And so you decided to leave academia in order to start a career in the financial sector?

Matthias Meul: "Quite so. At the time, my colleagues at university were primarily focused on researching whether one model had statistically better performance than another, up to a very minimal threshold. However, in the business world, the success or failure of a data science project isn't solely determined by statistical significance. It's about making practical changes, solving business problems, and improving processes' efficiency. Instead of pursuing an academic career, I started at ING and then with Deutsche Bank. Later on, I made a slight sidestep outside of the financial sector and worked for the National Lottery for four years. During that time, I was the only data professional behind e-lotto.be, an online gambling platform. It was fascinating because any analysis I conducted directly influenced our customers, and we could establish direct communication with them. In 2018 I transitioned to my current position as the head of a team of data scientists in AG Insurance's Corporate Marketing department."

What does your job entail exactly?

"We serve as a transversal support service for the three business units at AG Insurance: life, non-life, and employee benefits, as well as healthcare and other support services. We are there to assist the business units when they encounter a data science issue or when there's a need for insights that requires data crunching."

"On the one hand, we act as internal data science consultants, and on the other hand, we focus on piloting our end customers' insights: sharing the knowledge and deep insights about our customers across the organization. It's important to note that we typically don't have a direct sales model. We sell our products through a bank channel or brokers."

What attracts you in the insurance sector?

"The sector offers a wide range of financial services products and services. Almost everyone has one or more of these products. They play an integral part in people's lives and can make a significant difference. Insurance products, for example, help protect assets and plan for the future. The level of planning may differ depending on a person's age. Older individuals may focus more on succession planning, such as inheritance matters, while younger individuals may look into building assets and investment products. That variety and the overall impact on people's lives makes working in this domain fascinating."

"We strive to make it easy for our customers, which involves leveraging data to ensure our processes are as efficient as possible"

"At least as attractive is that the potential for utilizing data is virtually limitless. For example, we use data to continuously assess how we can improve care for our insured individuals. We also deal with car insurance, home insurance, and fire insurance, focusing on prevention. However, this is just the tip of the iceberg in terms of product-related initiatives. Additionally, customer satisfaction is of great importance to us. We strive to make it easy for our customers, which involves leveraging data to ensure our processes are as efficient as possible. We aim to provide relevant contacts and products that align with the customer's perspective. Ultimately, our goal is to meet the customer's needs and preferences. Data analysis is conducted with the customer in mind, rather than simply for the sake of data science. As a support unit, our primary focus is serving our internal customers and assisting them in achieving their goals. We also collaborate extensively with distribution partners. Using data, we aim to facilitate highly relevant interactions with these partners. The objective is to personalize the services provided by AG, tailoring them to individual customer needs and preferences."

What are the challenges in the sector?

"The most significant challenges are related to perception. While many people are insured, it's crucial to ensure they understand the products they have and the benefits they offer. We strive to prevent customers from perceiving insurance as something they merely pay for without receiving anything in return. It's important to gauge how aware our customers are of the products and increase their understanding through various applications."

What's the added value of Customer Insight Analytics? Would AG Insurance be a different company without you and your team?

"The team is relatively new, having been established around seven to eight years ago. We play a distinct role, since we operate at the transversal level. Our primary focus is providing data science consultancy. If a 'simple' report needs to be generated, it would be more efficient for a reporting team or a data person within the business unit to handle it. However, when specific data science expertise like building algorithms or delving deeper into existing data is required, we provide assistance. This often involves classification models, predicting future events, anomaly detection, fraud detection, and similar applications."

"Another key differentiating factor is our customer-centric perspective. We assist the business units in serving their customers even better by offering transversal customer insights. Together with the BU's, we strive to consider the entire customer experience, transcending individual contracts and distribution channels. By taking this approach, we identify opportunities and risks that may otherwise go unnoticed. Moreover, we focus on obtaining a comprehensive understanding of AG's customer base, including the number of customers, their distribution channels, multi-product relationships, age demographics, geographical locations, and other relevant factors. While we have made significant progress in this area, there is ongoing work to refine and enhance our understanding."

"Our insights are also utilized in our brand campaigns and supporting brand activations, such as sponsoring initiatives. To achieve an optimal return on investment for our marketing expenditures, it's crucial to understand our customers' demographics, interests, and residence."

After 5 years at AG as the Head of Customer Insight Analytics, do you see specific differences in customer behavior in insurance as compared to other industries?

"The differences in customer behavior in the insurance industry is influenced by the nature of the product. In our analyses, for example, car insurance tends to have lower customer loyalty compared to pension savings or products associated with employers. Compared to other sectors, it is not uncommon for customers to remain with us for decades, which is quite rare elsewhere. However, this presents challenges in terms of effectively communicating the added value, the importance of coverage, long-term planning, and selecting appropriate products. That, in my view, is the main difference."

Here we find ourselves at the intersection of behavior and data?

"The influence of non-exact sciences and data evaluation is something I consider important. In our analyses, we mainly focus on contractual data - information that people provide when they subscribe to our insurance contracts - such as age, location, and financial details. This data represents the core transactional truth. We see, for example, that people between the ages of 20 and 30 typically have motor insurance as a first pension product. Analyzing this data in various ways and gaining insights from it can significantly impact decision-making processes. However, it only tells part of the story. It doesn't provide insights into the reasons and factors driving customers' decisions. To uncover these motivations, it's necessary to conduct market research, which involves asking the right questions to a more limited group. So, in my interpretation, these two aspects complement each other. In my team, we strive to combine insights from different sources to ensure we draw accurate conclusions and take appropriate actions together with the BU's."

