Once, creditworthiness was judged by a handshake and a gut feeling—or so the stories go at family dinners. Fast-forward to today, and it sometimes feels like your smartphone knows more about your character than your local banker ever did. In a world where your selfies and swipes are data points, this post questions: What if being 'the product' doesn't have to mean losing your dignity? Join us as we journey from TikTok-style data grabs to privacy-centric alternatives that aim to put people, not just numbers, at the heart of credit decisions.
From Adware Nightmares to Device Metadata: How Data Collection Shapes (and Misshapes) Us
1. Social Media: When “Free” Isn’t Really Free
He scrolls through TikTok or Instagram, and wonders—how much do they know about him? It’s not just his name or email. It’s every like, every pause, every odd hour he checks his phone. These platforms collect every single personal detail they can grab from a device. Why? To deliver “better” ads. But better for whom? Not the user, that’s for sure.
As one industry insider bluntly put it:
"Every time the product is free, guess what? You are the product. So your time is being monetized."
That’s the trade-off. Free apps, endless entertainment, but the cost is privacy. He’s not just a user—he’s the commodity.
2. That Creepy Feeling: Midnight Snacks and Data Trails
She downloads a free app to track her sleep. Suddenly, ads for cookies pop up at midnight. Coincidence? Maybe. Or maybe not. There’s that uneasy feeling—how did the app know her cravings?
It’s not paranoia. Many apps quietly harvest data: location, habits, even the time she opens the fridge. The more they know, the more they can sell. It’s unsettling. Feels a bit like someone’s always watching, even in the dark.
3. Fintech’s Alternative: Only What’s Needed, Nothing More
Now, contrast this with privacy-focused fintech startups. They don’t want everything. They don’t need it. Take Credolab, for example. Instead of hoarding data, they focus on what’s essential—just enough to assess risk or prevent fraud. And only with explicit user permission.
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Minimal Data Collection: Only the data required for credit assessment or fraud checks.
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Consent-Driven: Users must opt in. No sneaky permissions, no hidden tracking.
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Purposeful Use: Data isn’t sold to advertisers. It’s used to help people access mainstream financial services.
He might wonder: Is this just marketing spin? But the numbers back it up. Credolab operates in 52 countries. Their reach is global, but their approach is local—respecting privacy laws and cultural expectations.
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44% of revenue comes from Latin America and North America.
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42% of revenue comes from Southeast Asia, their original home base.
That’s not small potatoes. It’s a sign that privacy and inclusion can go hand in hand.
4. Why Does It Matter?
He thinks about it. She does too. What’s the real cost of a free app? Is it worth trading privacy for convenience? Social media giants see users as data points to be mined. Fintechs like Credolab see them as individuals, deserving of respect—and a fair shot at financial inclusion.
It’s not a perfect world. Some apps will always push the limits. But there are alternatives. There’s a way to use technology without feeling exposed.
Maybe, just maybe, the next time he downloads an app, he’ll pause. Who’s really benefiting? Who’s collecting what? And is he, once again, the product?
Rethinking Unscorables: When Credit Traditions Fail, Can Behavior Fill the Gaps?
Who Are the “Unscorables”?
A surprising number of people get rejected for loans or credit cards. Not because they’re risky. Not because they did something wrong. But simply because there isn’t enough data about them. As one expert puts it:
'Unscorable customers are simply unscorable because there is not enough traditional data.'
Think about it. Maybe someone just moved to a new country. Maybe they’ve never had a credit card. Or maybe the credit bureau systems just missed them. Whatever the reason, the result is the same: the system says “no.”
Why Traditional Credit Data Falls Short
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Gaps in credit bureau records: Not everyone has a long history of loans or bills.
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Telco data isn’t enough: Even if a bank tries to use mobile phone data, it only works if they access all providers. If not, there’s a 50% hit rate gap. Half the people are still invisible.
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Data asymmetry: Some get scored, others don’t. It’s not fair, and it’s not efficient.
So, what happens? Most banks just reject applicants they can’t score. No data, no deal. Simple, but not exactly smart.
Can Behavior Fill the Gaps?
Here’s where things get interesting. What if lenders could look at how someone behaves—not just what’s on paper? That’s what companies like Credolab are doing. Instead of relying on old-school credit reports, they analyze device metadata and behavioral patterns.
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Device metadata: Tiny bits of information from a smartphone or computer. Things like how often someone updates their info, or what apps they use.
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Behavioral patterns: Does the person keep changing their reported income? Are there lots of crypto wallets or gambling apps installed? These can be red flags.
