The Data Chief | Episode 58

Société Générale’s Innovation Data & AI Leader Julien Molez on Creating a Value-Driven Data Framework

Julien Molez

Innovation Data & AI Leader

Société Générale

Apple podcastsSpotify podcasts
Current EpisodeEP58: Société Générale’s Innovation Data & AI Leader Julien Molez on Creating a Value-Driven Data Framework
00:00
00:00

Episode Overview

At French bank, Société Générale, providing the best customer experience in the modern digital world means rethinking everything about banking, including its corporate structure. Three years ago, Julien Molez, joined the bank’s leadership team to become the first Innovation Data & AI Leader. On this episode of The Data Chief, Julien addresses changes sweeping the banking industry, including higher customer expectations, tougher regulations, and the ESG revolution. He also reminds us that at the end of the day, fancy AI models and algorithms will only perform as well as the data that goes into them.

Key Moments:

  • Creating a value-driven data framework (06:31) 
  • How do you achieve customer personalization while adhering to GDPR? (15:29)
  • How do you truly secure data at all touchpoints? (20:29)
  • How is Société Générale leading in ESG reporting? (23:44)
  • What were Société Générale’s unique challenges in scaling up AI use cases? (28:55)
  • How do you educate business stakeholders about the best data possibilities? (35:56)
  • What is a key data framework technique? (40:00)

Key Takeaways:

What does your role as an Innovation Data and AI Leader bring to the team? (01:20)

“Three years ago, we said…maybe we'd like to put a bit more emphasis on creating value, because we saw the different fintechs and big techs entering the financial services space, and becoming competitors. We saw that these competitors were leveraging data in their client value proposals. So we know we also had to adapt, not only being defensive by bringing good quality data for reporting but also leveraging data in a more offensive way to be able to bring more added value to our different processes and especially client processes.”

For Société Générale, the Innovation Data and AI Leader role is all about creating value. It’s not enough to have a defensive strategy for protecting your data. To stay ahead of the competition, must also use data to enhance and personalize the customer experience.

When introducing a new data framework, how do you create buy-in with business stakeholders? (13:31)

“It's really, co-construction in the design of the value framework and of the platform. So it's quite some time spent with the different stakeholders, just to make sure that we are aligned, that we hear the different constraints. It's not a pure top down model saying, well, that's gonna be the group framework and you get to apply it. We took a lot of time hearing call building and then publishing when once we all agreed.”

Co-creation with business stakeholders has been a huge part of Julien’s success at Société Générale. By listening to to each group’s constraints and focusing on alignment early on, he has created an environment where teams can operate freely within agreed upon boundaries, and be as agile as they need to be.

What were some of the unique challenges you discovered when scaling up AI use cases? (28:02)

It's very key to make sure that the business knows what it means to use data and AI. What can AI bring to you and how empowered do you feel to build data solution AI solution? They're going to change the way you work or the way you interact with your clients. And it's very difficult. It takes a lot of training, lot of awareness.

When it comes to scaling AI use cases, data quality and having the right data platforms are both critical. Equally so is education and awareness for business users. According to Julien, business users must be the driving force of your AI transformation, not the other way around, and this takes a lot of investment.

Key Quotes:

Three years ago, we said…maybe we'd like to put a bit more emphasis on creating value. We saw competitors were leveraging data in their client value proposals. So we knew we also had to adapt, not only being defensive by bringing good quality data for reporting but also leveraging data in a more offensive way to be able to bring more added value to our different processes and especially client processes.

All the reflection on our architecture is to make sure that this sensitive data cannot be copied and pasted and cannot be used in a non-appropriate way. And we have very strict rules.

There's a huge difference between what I call corporate AI and academic AI. Most of the time [in corporate AI] you get a good result with…a very basic algorithm from a machine learning point of view. But the key challenge will be how to define the business problem, and the key business metrics to solve, which is most of the time, not machine learning metrics.

Bio:

Julien Molez has more than 20 years of consulting, IT, and data experience in the Financial Services sector. He joined Societe Generale in 2014 where he contributed as an Associate Director to the development of the in-house consulting offer (SG Consulting & Transformation) as a member of the leadership team.

He became Data & Innovation leader in 2019 within Société Générale Innovation Team that is attached to the CEO to lead the AI & Analytics strategy and support every business line into having an impactful and measurable impact of analytics & AI in their digital transformation. Julien is graduated from Ecole Centrale de Paris.Follow Julien Molez on Linkedin