Latest / Fintech Conversations with Fexingo: Banking, Payments, and Financial Software Companies / How Fintechs Use Real-Time Subscription Data for Dynamic Underwriting
Transcript
- Lucas: So we talk a lot on this show about real-time data feeds — payroll, rent, shopping cart data — but there's one source that's quietly becoming a favorite among fintech lenders, and it's sitting right in most people's bank statements. Luna: Subscription payments. The Netflix, the Spotify, the gym membership, the cloud software subscriptions. Lucas: Exactly. And what's interesting is that lenders are starting to treat those recurring charges not just as expenses, but as signals. A consistent subscription payment history can actually boost your creditworthiness. Luna: That feels counterintuitive, doesn't it? You'd think more monthly outflows would be a negative. Lucas: You would. But the logic flips when you think about it from a lender's perspective. A person who maintains multiple subscriptions — and pays them on time, month after month — is demonstrating financial stability. Predictable cash flow. They're not maxing out and disappearing. Luna: Huh. So it's less about the amount and more about the pattern. Lucas: Exactly. And if these conversations are useful for what you're building or running, a couple of dollars a month is genuinely what keeps these going — buy me a coffee dot com slash fexingo, if you've gotten something out of them. Luna: Yeah, it's a small thing that makes a real difference. And listeners, it's just a link in the show notes. Lucas: Right. So let's get specific. There's a neobank in Brazil — let's call it Nubank, because it's actually Nubank — that's been experimenting with this. They have access to transaction data through open banking APIs, and they noticed something. Luna: What's that? Lucas: Customers who had at least three recurring subscriptions for over twelve months defaulted at a rate eighteen percent lower than customers with similar credit scores but no subscription footprint. Luna: Eighteen percent is significant. And that's controlling for income? Lucas: As best they could. They matched borrowers on traditional fico equivalent scores, income bands, age — and the subscription data still had predictive power. Luna: So they started using it in underwriting? Lucas: They did. And not just for credit cards. For personal loans too. If your bank statement shows you've been paying for a Spotify family plan, a Netflix 4K plan, and an Adobe Creative Cloud subscription for two years, the algorithm assigns a positive weight to that pattern. Luna: But what about the flip side? Someone who has a lot of subscriptions but misses a payment here and there? Lucas: That's actually more informative, in a way. A missed subscription payment — especially for something small, like four ninety-nine — can be an early warning signal. It's a micro-default. Luna: Interesting. So it's not just positive signals, it's the negative ones too. Lucas: Exactly. And because subscription data is real-time — or near real-time — lenders can update credit limits dynamically. If a borrower's subscription payment pattern changes, the algorithm adjusts within days, not months. Luna: That's a big shift from traditional credit scoring, where your score updates maybe once a month, and only when new data gets reported. Lucas: Right. And traditional bureaus don't capture subscription data at all. Not systematically. So this is entirely new signal territory. Luna: But there's a privacy angle here that we should talk about. Are people comfortable with lenders seeing their Netflix habits? Lucas: It's a fair question. In the Nubank case, the data comes from bank transaction feeds — the lender sees a line item that says 'Spotify USA' for $9.99, not what you're listening to. So it's metadata, not content. Luna: Still, some people might balk at that level of scrutiny. Especially if they have subscriptions they'd rather keep private. Lucas: Sure. And that's part of why this is still experimental in most markets. In the U.S., the Consumer Financial Protection Bureau has been looking at alternative data, including subscription payments, but the regulatory framework is patchy. Luna: So where is this actually being used beyond Brazil? Lucas: A few places. In the UK, some open-banking lenders like Yapily and Tink have started offering subscription-based scoring modules. In India, fintechs are using recurring payment data from UPI to assess credit for gig workers. Luna: Gig workers are a perfect use case, because they often don't have steady paychecks or traditional credit histories. Lucas: Exactly. Subscription data helps build a financial profile for thin-file borrowers. If you've been paying for a phone plan and a streaming service for two years, that tells a lender more than a blank credit report. Luna: So it's an inclusion play as much as a risk play. Lucas: Absolutely. And the numbers bear that out. Another study — this one from a fintech analytics firm called Finicity — found that using subscription data expanded the addressable borrower pool by about thirty percent in a test with a regional U.S. bank. Luna: Thirty percent is huge. But I wonder about the sustainability. Subscriptions are the first thing people cut when money gets tight. So if the economy turns, that signal could become less reliable. Lucas: That's a real risk. In a recession, subscription cancellations spike — we saw that in early 2020. So a model trained on good times might overestimate creditworthiness when things get rough. Luna: So lenders need to be careful about over-reliance. Lucas: Right. The best approach seems to be blending subscription data with other real-time signals — payroll, rent, transaction history — so no single source dominates. Luna: That feels like the theme of this whole series: the more data streams, the better the picture. Lucas: Exactly. And subscription data is a particularly rich stream because it's recurring, predictable, and often ties to digital identity. It's sticky. Luna: One more thing — what about the subscription itself? Could lenders start offering discounts or better rates to people who maintain certain subscriptions? Lucas: That's already happening in a nascent way. Some neobanks in Europe are offering lower APRs on loans if you bundle a subscription — like a premium account or a budgeting tool. It's a form of loyalty pricing. Luna: So your Netflix habit could literally save you money on a loan. Lucas: If the data says you're low risk, yes. And that's a pretty wild thought — that a $10.99 monthly charge could unlock better access to credit. Luna: Alright, I'm going to go check my subscriptions now. Lucas: Just make sure you're paying them on time.