Now, it is also making its way into the field of personal financewhere its influence can profoundly transform the way people plan, save and invest their money.
According to the “Money and Machine” report by the Oliver Wyman Forum, prepared in 16 countries, including Spain, a 86% of users are willing to use artificial intelligence solutions to manage their money, and 42% already do it regularly.
A tool that learns from financial behavior
The main advantage of this technology is its ability to analyze financial patterns and behaviors with a precision impossible for a person. Through machine learning, systems can recognize how people spend, when they save, or when more unnecessary expenses accumulate.
In this way, they offer personalized recommendations that help plan realistic budgets or detect areas for improvement. Digital banks and the most advanced financial applications are already integrating this capability to create automated savings planscapable of adjusting the objectives to the habits and income level of each user.
The interesting thing is that artificial intelligence not only interprets data, but also learn from user behavior and evolves with it. If revenue or priorities change, recommendations are updated automatically, something that previously required manual reviews and a lot of time.
Democratization of investment
Just a decade ago, investing was an activity reserved for those who had financial knowledge or could afford specialized advice. Today, the smart assistants and predictive algorithms allow anyone to access relevant information and better understand how markets work.
These systems collect millions of data from public and private sources, process them and transform them into understandable and useful information. The result is that users can understand market trends, simulate scenarios and make more informed decisions.
The democratization of investment It is, therefore, a direct consequence of the advance of artificial intelligence. However, experts insist that human supervision remains essential. The so-called “hallucinations”—errors generated by the models when interpreting information—can lead to wrong decisions if the results are not contrasted.
For this reason, entities such as N26 or BBVA recommend using these tools as support and not as a substitute for personal reflection or professional advice.
Automated budgeting and savings
Automation is another of the pillars of this transformation. Programs based on artificial intelligence can organize income, classify expenses and generate forecasts savings without the user having to intervene.
This represents a leap from traditional control methods with spreadsheets. Instead of entering data manually, the system learns from banking history and recent transactions to suggest adjustments in real time.
In this way, technology acts as a personal financial assistantwhich not only remembers the established goals, but also detects deviations and proposes corrective measures. The result is more precise, flexible management adapted to the circumstances of each person.
Smart comparators and faster decisions
Another practical application is in smart comparators. Artificial intelligence can analyze thousands of financial products – accounts, cards, loans or investment funds – in seconds and show which ones are most suitable for each profile.
This saves time and avoids mistakes when choosing banking services. The algorithms filter the information based on criteria such as profitability, commissions or risk level, and highlight the most advantageous options according to the user’s needs.
Furthermore, these platforms integrate elements of predictive analysisallowing them to anticipate changes in the market or detect opportunities before they become apparent to the average consumer. This speed of response can make a difference in making financial decisions.
Privacy and trust as great challenges
Despite its benefits, the adoption of artificial intelligence in the financial field poses challenges. He processing of personal data and the privacy protection These are the aspects that most concern users. Banks and fintechs must ensure that algorithms operate transparently and that recommendations are based on verified data.
European regulation advances in this sense, establishing rules that oblige entities to Test and audit your algorithmic models to avoid bias or errors. As the technology matures, consumer confidence also increases, allowing for more widespread and responsible use.
Artificial intelligence applied to finance represents a unique opportunity for improve financial education, optimize decision making and increase the economic security of users. By automating repetitive tasks and providing accurate analysis, you free up time and provide clarity about each person’s real situation.