Data Governance and AI for Financial Services and Public Sector

Summary

IDB Invest, the private sector arm of the Inter-American Development Bank, uses Databricks and Unity Catalog to govern data across operations that impacted close to 2 million people through MSME financing and recorded $13 billion in total activities in a single year.
Franklin Templeton uses Genie to enable business users — including financial advisors and compliance teams — to uncover portfolio research insights at scale without requiring technical data skills.
Both organizations emphasize that trustworthy intelligence at the point of decision — not just fast pipelines or clean dashboards — is the defining requirement when data infrastructure is tied directly to community impact and regulatory compliance.

Data Governance and AI for Financial Services and Public Sector

Industries from financial services to healthcare to public sector face unique demands: financial institutions need to scale investment analysis and compliance, while development banks must make data-backed decisions that directly impact communities in emerging markets. Each requires trustworthy data governance and AI infrastructure at the point of decision.
Hear from Igor Valentim of IDB Invest on how they use Databricks and Unity Catalog to govern data across 2 million MSME financings, and from Mark Nigro of Franklin Templeton on how business users are leveraging Genie to uncover portfolio research insights at scale. Both organizations emphasize that data infrastructure is not just technical, but human. It empowers small teams to make better decisions faster, and scales compliance-driven operations to external-facing work.
🤝

Chapters

FAQs

What is IDB Invest and how does it use Databricks?

IDB Invest is the private sector arm of the Inter-American Development Bank, focused on financing companies and mobilizing private investment to support micro, small, and medium enterprises in Latin America and the Caribbean. The organization uses Databricks and Unity Catalog to govern data across operations that impacted close to 2 million people through MSME financing and recorded $13 billion in total activities in a single year.

How does Franklin Templeton use Genie for investment research?

Franklin Templeton uses Genie to allow business users, including financial advisors and compliance teams, to ask questions about portfolio data in natural language and uncover research insights without technical data skills. This expands access to data intelligence across the organization rather than concentrating it in a small technical team.

Why is data governance especially critical for a development bank like IDB Invest?

IDB Invest's mandate is to finance communities largely ignored by traditional financing, meaning every decision directly impacts people's lives and livelihoods. Trustworthy intelligence at the point of decision is therefore not just a technical requirement but a human one, where data quality and governance directly determine the quality of outcomes for the communities being served.

What data culture shift are IDB Invest and Franklin Templeton pursuing?

Both organizations describe a shift from using data primarily for reporting to using it to directly drive decisions and external-facing work, including compliance and client advisory activities. This requires not just better technology but a change in how teams think about data — treating it as active intelligence rather than passive record-keeping.

