IFRS 17 Series #2 - Data Challenges

Welcome to part 2 of our series on IFRS 17. In this video we cover the data challenges associated with preparing for IFRS 17. 

Transcript 

Liam:

Hi there, Liam here from VantagePoint. As I mentioned in my previous video, which was sent through as an introduction, we are going through the challenges phase by preparing for IFRS 17. In this video series, I will be speaking to Matt, our director here who runs IFRS 17 practice, about how we are really overcoming some of these challenges. One of the most important ones for us and what we wanted to start on, was data challenges. How do we have all of our data in one centralised system, one centralised place? How do we connect to all of our disparate sources? And then how do we start to go about automating those data feeds? Matt, if you could maybe give us some context and some information around how you are overcoming those challenges, especially if you want to take the first one in terms of connectivity to disparate systems and having that centralised hub of data.

Matt Benaron:

I think the two points that you mentioned are the key ones: The pulling all the data together and then thinking about the process and automation. On pulling all the data together, in some cases, clients that we work with have already pulled together and they have an insurance data warehouse that might be finance-centric, it might be actuarial-centric. It could potentially be both. But in most cases, we are needing to pull data from different systems. Usually, the line in the middle is finance and actuarial but, depending on the way the overall group systems are managed, potentially there are a number of different finance systems and a number of different actuarial systems. 

Matt Benaron:

Thinking about how you will leverage tools like ETL, which is extract, transform, and load, to pull data from those different data sources into a centralised place is something to consider really early on in the project. Does the technology that you are using have the inbuilt capability to pull all of that data together? But it is not just putting it together, it might be performing allocations to bring the data to the right level of granularity. It might be validating it and potentially even doing some transformations like generating cash flows. I think that is the first part of the challenge. And then you mentioned automating the process. That is the next stage to think about after you have identified the data sources and identified how it is all coming together.

Matt Benaron:

Depending on what your existing working day timetable looks like and what your ambition is for the post-IFRS 17 working day timetable, there is often going to be a challenge around the availability of different data at different times. And you will want to get your IFRS 17 resolved as quickly as possible. So thinking about how you can arrive at that without necessarily having all of the data available right at the start of the working day timetable is key. For example, we work with some clients to look at potentially your liability for remaining coverage data is available earlier than your liability for incurred claims. How can you automate those feeds such that once that data becomes available, you can get it into your IFRS 17 solution as quickly as possible? And how can you overall build an end-to-end process that makes the whole IFRS 17 end-to-end process as succinct as possible?

Liam:

Just to recap, I guess there are two really important points here from my understanding: having a centralised data hub and then also being able to automate data feeds and automate manual data processing tasks that would otherwise need to be done taking up a quite considerable amount of people's time and energy.

Matt Benaron:

Exactly. And I think that if you get the right IFRS 17 solution, then those can all be solved in a single IFRS 17 solution if you don't already have technologies in place that are supporting automation, ETL, and process management.

Liam:

Fantastic. Great. Thank you. For today, we will leave it here in terms of data challenges. I hope that leaves you a little bit clearer on how we manage these data challenges at Vantage Point and how our solutions get across that first hurdle, which is around data accessibility and automation. Thank you very much for watching. We will see you in the next video.

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