The Indonesian Fintech Gold Rush: How Startups Convinced Investors That Fishermen Were the Next Unicorns
So, you want to build a startup. But not just any startup. A billion-dollar one! You’ve got zero background in finance, rural economies, or lending, but what you do have is a MacBook, a GoWork membership, and an insatiable hunger for venture capital.
Now, you just need a Big, Sexy Idea. Something that makes investors feel like they’re funding the future of humanity instead of just another app that burns money.
Enter Indonesia’s P2P lending and agri-fintech sector.
Your new pitch? "We will revolutionize financial inclusion by lending money to farmers and fishermen; people who have no banking history, no collateral, and a highly unpredictable income."
Here’s the playbook:
Find an “untapped market” that isn’t untapped so much as completely unserviceable.
Throw in some "AI-powered" nonsense, because nothing says trustworthy lending like a machine learning model trained on absolutely no relevant data.
Promise scale and disruption! Sure, no one has successfully made rural lending work, but maybe you’re just smarter than all of finance.
Investors eat it up. Money flows in. The company skyrockets in valuation.
Then, reality hits.
Borrowers default en masse. Investors realize they’ve funded a glorified charity with compound interest. Regulators start asking questions.
Now? The founders are pivoting, the VCs are pretending they were never involved, and fishermen are stuck repaying loans instead of buying new nets.
Who could have possibly predicted this?
The Billion-Dollar Fantasy: Convincing Investors That Fishermen Were Credit-Worthy
Venture capitalists are suckers for a good story, and nothing gets their wallets trembling like an untapped market that sounds huge but remains conveniently unverified. So, when some ambitious fintech founders walked in and declared, “Indonesia’s rural economy is a $50 billion opportunity just waiting to be disrupted!”, investors didn’t ask basic, logical questions like:
“Wait… why has no one tapped this before?”
“Is there a reason banks, which specialize in lending, avoid these borrowers?”
“Are we, perhaps, making an enormous mistake?”
Of course not. That would be boring. And if there’s one thing VCs hate, it’s boring.
But here’s the little technicality no one wanted to discuss:
These borrowers weren’t “unbanked” because financial institutions had cruelly ignored them. They were unbanked because they were terrible credit risks.
No stable income. No collateral. No formal records of financial behavior. The kind of red flags that typically make banks say, “Yeah, we’re good, thanks.”
But fintech startups didn’t let little things like “financial viability” get in the way. Instead, they did what every great startup does: create a flashy PowerPoint, fill it with terminology, and make sure the growth projections point aggressively skyward (never mind that they were entirely fictional).
Their strategy? Blind confidence and even blinder underwriting.
🚀 “AI-powered lending models will unlock a $50 billion market!” (Translation: We have no actual underwriting process, but we trained a model to approve anyone who says they own a boat.)
🤖 “Alternative credit scoring means we can assess risk in new ways!” (Translation: If they have a heartbeat, they get a loan.)
🌾 “We’re revolutionizing the way farmers access capital!” (Translation: We’re handing out loans to people who think ‘interest rates’ refer to how much people like them.)
Investors ate it up.
No due diligence, no second-guessing, just a blind sprint to fund “the next big thing.” Because nothing gets a VC’s adrenaline pumping like the promise of being early in an “untapped market.”
Never mind that the only predictable thing about lending to fishermen was that they'd predictably default. Never mind that their livelihoods depended on things like fish migration patterns and weather conditions; not exactly factors you can plug into an AI risk model.
But as long as those graphs kept climbing and the funding rounds kept coming, who cared?
Inflating Numbers & Playing the "Who Can Lie More Convincingly?" Game
The great thing about lending to borrowers who exist in the financial equivalent of a black hole is that nobody can verify anything. How many loans were given? Who actually repaid? Is Fisherman B even a real person?
These questions were deeply inconvenient for the fintech startups that had already promised investors explosive growth and market dominance.
So, what do you do when your numbers don’t look quite as impressive as your PowerPoint suggested they would?
You make stuff up.
🚀 Strategy #1: Loan Churn Disguised as Growth
Here’s how you turn zero actual growth into record-breaking expansion:
Fisherman A borrows money.
Fisherman A realizes he cannot possibly repay.
Fisherman A takes out another loan to cover the first loan.
Startup reports “200% increase in loan disbursement.”
If Wall Street banks can create synthetic derivatives, why shouldn’t a fisherman in Sumatra be allowed to take out six loans at once?
💸 Strategy #2: Bulk Lending to Fake Cooperatives
Since lending to individuals required at least some effort, startups discovered a workaround:
Instead of verifying borrowers, just hand out giant loans to "cooperatives," which are vaguely defined entities that supposedly represented groups of fishermen.
The problem?
Many of these cooperatives weren't real.
Money was taken, split between middlemen, and vanished into the abyss.
The startup still counted these loans as “active users” in their investor updates.
If the money technically left the platform, it counts as growth, right?
🛶 Strategy #3: Approving Literally Everyone
These fintechs promised sophisticated AI-driven underwriting, powered by cutting-edge machine learning, that could assess rural borrowers with pinpoint accuracy.
What they actually did:
Do you have a boat? Loan approved.
Can you borrow someone else’s boat for a photo? Loan approved.