Full transcript

[00:21] All right, welcome back to Summit Live Studio. I'm Adam Crown. I'm incredibly excited to host today's session with incredible customers. I lead industry marketing for healthcare and life sciences by day and today I have the distinct honor of interviewing folks like Igor. Igor Valentine is head of
[00:38] data management analytics and AI and IT governance at IDB Invest. So Igor welcome to the studio. Thanks so much for being here. Appreciate it. Tell us a little bit about you, your role and a little bit more about IDB Invest as well. Sure absolutely. So Eagle Ring team here
[00:53] as you just said among many other things I deal with data management analytics and AI for IDB invest for those less familiar with us IDB invest is the private sector arm of the interamerican development bank uh our mandate is to finance Latin America and the Caribbean
[01:09] for the private sector we do it financing companies and also mobilizing private investments to support that region u last year alone we we were able to impact close to 2 million people through MSME financing and also um we we register a
[01:27] record of $13 billion in in total activities which is kind of representative for the region. That's incredible. So you talked a little bit about S MSME. Can you define a little bit more about what those organizations are? Sure. Absolutely. So those are micro
[01:42] small and medium enterprises that we are financing uh in Latin America. And the interesting part about that is uh through those those small business is where we generate the impact because on the small business is when you truly uh
[01:57] expand and and impact the community that we are serving. That's incredible. So when you think about the human mandate around helping those communities what role is data and AI infrastructure playing in that context? Oh that's a that's a fantastic question. Listen, when an institution purpose is
[02:14] to impact these types of people, right, in communities that are largely ignored by the traditional financing, a definition of good infrastructure completely reframes, right? Um, we need to definitely uh it's not only about fast data pipelines or clearing
[02:30] dashboard. It has to be trustworthy intelligence at the point of decision. meaning that every decision that we make is backed by that specific intelligence and what we build on data bricks is central to that. That's incredible. I love hearing about all of the potential to transform every
[02:48] single industry and in this case it's lives in these communities. So when you think about the fragmented processes that uh you may have seen in a prior state, you know, how is governance, how is AI forward in infrastructure helping bring those new opportunities into those
[03:04] communities? Yeah. So every decision that we make at IDB invest, we do have a real uh human impact, meaning that what we are doing, you know, if you if you have bad data in attack company, you're just missing an upsell, right? But when you are doing
[03:21] this in a developing organization, international organization that means that decisions on on catalytic capital is being take. So they are deciding whether they want to deploy this capital in one side or the other. So uh we are investing a lot on data governance as well and unit catalog plays a very
[03:37] important role into this uh because that's how we governing our data. We ensure that the data has the correct quality and we are deploying solutions that are embedded into the business process that support those decisions. And so let's talk a little bit about that operational efficiency. It's top
[03:53] of- mind for every single organization today. You helped save million dollars. You've grown your analytics user base by over 85%. What are some of the challenges when it comes to technical but also the people in the process? How did you overcome that? Fantastic. Definitely not technical
[04:10] wasn't the challenge right cultural was the challenge. Uh when we look into we had a very embedded culture of of using data as just a reporting artifact meaning that we were consulting the data after the decision was already made and we had to shift that mentality towards
[04:27] using the data for decision making using before you ask and make those decisions. So that's why we had to act on the friction point let's call it right. So taking away that needs of having specialized teams to consult in analyzing the data and deploying
[04:42] solutions such as Genie spaces that allow those people to own natural language query the data asking the data and deploy enterprise solutions that allow them to really take advantage from this and use it at the decision point. That's incredible. Igor, thank you so much for joining us here in the studio
[04:58] today. I just wanted to also commend you on your jacket. Can you talk a little bit about that for a moment? Yeah. So, this is our we just won the public sector award for 2026. Super proud, super proud to be here representing IDBS and to wearing that that specific award. You guys are doing some incredible work.
[05:14] Well, thank you for joining us here today. We'll see you around the show. For sure. Thanks, Eigore. We had an awesome opportunity to hear from Igor at IDB Invest and really appreciated hearing about his story. All right, that was great. And we have
[05:29] Adam talking again, this time to Mark Negro from Franklin Templeton. So, let's see that. We're live here in Summit Live studio. I'm Adam Crown, industry marketing leader for healthcare and life sciences,
[05:44] and I'm really privileged to have incredible organizations here on the segment to talk about how they're using data and AI. Mark, we've got you here from Franklin Templeton. Tell me a little bit about yourself, your role, and a little bit more about Franklin Templeton as an organization.
[06:00] Adam, thanks for having me. Really excited to be here. So, Franklin Templeton, we're a $1.6 trillion asset manager. And my role is in our portfolio solutions team. And the way I describe what we do is we turn complexity into investment decisions. That can take on
[06:17] many different forms. I do a lot of manager research. I do a lot of market research and I work with teams working with distribution to get clients to find the most impro appropriate vehicles for them to invest to meet their investment objectives. We work across the US across
[06:32] vehicle types and we try to find ways to communicate clearly uh and effectively with those clients on those investment decisions. Awesome. So you mentioned you work with clients, distribution teams on behalf of investment managers and there's a really important aspect of
[06:49] making sure that you can help bring them clarity and also confidence in the data that they have to financial adviserss. What does that look like? How does that uh take shape within Franklin Templeton? Yeah, well you know we started this type of work uh when it was ad hoc when it's
[07:05] human work. It's analysts, consultants meeting with distribution partners as well as financial adviserss getting in a room, communicating over phones, over email. How do we find the right opportunity to work with them? How does that opportunity benefit them in the long run? So, this work has been
[07:20] something that a firm like ours would do uh over and over again throughout the years. Um, as we've built different tools, we've tried to figure out how can we scale this? And we've done many, many things over the years to figure out how to scale this. And some of the stuff that we're here to talk about today really helps take this to the next
[07:36] level. Once we scale these things, then it really opens up possibilities for deeper work, for different work that I'd love to discuss with you. That's incredible. So, uh I think you had mentioned this is one of the first data and AI summits that you have had an opportunity to come to. You know, the
[07:52] show we're at about 30,000 people here, which is crazy to think. You know, just last year, I think we had close to 20,000 folks. And a lot of the talks that are given are fairly technical in nature, but we're starting to see a pretty large evolution towards business
[08:07] users. You know, folks like yourself, even folks like me who are interacting more with their data. So, when you think about that and you think about all of the potential with uh data at Franklin Templeton, how is data bricks getting used in the context of a business user? Yeah, it's a really good point. Business
[08:23] users like myself are going to take advantage of the opportunity that these tools give them. So, I've been working with a really great data science team we have at Franklin Templeton. But I'll say even they are are overworked. Uh, and they've given us access to these tools to help us ideulate, help us build and
[08:40] and we've been able to do that and do that successfully. You're going to see more folks like me at these conferences. I'm here. I'm learning so much. I'm going to go back and I'm just going to scratch the surface of what I can do, but next time you see me, I'll be able to do more. you'll see more people like me, business users who are are taking
[08:56] business use cases and figuring out ways to put those into these tools, into these algorithms, these AI agents, uh, and into stuff like data bricks. That's incredible. So, you coming from that lens, I think it's really important when we're approaching these really transformational products to have a
[09:12] methodical approach to making an impact within your organization. So, using data, using AI to see around corners. tell me a little bit about how you're helping see see that around corners for your teams. Yeah, so everything we've we do um is
[09:29] highly regulated in our industry. So even our internal use only tools, the things that we're building using some of the tools that data bricks have those things are built with the idea of this is going to be regulated. This is uh we need to be communicating appropriately. We need to be following all the rules
[09:45] even if it is internal just as we were uh communicating externally for a client. So the idea is we'll be able to scale things as compliance is more comfortable with what we're doing as we're learning ways uh rules for the road for for uh how do we engage using these type of tools externally uh we're
[10:01] putting ourselves in a really good position to do that. So not only are we doing this internally but I think in the very near future we'll be doing it externally. We'll also be looking at not just a lot of uh product versus product in specific market research but pretty soon you're going to be see us doing
[10:17] portfolio research. How does this specific product change the makeup of a portfolio? Does it benefit the client overall? Um, anything investment related, these types of tools are really going to help us uncover those opportunities. How do we benefit the client overall though? That is what we're always seeking to do. And how do
[10:34] we do that in a compliance-driven framework? Incredible. Well, you have been an awesome uh discussion host with me today. I really appreciate you being here. Thanks for being here for your first data brick summit and hopefully next year we'll have even more to talk about. So Mark, thank you again for the time. I really appreciate it.
[10:49] You're welcome, man. And with that, we are officially going to wrap this segment. Thanks for tuning in to Summit Live today. Appreciate it.

Learn more about the Databricks Data and AI platform.

The information provided herein is for general informational purposes only and may not reflect the most current product capabilities or configurations.