AI solutions that creates real value, at scale. My team has grown multiple folds in a very short period of time, adding phenomenal value to the greater Aviva business not just locally, but within the region as well.”
Anshu Raj shared with Analytics India Magazine.
In this candid chat, he talked about how AI is the heart of all that they do in Aviva Quantum, how analytics has proved crucial for customer retention, the importance of partnering with universities to stay ahead in the data science domain, and more.
Analytics India Magazine: How is Aviva using analytics for customer retention and acquisition?
Anshu Raj: At Aviva, Customers are at the heart of everything we do. To that extent, we have built an AI-powered recommendation engine called “ADA” (Algorithmic decision agent) which gives the products our customers are most likely to buy ranked by probability. This model is the core of our customer cross-sell and up-sell activities.
With respect to customer acquisition, we are working with our digital marketing team to use AI-powered Multi-Touch Attribution Modelling to optimize marketing spend on the right channel(s) to maximise uplift on ROI. In addition, we work with our distribution function to allocate the right adviser to sell the right product at the right time to leads coming through our digital channels.
AIM: What are the other areas where Aviva is adopting analytics? What have been the benefits of analytics adoption? Please highlight with use cases.
AR: We embed analytics into each and every aspect of Aviva’s Insurance value chain from pricing to underwriting to recruitment, at scale. The benefits have been sales uplifts, reduction in loss ratio and an overall increase in customer satisfaction. Some use cases include the following:
- Building a smart, automated underwriting engine using AI to process medical reports and application forms to improve straight-through processing rates
- Enhancing health insurance pricing by predicting readmission rates through AI
- Improving the efficiency of claims team by automating claims settlements through reading claim documents, processing and predicting optimal claim settlement amounts
- Optimising the adviser recruitment process by predicting sales potential and expected tenure be leveraging on psychometric data and machine learning.
- And many more!
AIM: What are some of the challenges of setting up an analytics function in an organisation?
AR: The key challenge is to set up a data infrastructure that aligns the organisation’s data strategy to the broader corporate strategy. This infrastructure has to enable data scientists to work in an Agile manner, prototype fast and deploy at speed and at scale.
Another challenge is to find the right talent for the analytics function. Even if we can find someone with very good technical knowledge, we may not find the right domain knowledge. Functioning as an internal consultancy, our data scientists, engineers and actuaries must be able to explain the intricacies of complex models and communicate the value that it brings to the senior leadership team.
Also, analytics has many different workstreams and an organization needs to make sure all the skillsets are present in the analytics function. It cannot be only focused on one area. For e.g. in insurance space, we need to make sure analytics function have all the skillsets such as risk analytics, actuarial exposure, customer science, digital analytics, data engineering etc.
AIM: There’s a huge competition in this space. How do you keep up with it? How does the adoption of analytics play a key role here?
AR: The key is to evolve and continually learn. Within analytics, there are always new techniques and tools being created to further utilise the data we have available to us. Another key aspect is having ties with Universities who are teaching students about these latest techniques, and over the years we have had many interns join us to help spread their knowledge across the team. Aviva Quantum has a partnership with Cambridge University which equips us with unparalleled access to knowledge and research in data science.
I’m also a keen advocate of attending seminars, webinars and conferences and I’ve done a number of talks for various conferences in Singapore where I’ve both shared insights on what Quantum has been working, gotten ideas of how we can develop our inhouse capabilities further and shared thought leadership on how AI can be used to reimagine Insurance from the ground up.
AIM: What does the unit Aviva Quantum do? How is it different from other functions in the organisation?
AR: Aviva Quantum is Aviva’s global data science practice. It was established 2 years back to bring all the data scientists in Aviva globally under one umbrella in order to transform insurance and bring material impact at each stage of the insurer’s value chain. Aviva Quantum is not an R&D hub but a fully embedded function within our business. Every initiative is sponsored by a business leader and the project outcomes are measured and evaluated as any other project. Hence, it becomes important for us in Aviva Quantum to deliver projects which brings a tangible benefit to the business
AIM: How has analytics disrupted the insurance sector over the last few years?
AR: Analytics has given the insurance industry a whole new set of lenses that allows insurers to study, understand and empathize with customers and distributors like never before. The unprecedented level of insights allows the industry as a whole to move faster, go further and do better at everything from pricing to distribution to customer service or in other words covering the entire value chain.
AIM: How is its growth in the Indian market?
AR: My perspective is that the growth of analytics in insurance in the Indian market is extremely good. I started my data science journey more than 12 years back in India and since then a lot has changed. One of the key visible change I see is the buy-in from senior management and the recognition of analytics in bringing material business value. Also, the talent pool of data scientists and data engineers have increased significantly. A lot of specialized AI start-ups have helped in increasing the talent pool.
