“,” Gwenaël Gavray said in an interview with Delano earlier this year. Gavray is a partner at Avantage Reply, an advisory firm specialised in financial sector regulatory risk, and was speaking about the type of projects they take on for banking, insurance and fund industry clients.

So what exactly does it mean to ‘master data better’?

Helping financial firms use their data better, often involves “better organising data, having better governance around data, how it’s used, how it’s structured, and how it’s organised within the institution,” Ryan Davis, associate partner at Avantage Reply in Luxembourg, said during the interview. “You often find, especially with large financial service institutions, be they insurers, banks, funds, if they have grown inorganically through adding on bits and pieces through acquisitions, when you come in, each of these entities is coming with data which is potentially organised in a different way, stored in different systems, used in a different way.”

Other clients are looking to take advantage of artificial intelligence and machine learning systems, or want “better risk modelling and better use of data to assess potential issues or stresses or problems,” stated Davis.

Pressure to be accurate

“Data quality” is a fertile field, said Gavray. For instance, local banks are supervised either by the Luxembourg Financial Sector Supervisory Commission (CSSF) or the European Central Bank. In both cases, they need to comprehend, “how do they monitor the activity of the bank? How can they understand what the bank is doing? To prove the reporting and if the reporting is inaccurate, if there are any mistakes in the reporting, of course, the supervisor has a really hard time understanding. So they put a big emphasis and a big pressure on banks to be really accurate. And by pressure, I mean, it can go up to fines and it’s public, so it has a huge impact on reputation and so on.”

“Banks see that it’s really important to have a perfect understanding of their activities and that they’re reported correctly,” he continued. “Controlling the quality, making sure that you’re reporting things in a consistent manner is something that is a real hard task to do”.

Known unknowns and unknown unknowns

The recent EU sanctions against Russia, following its invasion of Ukraine, is a good example. European banks “were supposed to immediately identify their exposure to Russia. And that is not something that’s easy to do,” Gavray pointed out. “They saw it coming; it’s not like it happened overnight,” yet many financial institutions still struggled.

Then there are events that financial firms do not see coming. “It happened a few years ago, with Fukushima. All of a sudden, you needed to know exactly what’s your exposure to Japan, because there’s been a catastrophe there. This is where they realise that sometimes they do not have a clear, clear understanding of how their data is structured and how they can pull this out.”

In other words, it is important to make data more searchable and more analysable.

“There’s no magic solution here,” Gavray said. “You need to have governance in place, you need to make sure that you have quality controls, that you understand who’s the owner of the data, where the data comes from, where it is utilised. And that you have a consistent view, that it’s up to date, that it’s relevant.”

This article was published for the Paperjam + Delano Finance newsletter, the weekly source for financial news in Luxembourg. .