Tom Gerritsen is Head of Group Data Analytics at AIA Group, leading the execution of the group-wide data analytics strategy. Tom has a background in data analytics, predominantly within the banking and insurance sectors, having worked for Fortis, Aegon, Rabobank and Amazon across multiple continents before joining AIA in a career spanning more than 20 years. With a focus on the use of data-driven models for sales, marketing and business operations to deliver tangible results, he has developed from marketeer to data expert keeping a sharp focus on how to add value to both the customer and the business.

In an exclusive interaction with us, Tom shares his thoughts on how data analytics can empower the insurance industry and steps for smarter data utilisation in 2023 and beyond.

As per a recent Salesforce Survey (here), business leaders are struggling to put data into practice to quickly make strategic decisions. What steps do you recommend towards addressing this conundrum?

One of the first things that needs to be done before putting data into practice to quickly make strategic decisions is to have an overarching strategy around it. At AIA, the overarching long-term business strategy driving our digital transformation has been our corporate strategy – Ascend 200.

The vast amount of data can be daunting, that’s why making sure that having quality and accessible data in the right format, on the right platform, and delivered to the right people are crucial for business leaders to make sense of and make strategic decisions out of it.

The fact that data is driving the key decisions that power the business strategy makes it much more impactful than just having a technology transformation with a data usage strategy. It also makes the whole process more acceptable to key business leaders

Once businesses recognise the benefits of using data throughout the whole process, and how analytics and AI drive efficiency, productivity and improve customer experiences, the pace and scale of transformation accelerate.

At AIA, our digital transformation in the last two years was achieved by putting analytics and AI at the heart of everything we do and introducing centralised governance and sharing of best practices between the Group and individual business units. We continue to deepen and industrialise the use of AI and analytics across the Group, with a total of 235 high-impact use cases implemented since 2021, including 111 deployed in 2022.

How can data analytics empower the insurance industry and agents to better serve the diversified customer demographics?

Data analytics is a powerful tool for the insurance industry and agents to better serve diversified customer demographics. It helps insurance companies and agents better understand their customers, develop more accurate pricing models and create personalised products and services that meet the needs of a diverse customer base. We figure that the benefits of data analytics are noticeable in:

Transforming the agency experience:

• Leveraging AI is effective in recruiting and training agents to support them with selling and helping them manage performance. Taking AIA as an example, 80% of agents were onboarded by iRecruit, our digital recruitment platform in 2022.
• AI helps match the right agents with customers, and analytics arm agents with data-driven insights to help sell better quality, more tailored products. The use of analytics and AI increased leads by nearly 30% in 2022 compared to 2021, and the quality of leads improved. Agents are better equipped to provide customers with more tailored, relevant services, treating them as individuals, not a number.

Drives speed and efficiency for customers’ claims:

• The automation of the Buy, Service, and Claims straight through processing (STP) relieves anxiety over the claims process and enables immediate coverage, claim, and response for customers. It makes customers feel that they are being served with tools and insights that are timely and relevant.
• By December 2022, 63% of AIA’s claims were settled on the same day, 93% of claims were paid digitally and 70% of all customer interactions across 18 markets are STP, the highest in the insurance industry. This is improving the overall customer experience while mitigating fraud, waste, and abuse (FWA) risks.

How can businesses enhance customer engagement with generative AI tools? How is AIA doing that?

AI will revolutionise the business sector as it makes interactions with customers faster, more efficient and personalised; individuals feel they are being served with tools and insights that are timely and relevant. Generative AI is likely to ultimately narrow the distance between all interactions that customers have eg. with the companies and within their networks, leading to a need for customer engagement across all touch-points of customer interactions. This will provide unique challenges around customer privacy as well as an immense opportunity.

With the emergence of effective and accessible AI-powered tools, organisations will be eager to implement AI to accelerate their work processes.

AIA has 230+ analytics use cases, including machine learning and AI, and we are testing generative AI’s capabilities. In 2023, we are building on these foundations to become a totally data-driven organisation with a specific focus on developing auto-underwriting, contact centre robots, and voice/chat-free text analysis.

For example: for operations, we are looking at generative AI to analyse free-text customer feedback of our customer app, AIA Connect, which is a mix of Chinese and English. For distribution, we look at improving prospecting and selling with our social media tool, SIM. Generative AI can potentially automate personalised human-like SIM messages and response generation/suggestions.

Over the past few years, AIA has developed these technologies to better serve customers. We have launched empathetic bots like Xiao Bang, an AI-powered voice robot in Mainland China, to handle outbound calls and complex two-way 24/7 conversations with a growing portfolio of applications that anticipate customers’ needs to reduce hassle and waiting time.

AI is transforming interactions and broadening access at a miraculous pace, while importantly human beings provide safeguarding to build trust. AI, data analytics, and humans will forge the future of the industry.

Almost one-third (30%) of business leaders are overwhelmed by the amount of data, which is expected to more than double in size by 2026. What best practices do you advocate for organisations to utilise data amidst data bombardment?

The challenge intensifies especially for multinationals as the aggregate of data from a diversified customer demographic can be overwhelming. Therefore, a centralised governance and local business empowerment model are both keys to our success. Businesses should hold regular review meetings between headquarters and each market to discuss progress and challenges at a working level, as well as to facilitate close collaboration by sharing best practices and instant support if needed.

Multinationals should also ensure that customers are at the forefront of this data explosion. A disproportionate amount of effort should be towards protecting the customers from this explosion at the organisation, and ensuring that customers are engaged on need, relevance, and immediate action basis only. This will also ensure that the organisation is able to focus on data usage where it is needed the most, without getting into the trap of trying to utilise every bit of data available or getting generated.

To keep on track, and ensure wider business adoption of analytics and AI, business leaders should create analytics impact KPIs that prioritise, incentivise, and glamourise analytics within the organisation. Impact KPIs help spread the rise of analytics among all business units, and open up further opportunities for analytics implementation. For example, our AI Claims solution in AIA Korea is helping us process claims straight-through-processing and is measured as a key KPI.

Business leaders should also encourage a culture of test and learn, with business and IT teams testing technology implementations – such as generative AI, Blockchain, Web3, and Metaverse – to proactively explore the value to the customer and business.

Analytics teams should have enough independence to work closely with the business but have their own responsibilities. Having their own budget for R&D is also a way to accelerate innovation.

Lastly, what will be your one go-to advice to CIOs and CDOs for smarter data utilisation in 2023 and beyond?

At AIA, we believe the combined power of technology, digital, and data analytics forms a guiding principle that helps us systematically transform into a more customer-centric, world-class, digitally-enabled organisation. The future of technology is exhilarating with emerging phenomena like generative AI, Web3, and other decentralised platforms, all of which rely on smarter ways to utilise data.

We see that consumerisation of search and knowledge management will likely happen over the next decade, driven by generative and conversational AI capabilities. The life insurance industry and the skills required to stay at the forefront are evolving rapidly and show no signs of slowing down, hence the competition for talent is massive.

CIOs and CDOs should make sure the company is equipped with the best talents across the region from cloud specialists, data scientists, and analysts, to UX/UI designers. Upskilling and training would be vital to keep employees refreshed with the knowledge to leverage Analytics and AI, in order to transform its workflows and processes at a miraculous pace.

To achieve that, we have two Analytics training programs established in 2022 to support upskilling of employees. The dedicated Analytics Academy is equipping employees with analytics skills, and the Analytics Leadership Program is enabling senior leaders to effectively drive use cases and identify additional opportunities. More than 410 individuals have participated in the programs to date.