Can you vaguely gesture towards the sea and say ‘boat’? Loan approved.
When default rates hit 50%+, did the fintechs panic?
Of course not.
Instead, they assured investors that their “risk models were performing as expected.”
Which, to be fair, was technically true... if the expectation was “complete and total financial collapse.”
The Fallout: When The Fish Stopped Paying Their Loans
Fast forward a few years, and (surprise!) the fintech lending boom collapsed under the sheer weight of its own nonsense.
Who could have guessed that lending large sums of money to people with no credit history, no collateral, and an income entirely dependent on the weather wouldn’t turn out to be a sustainable business model? (Oh right, banks. That’s why they never did it in the first place.)
Some fintechs collapsed due to blatant fraud others simply ran out of fresh suckers to lend to; or, more crucially, ran out of new investors to keep the Ponzi cycle spinning.
For years, these companies managed to keep the dream alive by shuffling money around, inflating user numbers, and raising bigger and bigger rounds to cover up the mess.
But eventually, something dreadful happened.
The fishermen stopped paying.
Suddenly, the magical, fast-growing fintech lending sector looked a lot less like the future of finance and a lot more like a really dumb idea that just got very expensive.
And just like that, OJK (Indonesia’s Financial Services Authority) suddenly remembered it had a job to do.
Because nothing makes a government spring into action faster than:
Thousands of rural borrowers drowning in unpayable debt.
Debt collectors making threats that range from “mildly concerning” to “full mafia movie.”
By then, the damage was done. But don’t worry, the fintech companies had a plan.
What's Next? The Next Fintech Scam Is Already Brewing
If you think this was the last fintech Ponzi scheme, I have a bridge in Brooklyn to sell you.
Venture capitalists may have burned billions funding bad loans, but don’t worry, the startup machine never stops.
There’s always a new way to repackage old failures, slap on some fresh paint, and sell it to investors who, frankly, have the attention span of a goldfish swimming in venture capital.
So, what’s next? Here’s a sneak peek at the next fintech disaster in waiting
💸 “Sharia-Compliant” Lending (Now with Extra Moral High Ground!)
New pitch: "It's not interest! It’s a profit-sharing model!"
Translation: Same unsustainable lending model, but now with religious branding.
The logic is simple: If predatory fintech lending failed when it was just regular old capitalism, surely it will work if we rebrand it with Islamic finance terminology!
Debt is bad? No problem! We’ll call it “cost-plus financing.”
Interest is forbidden? That’s okay, we’ll just charge “service fees” so high they look exactly like interest.
People still can’t afford to repay? Well, that’s between them and their faith now, isn’t it?
The end result? The same cycle of financial ruin, except with added religious legitimacy.
🤖 AI-Based Loans (Because That Worked So Well Last Time)
New pitch: "AI can now predict rural borrowers' ability to pay!"
Reality check: AI is not magic. No amount of machine learning can make a fisherman’s income less dependent on the weather.
But that won’t stop fintech founders from convincing investors that AI will “fix” credit risk. Because why learn from past mistakes when you can just automate them faster?
Get ready for:
“Predictive repayment models” (Translation: The same broken lending system, but with fancier math.)
“Smart contracts for lending” (Translation: Code that automatically enforces bad loans.)
“AI-powered risk assessment” (Translation: A random number generator with an MBA.)
The results? Exactly the same.
🪙 Tokenized Agri-Finance (Putting This on the Blockchain, Because Why Not?)
“What if farmers repaid loans in crypto?” (What if we just didn’t give loans to people who clearly won’t pay them back? No? Okay, never mind.)
If there’s one thing fintech grifters love more than P2P lending, it’s pretending blockchain will fix financial inclusion. So, naturally, the next pitch is:
“Let’s tokenize agricultural finance! Farmers will repay loans in our custom crypto token!”
And investors, instead of asking basic questions like:
“Why would a rural fisherman want to be paid in a volatile digital asset?”
“What happens when the token’s value crashes?”
…will instead nod enthusiastically and throw millions at the idea, because blockchain makes everything sound futuristic and vaguely legitimate.
The best part? None of this is new. It’s the same terrible lending model, just with a slightly different scam structure.
Give it another 6–12 months, and we’ll be right back here, watching another wave of fintech startups convince investors that this time, really, truly, definitely, rural lending will be profitable.
The Indonesian fintech lending disaster was a perfectly predictable trainwreck that everyone chose to ignore.
Startups pitched an obviously broken idea (but with lots of charts and jargon).
Investors shut off their brains and threw in money anyway.
Numbers were inflated beyond recognition to keep the dream alive.
Borrowers defaulted en masse (because fishermen don’t suddenly develop stable incomes just because an AI model says so).
And now? We’re left picking through the wreckage while the founders quietly update their LinkedIn profiles.
And yet… this isn’t the end.
If history has taught us anything, it’s that the fintech grift is eternal.
Right now, somewhere in Jakarta, a new startup is pitching VCs the exact same broken idea, just with a slightly different color scheme.
And guess what? Investors will buy in again.
Because who needs sustainable business models when you have hype, FOMO, and a PowerPoint deck featuring graphs that only go up?
See you all in 2029, when we’ll be scratching our heads wondering:
"Wait… why did we think AI-powered blockchain fish loans were a good idea?"