March 1, 2023

11:00 am - 12:30 pm EST

Transunion Keynote: Self-Service in a Regulatory Environment

Deepika Duggirala leads the strategy and execution of cloud-based platform transformation at TransUnion. With over two decades of experience, she combines an enterprise mindset with agile,
innovative thinking that drives the development of competitive, scalable products.

Duggirala began as a software engineer and has led development teams at organizations ranging from startups to large, global enterprises such as Motorola, Nielsen and SAP and has an extensive background in data and analytics.

She serves on the Regional Advisory Board of Comp-U-Dopt, an organization that increases computer access and technical literacy for Chicago youth. She holds an M.S. in Electrical and Computer Engineering from Rutgers University and a Bachelor’s in Electronic Engineering from Nagpur University in India.”

Topics Covered

Customer Use Cases
Data Mesh
Real-world implementation

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Note: This transcript was created using speech recognition software. While it has been reviewed by human transcribers, it may contain errors.

Deepika Duggirala:

Hi everyone, it’s great to be here and talk to you about how TransUnion is using Dremio for our self-service capabilities and analytics in a regulated environment.

What is TransUnion?

I thought I would start by talking to you about TransUnion because I think most of you think of it as a credit reporting agency, but we’re more than that. We operate in 30 countries across five continents and we pride ourselves on being an information and insights company. What we do is make trust possible by ensuring that every individual, every one of us is reliably represented in the marketplace. I run architecture and tech strategy and I’m responsible for the buildout of shared capabilities and platforms at TransUnion to enable us to do this in a secure, compliant, and consistent way across the globe. So I’ll start by.

We Make Trust Possible

We say make trust possible. What does that mean, right? It’s about providing powerful consumer insights. Insights about the core identity, a multi-layered, contextualized understanding of a person that is accurate across their online and offline identity fragments, if you will, as they go out their lives. As well as relevant information. So it’s recent observable events that feed this. TransUnion stewards this data with our expertise, but more importantly with the accordance of the local regulations that exist around the world in terms of protecting that identity. And this true picture, this identity is the core of the products and solutions that we offer globally. It enables not only credit, which is what we’re all familiar with, but it enables fraud, risk, marketing, as well as other advanced analytics capabilities all around that. And that’s what our world is.

And as companies use that information and our solutions to transact with confidence and build confidence with their consumers, consumers use TransUnion products and services to access, maintain, and protect their identities. So together this creates really great experiences, but personal empowerment and economic opportunity. And at TransUnion we call that information for good because that’s what we want this data to be used for.

Analytics Platform

So when we talk about an analytics platform at TransUnion, it’s about enabling those powerful opportunities and creating new ways of using information for good. At the same time, we have to be cognizant of the fact that we’re dealing with highly confidential personal data and we place a premium on that trust. The trust of the individuals around the globe whose data we manage. The trust of the businesses who use this information to execute on their transactions and businesses. At the same time, we want to enable innovation. We want to enable experimentation. We want to allow this diverse group of users of TransUnion data. When you think about our data scientists and data analysts internally and our external customers to be able to collaborate and unlock new opportunities. So it’s paramount for us, that we manage our data in a secure and compliant way, but still build an analytics platform that’s easy to use, that’s performant, and that allows them to continue to build new solutions.

Hybrid Multi-Cloud

And as we’ve moved into our digital transformation, our intent is for this analytics platform to be available globally. So it’s a consistent way in which we’re accelerating innovation across the globe. Our digital transformation, similar to many companies that are going through it right now, is really about embracing the public cloud, finding a way to accelerate how we innovate and bring products to market. So while the public cloud gives us the access to technology and to scale and availability that comes with it, we realize that there might be certain use cases and situations where we don’t want to adopt one or the other environment. So we built what we call a hybrid multi-cloud. We don’t see ourselves in one environment ever again. We have this varied environment across public clouds as well as our on-prem data centers, which creates our control plane at the bottom and then our analytics capabilities and other common capabilities built on top of it really to look across this. So as you can see, the complexity, the diversity of our data is growing as we go through this. And we hold the responsibility of that secure access and manage governance. But in general, what we’re looking to do is allow our data to live where it lives, allow access only to users who are allowed to use it, but allow that access in an easy to use way so that innovation happens across the board. Piece of cake, right?

The Role of Dremio

That’s where Dremio comes in for us at TransUnion. It has allowed us. It’s been part of our architecture for a long time. We were early adopters of Dremio at TransUnion because it allows us to bring together that state-of-the-art tooling alongside self-service data access in a governed way. So I talked about our geographically distributed data, but when you think about the different types of data sources that we deal with, we tend to have structured, unstructured data. We have data that’s proprietary to us that needs to be analyzed alongside some public data sources, for example. And the reason Dremio was such a great fit is it created a data mesh for us across all of these. And it allowed our customers, our users, data scientists, data engineers, data analysts to use SQL to access and explore data across the enterprise.

Now, I talked about our transformation. I talked about this hybrid multi-cloud. What we’ve done is we’ve expanded the complexity of that. We’re working with Dremio because our goal is that in this expanded data mesh, Dremio becomes the single consistent query engine. So it’s not just about SQL based querying, it is the BI tools and the point-and-click interfaces. The different ways in which a user may want to access the data. We still support it in a common way. Behind the scenes of all of this and I talk about the users a lot, cause at the end of the day it’s the experience that matters, right? What we do is behind the scenes manage the complexity of the governance around it.

The fine-grained access controls work perfectly for us on that front. So every user that has access to TransUnion data has a well-defined process they have to go through. We have policies around who can access what information at role level. Specific columns that should never be visible. Users and groups of individuals that can access certain data sets, certain folders, certain tables, all of that authorization control. All of the entitlements are managed through Dremio for the users that are interacting with it. So this seamless, easy to use data environment, what it really enables our associates to do, our data scientists to do is focus on that information for good and focus on creating innovation, creating financial inclusion.

Examples Throughout the World

And what I thought I’d do is end with a couple examples of what this really means. So in the United States traditional credit scoring is done based on data at a point in time. So through the data analysis and looking at the different types of data points that are available on consumers, our data scientists determined that by using trended credit data rather than a point in time that looks at payment history and the amount of money borrowed over time, mortgages, and everything else alongside the day-to-day activities that we do as consumers, right? How are we doing with our accounts? How often do we move? What’s our address stability? How are we doing with the little microfinance loans that we take or our rental payments? Really starting to bring those together increases the number of people that actually can participate in the credit ecosystem. So there are people that are not represented in the credit ecosystem today for a variety of reasons and about 60 million additional consumers right here in the United States were able to gain access to credit because of this combination of critical data points and information.

Another example is in India. India as many of you might know, is primarily an agricultural economy. About 55% of the workforce in India operates in the agricultural sector. But getting loans for farmers is really difficult because banks and lenders deal with this complexity of trying to figure out what’s the credit risk of the individual I am giving a loan to, but what’s the production risk on the land on which the crop is being grown? Is that going to be productive? And this really made access to credit for farmers difficult. What TransUnion CIBIL, which is the division in India, did is they partnered with a company called SatSure that has geospatial data and they combine traditional bureau information with agricultural information about the land and what’s growing and what’s happening there. And together created a report that really helps lenders make those decisions quickly. A staggering 89 million farmers in India have access to easier credit because of this. My friends, that’s information for good and that’s the power of data.