I remember grabbing coffee with a founder a few years back. Bright guy, incredible idea, tons of grit. But he kept hitting a wall. He couldn’t get a business loan to scale his inventory. Why? Because his credit history was thin. He’d been bootstrapping, paying for everything in cash, and the traditional banks just saw a ghost. It was frustrating to watch a great entrepreneur get held back by such an outdated system. That’s not a unique story. Billions of people around the world are either unbanked or underbanked, locked out of the financial system that could help them build a better life.
For too long, the financial system has excluded billions of people. But AI is starting to change that. I’ll show you the inspiring ways that AI is being used to promote financial inclusion and give everyone a fair shot.
The Broken System
The traditional way of assessing creditworthiness is broken. It relies on a handful of data points that don't tell the whole story. Things like your credit card history, mortgage payments, and car loans. If you're young, a recent immigrant, or someone who's always been responsible with cash, you're basically invisible to the banks. It's a catch-22: you can't build credit without getting credit, and you can't get credit without having a credit history. It’s a system that was designed for a different era, and it’s failing a huge portion of the world’s population.
AI-Powered Alternative Credit Scoring
This is where AI comes in. Instead of just looking at your credit history, AI algorithms can analyze thousands of alternative data points to get a much more accurate picture of your financial health. We're talking about things like:
- Utility payments: Are you paying your electricity and water bills on time?
- Mobile phone usage: Your data top-up patterns can be a surprisingly good indicator of financial responsibility.
- Rent payments: A long history of paying rent on time is a huge green flag.
- Supplier and customer data: For small businesses, their relationships with suppliers and customers can show a lot about their financial stability.
By looking at this broader set of data, AI can identify creditworthy individuals and businesses that the traditional system would have overlooked. I’ve seen this firsthand with some of the companies I’ve invested in. They're using AI to build credit models that are not only more accurate but also fairer. They're giving people like that founder I mentioned a chance to prove themselves.
Banking in Your Pocket
Another huge barrier for the underbanked is the cost and inconvenience of traditional banking. Maintaining a bank account can be expensive, with all the fees and minimum balance requirements. And if you live in a rural area, just getting to a physical bank branch can be a major challenge.
AI-powered mobile banking platforms are turning this model on its head. By automating many of the back-end processes, these platforms can offer low-cost, or even free, banking services. And because they're accessible through a smartphone, they can reach people in the most remote corners of the world. Think about it: you can open an account, check your balance, pay bills, and even get a loan, all from the palm of your hand. It’s a revolution in financial access.
Your Personal AI Financial Advisor
But it's not just about access to basic banking services. AI can also provide personalized financial guidance to people who could never afford a human financial advisor. AI-powered tools can help you:
- Create a budget: Track your income and expenses and see where your money is going.
- Set savings goals: Get personalized recommendations on how to save for a down payment on a house, your kid's education, or retirement.
- Make smart investments: Even with small amounts of money, AI can help you invest in a diversified portfolio and grow your wealth over time.
This is incredibly powerful. It’s like having a financial expert in your pocket, helping you make smart decisions and build a more secure financial future.
My Take
As an entrepreneur and investor, I’m incredibly excited about the potential of AI to create a more inclusive financial system. I’ve backed over 200 companies, including some of the biggest names in AI like Anthropic, OpenAI, and Scale AI, because I believe in the power of technology to solve real-world problems. And financial inclusion is one of the biggest problems we face.
Of course, there are challenges we need to address. We need to make sure that the AI algorithms we use are fair and unbiased. We need to protect people's data and privacy. But these are solvable problems. The potential rewards are just too great to ignore.
We're at the beginning of a new era in finance. An era where your financial future isn't determined by your past, but by your potential. An era where everyone, regardless of their background or circumstances, has the tools and support they need to thrive. It’s not going to be easy, but I’m confident that with the help of AI, we can build a financial system that works for everyone. The future of finance is not just about making money; it's about making a difference. And that's a future I'm excited to be a part of.
Frequently Asked Questions
How has this view evolved over time?
My thinking on most topics has changed significantly over the years. Early in my career, I held many conventional views that experience proved wrong. I try to update my beliefs when the evidence changes.
What's the most common pushback you get on this?
People often push back by citing exceptions or edge cases. And they're usually right that exceptions exist. But building a strategy around exceptions rather than patterns is a losing game for most founders.
What experience informs this perspective?
This perspective comes from over a decade of building companies in Silicon Valley, two successful exits (RemoteTeam to Gusto, MovieLaLa to Gfycat), and investing in 200+ startups including Anthropic, OpenAI, and Scale AI. I write about what I've lived.
How can I apply this thinking to my own situation?
Start by identifying the core principle behind the opinion, not the specific example. Then ask yourself: does this principle apply to my context? If yes, test it in a small, low-risk way before going all in.