Decoder with Nilay Patel
Experian's tech chief defends credit scores: 'We're not Palantir'
26 Jan 2026
Chapter 1: What is the main topic discussed in this episode?
Hello, and welcome to Decoder. I'm Nilay Patel, editor-in-chief of The Verge, and Decoder is my show about big ideas and other problems. Today, I'm talking with Alex Lintner, who is the CEO of technology and software solutions at Experian, the credit reporting company. Experian is one of those multinationals that's so big and complicated that it has multiple CEOs all over the world.
So Alex and I spent quite a lot of time at the beginning simply talking through the decoder questions so I could understand how Experian is structured, how it works, and how the kinds of decisions that Alex makes actually work in practice. There's a lot there, especially since Alex is in charge of the company's entire tech arm.
That means he oversees big operations like security and privacy, and now, of course, AI.
Chapter 2: What is Experian and how does it operate?
All of which is always important, but even more critical when you factor in what kinds of information Experian collects and stores about Well, literally everyone.
See, if you want to participate in the economy the way the vast majority of us would like to do, renting an apartment, buying a car, getting a job, applying for a mortgage or a student loan, you're part of Experian's ecosystem, almost whether you like it or not. You'll hear Alex talk about consent a whole lot in this conversation, and he'll argue that you can opt out of the whole system.
But the reality for most people is that interacting with Experian is pretty much non-negotiable. It's hard to do basically anything involving money without a credit score. That's really the tension at the heart of a company like Experian.
Credit scores dominate so many aspects of our lives, and they're controlled and calculated in ways that most of us feel like we have very little direct influence over. But at its heart, Experian's core service is data. Data about people. About their money and what they do with it. The bills they pay or don't pay. About the decisions we make.
And all of this extremely valuable data weirdly makes Experian a part of our lives. Lives that become much smoother if the data the company collects about you tells a good story. So Alex and I spent a lot of time talking about the responsibility Experian feels towards all the people it serves. Not just on the security and privacy level. but also a moral one.
In fact, there's one particularly illuminating exchange that Alex and I had. A lot of people don't like the power Experian has, and by extension, they don't like the company either. So I asked Alex pretty directly about that, and I found his answer to be pretty surprising. It's maybe one of the most memorable answers we've ever gotten on Decoder, actually. You'll see what I mean.
I also asked Alex pretty directly about the other big, messy question taking the room, generative AI, and why exactly we should trust non-deterministic systems when they start interacting with really sensitive data about our financial lives and making decisions about us.
You'll hear Alex talk a lot about AI oversight and how it's being woven into the systems Experian uses for everything from risk assessment to predictive financial modeling. But as we all know, AI systems are inherently risky. They get things wrong. They hallucinate. They might make incomplete or incorrect conclusions about very real human beings in ways that dramatically affect their lives.
So I really dug into how Experian and Alex see AI technology being used internally and within the broader scope of credit reporting. And I also pressed Alex on the capability gap between what AI might be able to do today, what we think it can do, or what AI executives tell us it can do. and the reality of what it can actually do and how well it does it.
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Chapter 3: How does Experian influence personal financial decisions?
I think Experian wants to be known as an AI company. We're going to get into that. Why don't you tell me what you think Experian is today and what it has been and what you think it should be in the future?
Experian is a global data and technology company. We help consumers and businesses to make financial decisions and protect their data and identities. On the B2B side, we have four verticals, financial services, healthcare, automotive, and marketing services. On the D2C side, we protect...
I would say we provide consumers with information that helps them understand, protect, and manage their financial lives. So we help them build credit, qualify for their next desired loan. My favorite example is they're getting their first mortgage, which is a hard thing to do in America, but a major wealth builder for Americans.
We give them access to comparing financial products so they can lower their borrowing costs. We protect them from fraud and identity theft, like I mentioned earlier. And we help them save when they buy car insurance.
