The banking sector faces technological challenges that are no longer limited to the adoption of new tools. The digitalization of services, financial innovation, and the growing capabilities of criminal organizations require strengthening the protection of the integrity of the financial system.
The Superintendent of Banks, Milton Ayón Wong, stated that prevention must adapt to an environment that is changing rapidly.
To achieve this, he noted, institutions need to review their methods and anticipate the risks that arise with new technologies.
Technological transformation has expanded the use of artificial intelligence in tasks such as risk assessment, fraud detection, customer service, and regulatory compliance.
The challenge for banks is to use these tools quickly without losing the ability to explain, control, and validate the decisions they produce.
Ayón Wong stated that "reconfiguring prevention means continuously rethinking our approaches, strengthening our methodologies, and preparing ourselves to face scenarios that evolve rapidly."
The official emphasized that prevention does not depend solely on compliance areas. It also requires the participation of the authorities, boards of directors, senior management, audit, risk management, and the rest of the staff of the supervised institutions.
During a recent event, participants analyzed regulatory chang…
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A woman carries out a financial transaction and receives banknotes at the service counter of a bank branch in Panama. (Illustrative image Infobae)
The banking sector faces technological challenges that are no longer limited to the incorporation of new tools. The digitalization of services, financial innovation, and the growing capabilities of criminal organizations require strengthening the protection of the integrity of the financial system. The Superintendent of Banks, Milton Ayón Wong, stated that prevention must adapt to an environment that changes rapidly. To achieve this, he noted, institutions need to review their methods and anticipate the risks that arise with new technologies.
Technological transformation has expanded the use of artificial intelligence in tasks such as risk assessment, fraud detection, customer service, and regulatory compliance. The challenge for banks lies in using these tools quickly without losing the ability to explain, control, and validate the decisions they produce.
Prevention must adapt to an environment that changes rapidly, said the Superintendent of Banks, Milton Ayón Wong.
Ayón Wong maintained that "reconfiguring prevention involves continuously rethinking our approaches, strengthening our methodologies, and preparing ourselves to face scenarios that evolve rapidly."
The official emphasized that prevention does not depend solely on compliance areas. It also requires the participation of authorities, boards of directors, senior management, audit, risk management, and the rest of the staff of supervised institutions.
During a recent event, participants analyzed regulatory changes and trends related to money laundering and terrorism financing. The gathering also addressed the risks posed by new technologies and featured national and international speakers.
The expansion of automated systems creates an additional requirement for financial institutions. It is no longer enough to verify that a tool delivers results: banks must be able to demonstrate how it reached a conclusion, what data it used, and what oversight exists over its operation.
A digital scammer in a dark hoodie communicates by phone with a victim while posing as a bank advisor in front of multiple monitors. (Illustrative image Infobae)
A SAS study with contributions from IDC indicated that worldwide, banks are accelerating their use of artificial intelligence, although doubts persist about the reliability of these solutions. The report Data and AI Impact Report: The Trust Imperative established that only 11% of banks combine high trust in artificial intelligence with systems whose reliability can be demonstrated.
The distance between adopting a technology and backing up its results takes on a special dimension in the financial sector. An automated decision can affect access to credit, a fraud alert, a transaction, or the relationship between a person and their bank.
The international analysis also showed that 47% of banks are experiencing what IDC calls the "trust dilemma." This situation includes institutions that have reliable systems but have not yet fully leveraged them.
A man holds his head in front of a laptop whose screen displays a bank alert for identity theft. (Illustrative image Infobae)
Banking is among the industries that invest the most in artificial intelligence. Even so, the study noted that 23% of banks reach the highest level of the Trustworthy AI Index. The measurement reflects that technological adoption alone does not guarantee solid use of models. Institutions need mechanisms that allow them to review data, identify the controls applied, and monitor the response of each system.
This need gains strength as analytical tools intervene in higher-impact decisions. An institution must know under what criteria a model classified a transaction, detected unusual behavior, or defined a risk level.
The challenge also extends to processes related to fraud and security. Analytical capabilities make it possible to identify atypical movements and react more quickly to new threats.
"Banking has always operated on trust. What changes today is that this trust must also extend to the data, models, and artificial intelligence systems that support critical decisions. In credit, risk, fraud, compliance, or customer experience, it is not enough for AI to be fast: it must be explainable, governed, and traceable," said Ricardo Saponara, Leader of Risk, Fraud, and Compliance Advisory for Latin America at SAS.