We are the flywheel: not big, but able to set everything in motion
Interview with Greg Tisson, Head of Data Management at Athora Belgium
Physicists in the insurance world are not that common, let alone doctors in physics. Head of Data Management at Athora Belgium, Greg Tisson, traded in his academic universe as a PhD for a career in banks (BNP Paribas Fortis, ING Belgium) and now a pure life insurer. "While data management may be a new discipline within Athora, it leads straight to the essence of the business and impacts all levels of the organization. What gives me a lot of energy is that my mission transcends 'data', we really need to kick-start a change."
His PhD in physics at the University of Antwerp focused on medical imaging, specifically on mathematical models to improve medical reconstruction techniques, such as those used in CT-scans. Not only the medical, but also the financial world was keen on the likes of Greg Tisson. The period is significant, as it was 2006, two years before the global financial crisis that resulted from the bankruptcy of Lehman Brothers. "The sky was still the limit," Greg Tisson recalls, "and banks were looking for people with my profile, especially to go to the trading floors and use mathematical modeling to outsmart the market."
That call didn't fall on deaf ears?
Greg Tisson: "It sure didn't. Also because I wanted something different than the purely academic world. That's how I got in touch with BNP Paribas Fortis - then still Fortis - and ended up in business intelligence. Essentially, it came down to centralizing and getting tons of data in order. We had to ensure that all the different stakeholders within that big bank got their information. There were discussions on the quality of data for sure (genre: 'I have to create a report for client Y, but I'm getting 'dirty' data from you') but at the time it wasn't yet about data governance, about who was responsible for the quality and management of that data. That's what I'm doing here at Athora now."
"Also at BNP Paribas Paris, I worked as an international auditor for some time and in that role I also got to know myself better. As an auditor, you map out all possible risks and put them in a report with an action plan. However, auditors cannot be part of the implementation. And that's exactly what I liked most: working with people and thinking about processes, systems, data. To change and implement things. And that too is what I do here at Athora now."
You are the very first Head of Data Management at Athora Belgium.
"That role is indeed new because Athora realizes that it is a new capability that needs to be developed. Not only insurance companies, but almost all companies recognize that data is the new gold, to repeat the cliché. But with data, you bring a company back to its bare essence, which is what attracts me to it."
"This new role is an opportunity, but frankly also an obligation due to regulatory constraints. The National Bank of Belgium imposes strict requirements on banks and insurers regarding data quality and financial reporting. In addition, you also have the GDPR legislation which made it clear to the business world that they were working with personal data and that it had to be protected. In that context, Athora defines new roles and responsibilities - it's that process, among others, that I facilitate. Only when that is clear, we can take the next step, look at what our requirements are and how we link our data management story to our strategy."
What is the significance of the Head of Data Management within Athora?
"At this moment, my role is less significant than when I started at Athora five years ago - when it was still Generali. Then, as a manager of the Transversal Projects & Processes team, I had to manage all the strategic projects by putting the right people on the right places, and at the same time I still had process analysts from my team carrying out typical OPEX missions within the company. But the data perspective was never consciously raised at that time."
"Data is the bread and butter of what we do"
The importance of data is increasing and your species weight is decreasing, that sounds contradictory.
"I now have to start pushing the company towards an awareness, towards a kind of data literacy, a data culture. And that is precisely what attracts me to my assignment: I have to kick-start a change story and make everyone aware that they - and not IT - are responsible for the quality of their data. Data is not IT, as many think. IT is what the bank is to your money, because it is your money: IT is a custodian. That entails a culture shift and also explains why my capability falls under the COO, who also manages IT. And my role remains very transversal at the same time because data travels through the company. The insurance policy that an employee enters in the back office (name, national registration number, premiums payable, reserves...), that data is the bread and butter of what we do. That data pops up throughout our organization and has an impact nearly everywhere."
"Also, if there's a problem with that data, the general reflex was to contact IT, although very rarely it's a problem with the system as such, but perhaps it's due to a policy administrator who did not perform a proper check or didn't have the data at his/her disposal... Most of the time the problem is caused by human manipulation, because a process is basically a series of manipulation tasks of something. In the financial sector, this means that 99 percent of the time, someone enters or deletes something on a keyboard, a screen, or an application. That's basically how the data we're interested in travels through the company."
"So if you want to streamline or improve processes, you automatically come into contact with IT systems, but also the people who work with them and as such the corporate culture. It makes my job a combination of intellectual tinkering and social skills."
There are several reasons why data can be wrong or misinterpreted.