So that's Experian to me. This is going to be very reductive. And I'm saying it on purpose because I'm curious if it really is this simple or if there's more complexity there. That sounds like Experian maintains a big database of information about people, mostly about their credit. And when you say it protects that information –
That's because having all that data is very important and very powerful and very valuable. But it's also the information that mortgage lenders use. It's the information that car insurance brokers use. How do you think about the core product? Is it just a database or do you think about it differently?
Well, what you want to do is AI.
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Chapter 4: How does Experian handle consent and data usage?
If I go straight to the AI topic, though, maybe we should back up a little bit. If AI is a platform capability, it's not a feature. And we use AI primarily to help embed governance, help explain ability, which is required by law and desired by the consumer, and to actually facilitate human oversight.
Um, so then when you, when you then back up, uh, uh, into, you know, where we came from and your, your question at the core with all the data that we hold from a technology perspective, and I'm the tech guy, so I'm going to talk about the technology. Uh, that means that we apply data analytics and AI, uh, into the hands of decision makers.
Chapter 5: What are the implications of credit scores on individuals?
And those can be in businesses, financial institutions, mortgage companies, like you just said, but we also supply it to the consumer directly. And the objective is the same. The objective is to turn complex data, complex information into easy to understand, actionable guidance, so that either the lender or the consumer can make a confident decision. Yeah, and that's the objective.
You need the same data for that. And both sides need to see it because the data is the objective truth. And then the consumer can make a decision and the lender can make a decision if you're talking about financial services in particular, which your example did.
Sure. I think maybe I'm just – I'm way at the bottom. I'm at the primitives here. The main thing is a big database of financial information about consumers and their credit history and their ability to pay for things. Is that – the main thing or is there another core element of the product?
It's a core element. I think you're overemphasizing the financial information. Financial services is one of the sectors, like I said earlier, we have a lot of other information that is useful, that has nothing to do with sort of the core lending information that we have, the history of people's lending behaviors. And the other information is just as useful.
So if you look at the automotive industry, Vertical, for example, we have an equivalent to most people know Carfax. We have something called AutoCheck. It has vehicle history, ownership history, maintenance and repair history, accident history. So there is a lot of other information that is actually relevant for these decisions. It's not only the financial information that we have about people.
And by the way, when people say financial information, often it's interpreted as We have account numbers, et cetera. So we do need account numbers to match the accounts to people, but it never goes out. And it's double encrypted, so super protected.
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Chapter 6: What responsibilities does Experian have towards consumers?
We don't use any of that information for any of the services that we provide, except for the pinning so that we can match it to a person.
Can I offer you my feature suggestion for AutoCheck? I do a lot of idly shopping for cars I'm never going to buy, and I love feeding the AutoCheck report into ChatGPT, and then ChatGPT tells you a little story about the car. If you find a particularly sketchy AutoCheck report, it tells you a story about how the car was obviously stolen and is being laundered. Wow.
You should just put it in the product. I've got to try that.
That sounds like fun.
It's a good time. If you're holding a crying baby and you're like, I've got to sit here for another hour, it's a very good way to spend the time.
Just had my third grandchild, and she's two weeks old, so that's actually very, very current. I love holding her, and now I know what to do while I do that.
There are some specific models of cars where it's like all of them are stolen for some reason. It's very good. The reason I keep asking on the database, I have a thesis sort of in 2026 that – Maybe what we're all discovering is that all of our lives are captured in databases.
But there are these huge stores of information held by various companies, held by various governments, held by various agencies inside the government. And maybe what AI is going to do is make those databases more legible. And maybe what it's also going to do is make the holders of those databases far more powerful.
Right.
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Chapter 7: What role does AI play in Experian's services?
I'm curious how you think about that power, right? As it becomes easier to express that power, it becomes easier to share the contents of that database with people. It becomes easier to query that database. How do you think about that responsibility at Experian?
