Tom Gerritsen is Group Head of Data Analytics for AIA Group, leading the execution of the Group’s overall data analytics strategy. Tom has a data analytics background primarily in the banking and insurance industry and in a career spanning over 20 years he has worked at Fortis, Aegon, Rabobank and Amazon on multiple continents before joining AIA. rice field. He has grown from a marketer to a data expert with a focus on using data-driven models for sales, marketing and business operations to deliver tangible results, adding value to both customers and businesses. focus on how to
In an exclusive conversation with us, Tom shares his thoughts on how data analytics can empower the insurance industry and steps towards smarter data usage in 2023 and beyond. doing.
According to a recent Salesforce study (here), business leaders struggle with putting data into action to make strategic decisions faster. What steps would you recommend for dealing with this conundrum?
One of the first things you need to do before putting data into practice to make strategic decisions faster is to develop a comprehensive data strategy. At AIA, our comprehensive long-term business strategy to drive digital transformation is our corporate strategy, Ascend 200.
The sheer amount of data can be daunting. Therefore, providing high-quality, accessible data in the right format, on the right platform, to the right people is critical for business leaders to understand data and make strategic decisions. that.
The fact that data is driving the critical decisions that drive business strategy has far more impact than the technology transformation that accompanies the data usage strategy. It also makes the whole process easier for major business his leaders to accept.
The pace and scale of transformation will accelerate as companies realize the benefits of using data throughout their processes, and how analytics and AI can drive efficiency and productivity and improve customer experience.
At AIA, the digital transformation of the past two years has been achieved by putting analytics and AI at the center of everything we do, implementing centralized governance, and sharing best practices across the group and individual business units. rice field. We continue to deepen and industrialize the use of AI and analytics across the Group, with a total of 235 high-impact use cases deployed since 2021, including 111 in 2022.
How can data analytics help the insurance industry and agents better serve their diverse customer base?
Data analytics is a powerful tool for the insurance industry and agents to better serve their diverse customer base. It helps insurers and agents better understand their customers, develop more accurate pricing models, and create personalized products and services that meet the needs of a diverse customer base. We believe that the benefits of data analysis are prominent in:
Transforming the agency experience:
- Leveraging AI is effective in recruiting and training agents, and supports agent sales and performance management. Taking AIA as an example, 80% of his agents have been enrolled in his 2022 on iRecruit, our digital recruitment platform.
- AI helps match the right agents with customers, and analytics gives agents data-driven insights to help them sell better, more customized products. The use of analytics and AI has improved lead quality with nearly 30% more leads for him in 2022 compared to 2021. Agents treat customers as individuals rather than numbers and are better prepared to provide more customized and relevant service to them.
Drive customer complaint speed and efficiency.
- Automate straight-through processing (STP) of purchases, services, and claims to take the worry out of the claims process and enable faster customer reimbursement, claims, and responses. This makes customers feel they are provided with timely and relevant tools and insights.
- By December 2022, 63% of AIA claims will be resolved on the same day, 93% of claims will be paid digitally, 70% of all customer interactions across 18 markets will be STP, and the insurance industry will is the best in This improves the overall customer experience while reducing the risk of fraud, waste and abuse (FWA).
How can businesses use generative AI tools to enhance customer engagement? How is AIA doing it?
AI is revolutionizing the business sector by making customer interactions faster, more efficient, and more personalized. I feel provided with timely and relevant tools and insights. Generative AI could ultimately bring the distance between every customer interaction. Within companies and their networks, it leads to the need for customer engagement at every touchpoint of customer interaction. This presents unique challenges and great opportunities for customer privacy.
With the advent of effective and accessible AI-powered tools, organizations are eager to implement AI to accelerate work processes.
AIA has over 230 analytics use cases including machine learning and AI, testing the capabilities of generative AI. In 2023, we plan to build on these foundations to become a fully data-driven organization with a particular focus on developing automated underwriting, contact center robots, and voice/chat-free text analytics.
For example, in terms of operations, we are looking at generative AI to analyze free-text customer feedback for AIA Connect, a customer app in mixed Chinese and English. When it comes to distribution, we are looking to improve lead generation and sales with SIM, a social media tool. Generative AI could potentially automate the generation/suggestion of personalized human-like her SIM messages and responses.
Over the past few years, AIA has developed these technologies to better serve its customers. We have launched empathy bots like Xiao Bang, his AI-powered voice robot, in mainland China. It handles outbound his calls and complex two-way his 24/7 conversations with an expanding portfolio of applications that anticipate customer needs to reduce hassle and wait times.
AI is transforming interaction and expanding access at a miraculous pace, but importantly humans are providing protections to build trust. AI, data analytics, and humans will build the future of the industry.
Nearly a third (30%) of business leaders are overwhelmed by the amount of data expected to more than double by 2026.
This challenge is especially exacerbated for multinational companies, where the aggregation of data from diverse customer bases can be overwhelming. Therefore, both centralized governance and a local business empowerment model are key to our success. Companies should hold regular review meetings between headquarters and each market to discuss progress and challenges at the operational level, and foster close collaboration by sharing best practices and immediate support when needed. should be promoted.
Multinationals also need to make sure their customers are at the forefront of this data explosion. A disproportionate amount of effort must be put into protecting customers from this surge within organizations and ensuring that they only engage based on need, relevance, and immediate action. This allows organizations to focus on using the data they need most, rather than falling into the trap of trying to use all available or generated data.
Business leaders track analytics and AI to create analytics impact KPIs that prioritize, incentivize, and engage analytics within their organizations to ensure broader business adoption is needed. Impact KPIs help broaden the rise of analytics across all business units and open more opportunities for analytics implementation. For example, AIA Korea’s AI invoicing solution helps them process claims directly, which is measured as a key KPI.
Business leaders should encourage a culture of testing and learning. Business and IT teams should test implementations of technologies such as generative AI, blockchain, Web3, and the Metaverse to actively explore customer and business value.
Analytics teams must be independent enough to work closely with the business, but they have their own responsibilities. Having your own budget for research and development is also a way to accelerate innovation.
Finally, what advice do you have for CIOs and CDOs to make their data work smarter in 2023 and beyond?
At AIA, we believe that the combined power of technology, digital, and data analytics guides us in systematically transforming into a more customer-centric, world-class, digital-enabled organization. The future of technology is exciting with emerging phenomena such as generative AI, Web3, and other decentralized platforms. All of this relies on smarter ways to use data.
We believe the consumerization of search and knowledge management is likely to happen over the next decade, driven by the capabilities of generative and conversational AI. Competition for talent is heating up as the life insurance industry and the skills needed to stay at the forefront are evolving rapidly and show no signs of slowing down.
CIOs and CDOs need to ensure their companies have the best talent across the region, from cloud specialists, data scientists and analysts to UX/UI designers. Upskilling and training are essential to keep employees equipped with the knowledge to leverage analytics and AI to transform workflows and processes at a breakneck pace.
To achieve this, there are two analytics training programs established in 2022 to support employee upskilling. A dedicated Analytics Academy equips employees with analytical skills, and the Analytics Leadership Program empowers senior leaders to effectively drive youth cases and identify additional opportunities. To date, he has had over 410 people participate in the program.