"The understanding of the same business notion or information concept, such as mathematical reserve, can indeed differ - even within the same company. Hence the need for a business glossary to speak the same language with the same vocabulary within Athora. Also, another example, when marketing talks about a customer, it should be in the same language as the policy manager - that's where the whole data story begins for me."
"That's what energizes me in my current role: I get to make everyone in the organization aware of their crucial role in information sharing and point out to them that they play a part in a bigger data story. We are like a flywheel: not particularly large ourselves, but capable of setting the whole organization in motion. Or more accurately for now: we are setting up that flywheel."
"I find that when you offer people on the floor something that they realize also has added value for them, however small it may seem, they are happy to get involved. A great example is a visualization of how our IT systems are connected, a mapping where you get a full picture of who plays what role in the process and how the data travels throughout the organization."
"If everyone understands better where the data comes from, what will ultimately happen with it, and talks about it with each other, then our way of working will automatically become more efficient"
"A very important process in the insurance sector is the calculation of our solvency ratio. The amounts entered by a policy manager ultimately end up in a financial report that says something about our solvency. Thanks to that full picture, a policy manager starts to realize that he or she is not working in a silo, but that the input has an impact throughout the whole organization. If everyone understands better where the data comes from, what will ultimately happen with it, and talks about it with each other - understanding and talking, that's culture - then our way of working will automatically become more efficient. That's where my role with data literacy lies - what language do we speak, where can you find the full picture of what's happening within Athora, what are our data definitions, who does what checks with our data."
What is Athora's data strategy?
"Generali, the predecessor of Athora Belgium, did life and non-life. We are a pure life insurer. What sets us apart is our business model and strong discipline on cost. I have to tie the data story to that. As such, our data strategy has two aspects: regulatory compliance (how do we ensure that our prudential reporting to external parties is correct) and efficiency (how do we ensure that we become a more efficient company by improving data quality). In data management, this is called a defensive strategy."
"Additionally, Athora is growing inorganically through M&A activity, as we are doing now with the acquisition of the NN closed book portfolio. Data diligence, meaning being able to prepare well for the data migration during such integration, will not be possible if data governance & management fundamentals are not in place."
"I don't really believe in revolutions in the insurance sector, but in continuous improvements"
What are obstacles to achieve this?
"It is key to write that transversal story so that employees know what each and everyone involved in the process is doing. We need to develop new skills and ensure that knowledge of how data travels within the company is shared better. This brings us back to the business glossary and data dictionaries, which clarify who performs what controls and documents who is responsible for which data. That is the goal today, with the challenge of getting everyone to prioritize it."
"However, it is true that if we achieve results, it immediately has a company-wide impact. That is what inspires me. I have a natural appetite to listen to and work with people on the floor, but the levers to effectively change something are with management, so you definitely need to get them on board first."
"Even though the IT infrastructure will eventually come to the table, my role now is more about process improvement. By the way, you don't need a tool for every problem. You can solve a lot of problems if people know how they work, with which systems and why. The underlying layer where you realize that some of those systems may need to communicate better with each other, or are too expensive, or have passed their prime... that's where you need to involve IT."
Do you approach change management as evolution or revolution?
"I don't really believe in revolutions in the insurance sector, but in continuous improvements where you question yourself every day and make small improvements. Crucial is also the bigger picture: making people realize how their contribution(s) improve the process."
"I am fascinated by the business model of the insurance industry, a relatively stable industry that, certainly for life insurance, has a de facto focus on the long term. Athora is somewhat of a challenger, but if I compare the insurance sector to retail or the music business and how they have been caught by digitalization... The nice thing for us is that we can evolve."
But maybe the big change is yet to come and a revolution will still be necessary? How do you see the impact of artificial intelligence?
"I have some difficulty with the term 'artificial intelligence' and prefer to speak of 'stochastic parrots,' but that discussion leads us too far in this context. What is true, however, is that those stochastic parrots can yield enormous productivity gains, and that is true for all businesses. But back to basics: if our data is not of good quality, no application will bring us any gains today. In fact, in case you rely on poor data, you will quickly encounter major problems."
Greg's data
- 1 & 0 / We are living in an increasingly technological, data-driven and sometimes very technocratic world seemingly ruled by ones and zeros, but what really inspires me every day is the link with nature and with other people. There is an interesting tension there, but everything depends on how we as humans handle that technology & data. Too often today, we hear "the data says this" or "science says that", but it's important to realize that data is just a reduction of the categories of our own thinking and science is not a holy grail, but a method to arrive at truth. Data interpretation has always a subjective component. And science won't tell you whether life has meaning or not.