 So, welcome to the first event in the new insurance webinar series, and thanks a lot for your interest and the opportunity to share the learnings of our upskilling journey and our RTDA program with all of you. Before we dive into the content, please let me introduce today's speakers. My name is Daniela Damm. I'm the Division of Operations Officer of Group Risk Management at SWIS-3 and I'm one of the sponsors of the RTDA program. It is my pleasure to have with me George Spakalukas and Claudio Revello. George is the Head Model Development and Analytics, and if you ask me, he is the mastermind in the zone behind the RTDA program. Claudio is a model validation actuary by profession and an R enthusiast by nature, and I think his enthusiasm and his engagement is an essential part of making RTDA, not only an upskilling program, but a movement at SWIS-3. George will present you the RTDA program in detail and Claudio promised to show you how we adopt and can adopt R to make actual reports more engaging, more enthusiastic and how he would say more stunning. There will be time for questions at the end. You can type the questions in the text box and we will just get to it once our presentation is finished. So why did SWIS-3 invest in RTDA? As a company, we believe that data access to data and advanced analytics is an essential part of our strategy to make the world more resilient. Only if you embrace analytics, we will better understand the needs of our clients today and tomorrow, and it actually will help us to create better products for them that meet their needs. But it also will help us to become better and more efficient at what we are doing, be it pricing, be it underwriting, be it claims management, but also prevent and detect insurance fraud. Ultimately, we think as an industry, data analytics will be one step to make insurance more affordable. So thus as a company, we started the Atelier program. I think it started at the end of 2018, and literally it was a very, very small group of business professionals that were truly, truly enthusiastic about new technologies at their fingertips and the opportunity that it would provide to them. What bound us all together was the vision that we need to combine the best of both world's, both the insurance and the data world. So our idea and the vision was to take our people with their strong actual and risk background and then intense their work suck with data science programming skills and combine them with communication and visualization capabilities. We believed that this would enable them not only to automate their today's work, but actually make better access of the data, create new insights, and present these insights in a way that they are truly understood by business designers and make an impact on Srysry's performance. That's how we started. So can you go to the next slide? So where did we end today is with a huge network of more than 1,000 members that are actively engaging in a very collaborative spirit, sharing new knowledge, new technologies and how it can be applied in the business life. We have more than 20, 30 business cases on an annual basis, which ends up with 100 people, more than 100 people being upskilled and making a true change on Srysry's operation day to day. We have an annual actual conference, hackathons that are very established, truly global events and by now not only attended by actuaries across Srysry, but others professions as well. And at the end, Atelier also provides a fit for purpose workbench to our community which provides them with a professional environment with advanced computing power. If you ask me what is the difference and what makes Atelier truly successful is the high adoption rate. If I compare it with any training that I have seen in my career, this is a true differentiator. Normally, when you send people to a training, they go to a different NYM and they take a break from their day to day business, they get tons of new ideas, they are very enthusiastic and then there's the next Monday full inbox, lots of different conflicting priorities and at the end of the week, there were hardly had a chance to adopt their learnings and put any of their ideas and learnings into practice. That's where Atelier is truly different. In my language, Atelier is a training on the job. So basically what we are doing in Atelier is we're taking a concrete business challenge that our teams face. We are working with them. We are upskilling them to address this business challenge while they are learning. So at the end of a workshop, not only have they learned new skills, but they actually have made a change to their day to day operations and that impacts not only them, but actually also their team. So I think what Atelier is really good at is it reduces this friction between a training environment and your day to day business operation. Personally, if you ask me, and if you could go to the next slide please, what makes Atelier successful? If you ask me the top three facts that make Atelier is, first of all, senior management got out of the way, it only created a space for the team to just do it and get on with it. Then secondly, Atelier is truly community-based. It's by the business community, for the business community. It really is driven by the needs for our people, for our people. They speak the language, they know what is going on and what makes a difference to them. And last but not least, we have a small central team of true business professionals that are enthusiastic about new technology and that can bridge these two worlds of business and data technology. They are fast, they can adapt to new requirements and new developments. This team is led by Georges Bakalukas and it's my pleasure to welcome him on stage to tell you about the Atelier program in detail. So welcome, Georges, and thank you. Thank you very much, Daniela. Welcome everyone. Let's have a look at the agenda quickly. I will spend a few minutes giving you a bit of a background on what are the motivations at the individual level for me personally and others to get on the data analytics journey and how we have made it work with ThinsWish3. Hopefully, we'll inspire others to start similar journeys. And then I will quickly pass over to my colleague, Claudio, who will show you a few automated and stunning output that he has created using some popular workflows. So if I move to the next slide, if you think about it, today's world we cannot survive really without computers. And then provided you know that you have to use computers, you quite often have a choice between using a GRAC or user interface or programming. And really what comes down to it is that programming user interface are very easy to use because you don't have a lot of things to learn and you have information on your fingertips. And you can see on the left-hand side an application that you sometimes might be familiar to you and I didn't have to think, I could give an answer. By the way, don't try it with your spouse or your partner. I tried it and it failed, I had to spend even more time coding in English afterwards to get myself out of the decay I put myself into. But let's say that you want to do something that there is no button to press to get your job done. What do you do? And up to 40 years ago, we used a big blackboard like the one you see on the right-hand side and we started doing calculations quite often by hand. Of course, they have already been hand-held calculators and others. But the point being is it's not surprising or it's not surprised that Microsoft Excel has been the world's first killer app. The reason that people went to buy computers and the reason that we today have a desktop computer on our workstation is because when you have to do something that there is no button to press you down, you have to compute. At the same time, you need to achieve two things. One is to ask the