It’s not about snooping. The data is anonymized and stripped of personal details. In fact, the whole package is just 50 kilobytes—about the size of a single photo. And it’s processed in under a second.
What Banks Can (and Can’t) Really Know
Let’s be real. Banks can’t see everything. But they can spot patterns. For example:
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Field revisions: If someone says their income is €2,000, then changes it to €5,000, that’s suspicious. Maybe they’re just fixing a mistake. Or maybe they’re trying to get a bigger loan.
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Crypto wallets and gambling apps: A high number of these often means a higher risk of default. It’s not a guarantee, but it’s a clue.
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Selfie ratio: Oddly enough, lots of selfies compared to regular photos can also signal risk. Who knew?
Banks used to miss these signs. Now, with behavioral biometrics, they can flag potential fraud or manipulation—sometimes before it happens.
Why It Matters
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Fairness: More people get a fair shot, even if they’re new to the system.
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Speed: Decisions happen fast. No waiting weeks for paperwork.
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Privacy: No personal data leaves the device. Just patterns, not names or faces.
Of course, no system is perfect. Sometimes, genuine people get flagged. Sometimes, clever fraudsters slip through. But for the “unscorables,” this new approach is a game changer. It’s not just about numbers anymore. It’s about understanding people—one behavior at a time.
Debunking Misconceptions: The Myth of Universal Data and the Importance of Local Context
It’s tempting to think data is universal. Numbers are numbers, right? But when it comes to credit, risk, and the so-called “alternative data,” the reality is far more complicated. He might assume that what works in New York will work in Nairobi, or that a lender in London can just copy-paste a US playbook. That’s not how it works. Not even close.
Why US-Centric Notions of 'Alternative Data' Miss the Mark Globally
Many professionals—especially those based in the US—see alternative data through a narrow lens. They focus on things like rent payments, utility bills, or bank transaction histories. These are easy to access in some markets. But elsewhere? She might find there’s no rent data. No utility bill records. Sometimes, not even a basic credit infrastructure. It’s a different world.
The assumption that these data sources are available everywhere is, frankly, a myth. It’s a US-centric view that doesn’t hold up in emerging markets or regions where digital infrastructure is still developing. When lenders rely only on these familiar sources, they miss out on huge opportunities—and sometimes, they simply can’t operate at all.
Local Access (or Lack Thereof) Changes the Rules
He might wonder, what’s the alternative? In many markets, the answer lies in device data, telco records, or behavioral signals. These aren’t “new” sources. They’ve been around for years. But for some lenders, they’re only just discovering them. The irony? Device and telco data have been proven, again and again, to be reliable predictors of creditworthiness.
But there’s a catch. Accessing new data layers can add friction. She’s seen it happen: a lender asks a customer to connect their bank account. Suddenly, a new popup appears. The customer has to remember their login details. They have to trust the lender with sensitive information. Many just give up. The onboarding journey ends before it even begins.
Encouragement for Risk Professionals: Think Beyond Transactional Data
It’s time for risk professionals to broaden their horizons. Don’t get stuck on transactional data. There’s a whole world of alternative data out there—data that isn’t traditional, but is just as valuable. As one expert put it,
'The very definition of alternative data is everything that is not traditional. So don't focus only on transactional data.'
He might hesitate, thinking, “But is it safe? Is it accurate?” The answer: yes, if used wisely. Device and behavioral data can offer deep insights, sometimes even more than a bank statement ever could. But it’s not about piling on more data for the sake of it. It’s about finding the right balance—enough information to make a fair decision, but not so much that customers abandon the process.
Conclusion: Rethinking Data, Rethinking Credit
In the end, there’s no such thing as a universal data set. What works in one country might be impossible in another. He, she, or they—every risk professional—needs to recognize that local context matters. It’s not just about plugging in more numbers. It’s about understanding people, their behaviors, and the unique realities of each market.
The future of credit isn’t about squeezing everyone into the same box. It’s about flexibility, creativity, and respect for local differences. That’s how real progress happens. And maybe, just maybe, that’s how we finally start seeing people as more than just data points.
TL;DR: Modern credit assessment doesn’t have to sacrifice privacy or individuality. By blending behavioral data, device metadata, and strict privacy standards, forward-thinking fintechs are redefining risk—and giving the so-called ‘unscorable’ a fair shot. Rethink what’s possible for creditworthiness in the digital age.
Youtube: https://www.youtube.com/watch?v=RW4cNGujppQ
Libsyn: https://globalriskcommunity.libsyn.com/michele-tuci
Spotify: https://open.spotify.com/episode/6Vg19G0xS8JtDRCYkUl4kK
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