AI and money in 2026: what nobody’s telling you

6 min read

You applied for a loan. It was approved in 8 minutes.

Hace tres años eso era imposible. Hoy es lo que hacen Santander, BBVA y media docena de fintechs españolas cada día. Este proceso lo hace una máquina; está todo superautomatizado.

La verdad es que yo empecé a leer sobre esto pensando que no era algo que fuese conmigo, que era para gente más metida en el «mundillo».

Money doesn’t work the way it used to

El número que voy a decir igual es difícil de creer, pero el mercado de inteligencia artificial en fintech valía 17.100 millones de dólares en 2025. En 2026 ya está en 20.600 millones. Y se espera que llegue a 76.200 millones en 2033. Sin duda, un crecimiento exponencial, que es una locura.

En menos de dos años pasó de experimento a producción en 6 sectores.

En España, el 68% de las empresas del sector financiero ya tienen algún sistema de IA funcionando. No hablo de piloto experimental, sino de producción real, tomando decisiones sobre tu dinero ahora mismo. Y en LATAM, el 86% de las fintechs que adoptaron IA redujeron sus costes operativos un 44% de media. Cuando bajas costes así, algo cambia en cómo funciona el negocio. Y ese cambio siempre acaba llegando al cliente en mayor o menor medida.

Lo que me llama la atención de todo esto es la velocidad. La IA hace cosas en segundos que antes requerían días, analiza con una precisión que ningún equipo humano puede igualar a ese precio, y no para. No tiene días malos, no se pone enferma, solamente trabaja incansablemente y cada vez realiza el trabajo con mayor calidad.

¿Para qué usan en la banca la IA?

Cuando digo que la IA está en las finanzas, no me refiero a un chatbot que te dice el horario de la sucursal. Me refiero a cosas con bastante  más relevancia.

Detecting fraud before it happens

This is where AI has been working the longest. Current systems analyze thousands of transactions per second looking for unusual patterns. A purchase in Madrid and another in Tokyo one minute apart. A payment at 4 in the morning at a shop you’ve never bought from.

The result: fraud losses have fallen 40% on platforms using these systems. AI isn’t infallible — there are false positives, cases it misses — but it’s enormously better than previous methods. 64% of banks already use AI specifically for this, according to Capgemini.

Approving or rejecting loans

The traditional process took at least 48 hours. An employee reviewed documents, made calls, consulted databases. Now there are systems that do all of that in 8 minutes. AI cross-references your credit history, income, spending behavior, and hundreds of variables at once.

This has two sides. The good: the process is faster and, in theory, more objective. The less good: if the model has biases in its training data, those biases affect who gets financing. It’s a real problem that doesn’t get much public discussion.

Investment management and market analysis

Robo-advisors have been around for years, but in 2026, 55% of their users already trust the algorithm more than a human advisor. That’s a huge shift.

Tools like Indexa Capital in Spain use AI to analyze your risk profile, study market charts, cross-reference company results, and adjust your portfolio automatically. It does in seconds what a human would take days to do.

What changes for you

All of this sounds like something that happens in executive boardrooms. But it has direct consequences in your daily life.

Your financial data is worth more than you think

When you accept the terms of a financial app, you’re giving access to a very detailed behavioral pattern: where you spend, how much, when, on what. That data feeds models that then decide whether to give you a loan, what product to offer you, or what customer segment to put you in.

I’m not saying that’s bad. I’m saying it’s good to know.

Credit decisions are made in ways you can’t see

If the bank denies you a loan today, the decision might have been made by a model that nobody has asked to explain itself. In Europe there’s a right to an explanation when an automated decision affects you — it’s regulated by GDPR — but few people exercise it because few people know it exists.

Autonomous payments are going to increase

Forrester estimates that by the end of 2026, a third of business-to-business payments will be managed by AI agents completely autonomously. Today it’s in business environments. In two or three years it’ll reach consumers. Your insurance, your subscription, your mortgage — renewed and renegotiated by an agent acting on your behalf.

That can be very useful. Or it can be a problem if you don’t understand what that agent is authorizing in your name.

Why I think it’s worth staying informed about this

AI is changing the economy in a way that won’t wait for people to be ready. It moves fast. And the difference between people who understand what’s happening and those who don’t will show in concrete decisions: which bank to choose, which tools to use, how to protect your data, how to make the most of what already exists.

You don’t need to study machine learning or know how to code. You just need to read a bit, understand the basic concepts, and keep up with what changes.

On this blog I write about AI tools that I use directly for my work - such as Claude Code and his most useful skills - And what always amazes me is how quickly these things go from "experimental technology" to "something everyone uses without thinking about it". It's going to be the same with finance.

Some people are already using AI to make better financial decisions — analyzing their spending, comparing products, understanding contracts. And some people don’t even know those tools exist. That gap is going to keep growing.

Conclusion

When I started researching this I didn’t expect to find what I found. I thought it was going to be a complex topic, full of numbers and bankers. It turns out it’s one of the most tangible changes AI is bringing to everyday life, and one of the least talked about outside the sector.

I’m not an economist or financial analyst. I’m someone who’s been following the world of AI for a while and one day decided to look at how it was affecting money. And what I found seemed important enough to write about here.

Money and technology are increasingly intertwined, and a minimal understanding of how that relationship works is no longer optional. It is part of being informed in 2026.