computer the questions but then also in a way that it's easy for you to ask them. And that's why programming with Excel has become so important. And we'll see later what that means in our case. So if I move to the next slide, you heard me mention programming a few times but if you think about it, the first rule about programming is that we don't talk about programming. What I mean by that in your next slide, you will see some of the popular ways that we use to describe programming. We call it data processing, data analytics, data mining, data engineering, data science, all about programming. And you can see that terms come and go with fashion or with trends. And for example, if I show you this view and I'm here from Google how data processing became quite popular from the 1960s onwards, then data analysis start to pick up and data mining a bit later on. So we see the levels of sophistication that people use programming with data for to achieve the work. And if I give you a few examples from within Street 3, in the next slide, you see the snapshots of three of our published, Street 3 publications of business reports, one from the 1960s, one from the 1980s, and one from a bit more recent 2016. And I often go back to old published reports of Street 3 and other companies because this is a nice snapshot that explains or captures what was the thinking, what are the priorities, what were the ideas that influenced the decisions and the things that were of concern of companies. And if you look at the 1960s, we talk about investing in data processing equipment, replacing some mechanical calculators with computers. So essentially you see that the data processing was the first thing that came through across many companies in Street 3 as well. And then if you look at the 1980s, we start using the word data mostly on justifying our business decision, so exiting and unpopular market. That was the year where we first justified our chairman but then the decision to get out of the market for some data quality concerns and data availability concerns. And then we move into the 2000s, 2016, and the word data appears many times and we are communicating to the investors and customers and our colleagues that how Street 3 makes data available and makes decisions through data. We leave data as one of the slogans that we have. But behind all that is really programming. It's quite important to emphasize that because this is what allows us to communicate with the computer. So if I go back to the next slide, I'll just now spend a few slides to talk a little bit about how we actually enable people to adopt programming on the day to day in Street 3 in a little bit more detail than taking from Daniela and then I'll pass over to Claudio. So first of all, we have separated the Atelier program into three pillars. So we have the upskilling pillar where we have a different means of helping colleagues learn because everyone learns in a different way. We have the community pillar that helps us share experiences and formal channels of communication and also have the infrastructure pillar, which is also very important because we bridge the gap between what tools are available for business users and tools available for professional programmers. So we build a continuum across these two binary words. And this is a community-driven event and at the heart of it is what we call the Atelier case. So someone comes up with a real business solution or problem that they need to solve, they learn while solving it. So the new skills are applicable in other situations. They share with the community. So essentially, we encourage other people and the community itself to get inspired to do more. So you solve, you share, you learn, and you share. And I will look into a little more detail in each of the three elements in the next slide. So let's look back on the upskilling. We talked about having an upskilling case, an Atelier case, which is like a real business problem that someone needs to work through. And then we have a combination of classroom-style training, which is the master classes that we call, which are a little bit specific to the use case that we have, but a little bit more generic than the actual case. Some of the self-training that we have partnered with external providers, but the heart of the matter happens in the live coding sessions, where someone more experienced, weak in, weak out for several months, help the team that wants to solve something in actually achieving it. And this is almost like when you learn how to drive and you have someone next to you to help you driving, and then you become more confident the person that is not needed anymore. So it's a gradual approach of enabling the person to be able to code and understand how they can use technology and data. If I move to the next slide, that describes a little bit more the five things that we actually do when we say programming. So the first thing is preparing data. No matter how prepared the data is already, there's always a transformation that we need to perform to get in the right shape for our analysis. We explore trends. We understand them, the risk we model. And then we communicate our insights and we automate our processes, because quite often business professionals have to do things at that hook, but once you do it once, they might have to redo them again. How much of it you can save time by automating it, that also helps. And Claudio, in the next session, will show you a specific example about how you can communicate your insights and how to make your processes. And if I move to the next slide, I will touch a little bit on the community. Here it's quite important to have different channels of communication. We have an annual conference that brings momentum towards the upskilling cases. So if everyone knows that they're going to present at the end of the season to their colleagues and others, and also invest in presentation coaching to make sure that the message that they communicate to the audience is valuable to the audience, because quite often what technical people suffer, I have suffered in the past, is we spend all the time doing analysis and we have no time to prepare to present some informal channels with MS teams. We have some monthly meetups and we also have defaults on best practices, which are very important because quite often there's no material available there about how someone who is a business professional have been using Excel all their life can start using programming and use version control, use big pipelines, using data protection and guidance to make sure that they do best practice. So these are the things that we have added to the program. And the next slide talks a little bit about the workbench that we have. Quite often the upskilling makes people aware about the new skills that they have, but also is challenging about how you get access to the tools that you are required to perform your analysis. And so there we partner with the technology departments and the IT departments, where we make some tools that traditionally have been available only to the software part of the organization to business users. And also along with that, introduce the concept of a giant product that we have been to business professionals because quite often we have to collaborate with other people that use this framework. Also in the future, every company will become a software company to some extent. So the best practices, we need to adopt them. And the final reason is that quite often we want to have fun doing our job. We want to apply our personal vision. And having a framework that is flexible enough, but structured enough to allow us to apply this personal vision, help propel us forward and innovate. So these are the concepts here. And so that was this last slide of my presentation. I believe the next slide is the introduction to Claudio now. So I will.