Alternative Data: Technology Needs Humanity to Function

We have seen technology implementations that do not deliver the expected results. Not because the technology is bad, but because something fundamental is missing: understanding what we do with it and, above all, how it impacts the people on the other end.

Adding additional information, such as alternative data, is relatively straightforward. Today, there are numerous sources of information capable of enriching an analytical model. However, using them responsibly is an entirely different challenge. That’s where the real work begins.

The Illusion That More Information Is Enough

When we incorporate alternative data into an assessment or scoring model, the logic seems obvious: more information should lead to better decisions.

But that idea is only true when there is a clear purpose behind each piece of data used.

It is possible to analyze hundreds of variables related to a person’s financial behavior and build models with high levels of accuracy. However, the real question isn’t just how accurate a model can be, but what kind of decisions it’s helping to make.

Because a decision can be technically correct and still not be understandable to the person receiving it.

Technology has the ability to identify patterns, reduce processing times, and improve processes, but it doesn’t replace the responsibility to explain why a person received a particular result. That’s where many initiatives lose their value.

If someone receives a rejection due to “inconsistent transactions,” do they really understand what that means? Do they know what behavior influenced that decision? Do they have a clear understanding of what they can do to improve their situation and try again? Or did they simply receive a “no” that’s more sophisticated than before?

The difference between these scenarios determines whether technology is truly fostering inclusion or merely automating decisions.

How Can We Build Responsible Solutions?

When we design solutions based on alternative data, we learn that there are questions that must be answered at the start of the project — not at the end.

Can the decision be explained simply? Does it make sense to the person receiving it? What happens when someone asks why they were rejected? Is there useful information that will help them improve their chances in the future?

Answering these questions requires investing in elements that are often invisible but are essential for building trust:

Clear explainability of each criterion used. Teams equipped to communicate decisions in an understandable way. Financial education that helps people understand how to strengthen their profile. Support channels that make it easy to try again with clear and transparent information.

All of this requires time, investment, and commitment. However, it is precisely what distinguishes a system that is merely accurate from one that is also fair and accountable.

The Challenge Isn’t the Technology

We often think that the biggest challenge is identifying the best variables or finding new sources of information.

In reality, the challenge is much more human.

The right question isn’t, “What variables can I use?” but, “How can I explain each one in a way that a person can understand?”

A system where variables can be understood builds trust. A person who understands a decision — even when the outcome isn’t in their favor — is unlikely to feel excluded; they feel informed and know there’s a path to improvement.

That shift in perspective transforms the relationship between technology and people.

Why It Matters in 2026

Alternative data is already part of the evolution of financial services and will continue to gain prominence. The conversation is no longer about whether or not to use it. Today, the real discussion is how to use it in an ethical, transparent, and people-centered way.

The way institutions adopt these tools will determine whether they truly drive greater financial inclusion or simply refine traditional models without bringing about meaningful change.

The coming years will be decisive in setting that course in Mexico. Organizations that incorporate explainability, transparency, and communication from day one will build something more valuable than more accurate models: they will build trust.

Because alternative data, when used responsibly, fosters genuine inclusion.

In the end, behind every piece of data there is a story. Behind every variable, there is a person trying to get ahead. Technology can help us make better decisions, but it should never make us forget who it was created for. Because when we put people at the center, data ceases to be just information and becomes an opportunity.