"When it comes to customer data and what is exposed to them, there is no compromise"

"While we have a vast amount of data, we are also mindful of data collection, quality, and governance. At the company level, there are dedicated teams and individuals involved in data governance and management to ensure awareness of the importance and to maintain adequate data quality. We have implemented a comprehensive program and specialized tools to ensure data quality is checked at the appropriate levels."

Are there any ethical standards or considerations you need to take into account when gathering customer insights?

"We have dedicated teams in cybersecurity and place great emphasis on data protection and privacy. We comply with legislation such as the European GDPR and strive to go above and beyond its principles. For instance, we hold regular meetings with the team to evaluate data retention, determining which data is still relevant and what is no longer needed. These principles are also applied within the business units to ensure compliance with data retention policies. Customer satisfaction and respect for their data are top priorities for us."

How do you see the role of Data Analytics evolving in insurance in the next few years? Do you see any role for new technologies?

"While artificial intelligence is currently a hype, it will move into a phase where practical applications become more prominent. In my team, we see the application of AI as a sort of co-pilot, where it enhances the work of data scientists and individuals. AI will increase the output and productivity of those using it. It can be used as a tool to identify errors in code or expedite project development, starting from a white paper and generating initial Python code. This has the potential to greatly enhance productivity by outsourcing tasks that can be automated and seeking efficiencies wherever possible."

"It is however crucial to exercise caution and be mindful of the information we provide to systems like ChatGPT. We should refrain from sharing confidential or sensitive information. While exploring the possibilities of AI, my team is encouraged to proceed with the necessary warnings and guidelines in mind, such as not sharing confidential data and carefully reviewing the output, considering the echo chamber effect."

"At AG Insurance, we focus on developing narrow AI models for specific goals like fraud detection and anomaly detection. Narrow AI, in my opinion, involves applying mathematical principles to a larger dataset with increased automation, leading to broader AI applications. As a team, we work on developing concrete AI applications, both internally within AG and for our customers. For instance, colleagues implemented chatbots and leverage AI to automate processes such as handling paperwork and hospital bills, ensuring efficiency and improved customer service. Through the development of a specific model, we contribute to achieve a higher automation rate."

"Data science should be seen as a tool to solve specific problems, and not as a universal solution"

"These advancements are not only aimed at enhancing internal efficiency but also have the potential to transform the insurance sector. Within AG Insurance, we consider the megatrends that are likely to impact the insurance industry in the long term. As we witness the rise of smart devices and the Internet of Things (IoT), automation possibilities increase. While exploring these trends, we must assess their relevance to the insurance sector and determine the appropriate stance to adopt. The IoT, for example, offers potential benefits in terms of prevention and personalized pricing. However, it is crucial to ensure data accuracy and compliance with regulations. Currently, there aren't many insurance products directly linked to IoT in the market, but there is potential for societal impact. For instance, IoT could assist elderly individuals in living at home longer or facilitate preventative maintenance for vehicles. One example within AG is our health partner, which takes care of organization's wellbeing needs from A to Z. This work aligns with the broader trends and discussions happening in AG's Think 2030, where we identify major trends like AI, the Metaverse, and blockchain."

The concept may still seem like science fiction, but do you explore the metaverse at AG?

"We aim to gain a thorough understanding of it by selecting a group of people to dive into it and explore its concrete applications. We don't want to limit ourselves to philosophical discussions without experiencing it firsthand."

How important is collaboration between insurtech companies and traditional insurance companies in driving innovation in the industry?

"Collaboration between traditional insurance companies like AG and insurtech firms is indeed a driver of innovation. However, it's not just about insurtech companies. It also involves partnerships with universities and leveraging their research and techniques efficiently."

What insights have you gained those past five years as Head of Customer Insight Analytics?

"That a crucial aspect of successful data science projects is having the right people involved. This includes a knowledgeable business owner who identifies the business problem, a data owner who manages the data needed to address it and a data scientist to determine the relevant data science techniques. It's also vital to have a deep understanding of the environment, strategy, and the customer-first approach. Data science should be seen as a tool to solve specific problems, and not as a universal solution. We act as gatekeepers, determining when an advanced data science model is necessary and when a simpler approach suffices."

"We strive to reach as many people as possible, even those who are not directly involved in data science"

"Ensuring the importance of data science and data-driven decision making is recognized throughout the entire organization is essential. We strive to reach as many people as possible, even those who are not directly involved in data science. We organize regular data science community meetups where we share successful and unsuccessful use cases, learnings, and best practices. This helps inspire and engage a broad range of data professionals within the organization. Our goal is to encourage everyone to think about how they can contribute to value-added work and identify opportunities for simplification and automation."

How do you see the role of data analytics evolving in insurance in the next few years?

"Data science will play a significant role in AG's growth. With millions of customers and contracts, understanding the business and extracting valuable insights from data is crucial. While it's impossible to have individual interactions with every customer, data enables us to uncover motivations and behaviors through sampling and analysis. Mastering data and gaining insights from it are key factors in comprehending and serving our customer base efficiently."

How will customers perceive the difference in your operations?

"The key aspects for me are relevancy and efficiency. Happy customers are those who experience correct and easily accessible services. They can experience quickly and accurately handled claims, and the communication they receive is relevant and personalized."

Matthias' data

• 2 / My 2 sons, the future generation.
• 2:43:19 / My personal record for a marathon that I set after a lot of hard work and planning.
• 68 / The distance (in kilometers) I was able to go in my most recent race of running as far as possible in 6 hours.
• 2.700.000 / The individual policyholders we serve every day.