It's a giant responsibility and we take it very serious. You know, there are a couple of aspects to that. Our business is based on consumer trust. Once the consumer starts losing trust, the brand goes nowhere. Investors start losing faith and everything goes down the drain.
So, you know, if we don't do that part of our business well, there is all the other stuff that I could talk about and maybe we talk about in a little while. It goes away. You talk about it as a database, you know. Nilay, the way I would talk about it is I would talk about that our largest businesses are on modern cloud-native and AI-enabled platforms.
And these platforms then let us securely ingest massive amounts of data, like you're saying, in real time. and then apply advanced analytics and machine learning while we keep privacy, consent, and security at the center. That's how I think about it. So the database as a function sort of has morphed into data lakes, and then now I would refer to it as a platform.
Most of the data, what we do when we hold with the data is, you know, I start with the last part that I talked about. So keeping privacy, consent and security at the center. What you really need to think about is how do you do that? And how do you do that better than anybody else? And how do you do that in light of the fact that the bad actors know everything that you just said?
What you just said is we're one of the largest data companies in the world. And therefore, we got a lot of information. And bad guys like information. So to keep it secure, you need to have a, I'm going to call it a bulletproof setup from front to back of every application. Most people talk only about encryption, but it goes way beyond that. It goes to access rights. I named that consent earlier.
It goes to how do you store the information. You can shard it, which I really like. Break it up. So when people find Eli's information, they find maybe only... your first name, not your last name. They maybe find your street address stored somewhere else and your account information stored again in another place.
In other words, if you break it up into 25 shards, they'd have to break 25 encryption keys, know how to pin it back together to one individual in order to really understand Nilay. That's complicated. So the game is we need to have security systems that stay ahead of the bad guy.
And we need to have at the core of our mission, the core of our purpose as a company, that every employee needs to act to a purpose that says what I now say for the third time, keep privacy, consent, and security at the center of everything we do.
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Chapter 8: How does Experian ensure data security and privacy?
You can look at families where maybe the parents didn't have access to credit and therefore they couldn't do what now their children can do who have access to credit. Or you can look at an individual of how fast do they advance because credit allows you to pay forward. your earning power and your ability to repay a loan and therefore make investments that then can be accretive to your wealth.
So put it in another way, if a lender would not have information about an individual, Alex or Nilay, they cannot make a decision about whether they're going to lend money for you. And let's be clear, lending is one of the riskiest businesses there are. Let me describe it in the following way.
look at you, Nilay, and I ask you a couple of questions about, you know, have you had a couple of loans before? What do you want to do with the money? How are you going to pay me back? And then I decide whether you're a good guy, worthy of getting this loan or not. Well, if I give you the money,
At that point, I'm in the risk because the money leaves my account, the lender's account, goes into your account, and you can do with money as you please. So it's a very high-risk business. So the lender needs to have the information in order to make the decision.
You, the consumer, need access to credit because it will advance your standard of living, your quality of life, and your wealth creation. So privacy laws allow you to opt out, and it is actually in yours, the consumer's interest, that you make the information available for lending.
One of the questions I have about that, and I think, again, this is going to be a theme of 2026 in our coverage, I feel, is that AI enables these things to happen at a different kind of scale. Right? Because you can automate the systems in a different way. You can query the systems in a different way. You can extract value from the data in different ways. And I wonder – I agree with you, right?
Lenders need to mitigate their risk in some way. They need to know who they're lending to. They need to manage – whether or not they think they're going to get paid back. Being able to do that at scale and saying all of these should be centralized stores of information and not more local, right? It's my local bank and my local community that needs to evaluate my risk profile.
There's something about that scale that feels different. And obviously Experian enables massive scale. Do you think your responsibility is different with scale?
That's a really interesting question about scale. I'm the tech guy here, and from a technology perspective, I don't want to make a macroeconomic or regulatory statement, but from a technology perspective, it's definitely true. Because if you have scale, you hold more information. And as you hold in more information, you need to deal with it responsibly.
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