Modernizing Finance Data for Faster and More Reliable Operations - with Ciprian Porutiu of Marsh

Yolandi de Weerdt (0:12)

Welcome everyone to the Emerge AI in Business Podcast. Today's guest is Ciprian Porutiu, SVP of Strategic Initiatives at Marsh. Ciprian joins us on this episode to examine how enterprise finance teams must structure underlying data systems before employing automation and AI tools. He details why organizations should prioritize standardized taxonomies, common data dictionaries and federated data domains over single monolithic databases. Today's episode is sponsored by Fynapse. Just a quick note for our audience that the views expressed by Ciprian on today's program do not reflect that of Marsh or its leadership. In this episode, we cover how finance teams should structure their underlying data systems. To go deeper on this topic and learn how financial institutions are digitizing paper-based records to unlock usable data for AI and using alternative data like public web and social signals to enhance risk assessment, download our free PDF report AI in Financial Services Executive Cheat Sheet at emerj.com/fcs1.

That's emerj.com/fcs1 to download your copy. Now the conversation with Ciprian.

Ciprian, welcome to the Emerge AI in Business Podcast.

Ciprian Porutiu (1:48)

Nice meeting you, Yolandi.

Yolandi de Weerdt (1:50)

I should actually say welcome back, but it's been a while, so I'm really interested to hear what has changed in your mind since the last time you were on the show, but also what has stayed the same. And I think something that everyone talks about currently is about finance, needing to move faster, and everything has to move faster. But I don't feel that the part of the conversation that doesn't get enough highlight or attention is what is also quietly slowing it down, what is preventing us from moving faster. And it's really not just one big thing that's broken, right? It's if we think about the day to day, if we're thinking about the numbers that don't quite agree between the different systems or nobody being absolutely sure about what is the current version or the latest version that they should be working on or close week turns into a complete scramble because there are gaps that we cannot explain, things like that. So I want to start quite broad with you on that. What is creating the most pressure for finance teams right now, when it comes to their data and the system sitting underneath it?

Ciprian Porutiu (2:51)

Sounds good. So since last time we spoke, not much has changed, a lot has grown, but I'm still in the middle of change, transformation, engagement. Fortunately, the role has been very kind to me and allow me to run in all corners of the organization from finance transformation to CRMs to setting up new products. Obviously, now everything is AI, so accompanying journeys in different capacities in terms of engagement and deployment of AI tools both for colleague productivity but also for the product, so client-facing and partner-facing application. So I'm still very much focused and my life motive is also the people engagement. So obviously, companies made of people, processes, technology. A lot of times we focus on technology because it's something that grabs the headlines much more than anything else. The processes are probably much less and the people's perspective is also kept in the background and maybe it provides a headlines when someone lays off a lot of people to replace them with AI. But not necessarily from the perspective of how do we use our best resources and best assets if you want, without calling people assets to actually make the company become something that it's a competitive advantage rather just like one item in the assets balance sheet. So I'm still coming from the same perspective, but definitely finance data and data in general is more forefront of attention of everyone today when automation is no longer an automation, it's an automation patitiated by an AI and LLMs and SLMs and everything that wants to make the things as you said first faster. Everything has to go faster. And whether you want to go faster or you have to go faster because you have competition, because you have markets, because you cannot wait, definitely the speed is something that comes up to mind. But I always try to take a step back and say, obviously, everything you see, financial results, revenue top line or bottom line, efficiency, savings, everything else, is the top part of the iceberg. It's above the water line.

Everything, and it's basically the lagging indicators, the ones that everyone discuss in the quarterly reviews, in the EPS and every earnings calls. But what is underneath is the leading indicators and what creates the context and creates the situation for the lagging indicators to actually provide not just good results, but also reliable results, that one quarter is not up and then the next quarter is down and you don't know why. Well, the why it's below the water line. Below the water line when you see the capacity that you have and you create in order to deliver those products, lagging indicators, this is where the reach in which your expansion geographically or product or business or deepening and cross-sell and everything else occurs.