Using AI for fraud prevention

The use and development of technology has led to increased opportunity for digital theft and fraud. Undoubtedly, Artificial Intelligence (AI) has provided new ways to monitor these risks, facilitating processes and offering more security through routine checks and controls. 

A global survey by the Association of Certified Fraud Examiners (ACFE) and the SAS Institute found that 13% of organizations currently use AI and machine learning (ML) to prevent fraud. 25% are planning to incorporate said technologies in the next two years. 

Experts predict that the use of AI and ML will triple in the next two years. Similarly, more than half of the companies surveyed are considering increasing their technology budget to prevent digital crime, and it’s estimated that three out of four companies will use anomaly detection and reporting of exceptions by 2021. 

AI in the fight against digital crime and fraud

Among the many uses for AI in the fight against digital crime is device and browser analysis. These searches make it possible to detect behavioral patterns that indicate “non-human” behavior. This technique allows for the detection of bots made to perform tasks that may be harmful (overwhelming requests, unrestricted opening of accounts, etc.). Bots usually visit the same group of websites at the same hours, a behavior that is identified as invalid traffic by the systems in place. 

The use of AI allows for the analysis of up to 10,000 million impressions in the same day. Using models of machine learning facilitates the detection of digital fraud, and at the same time can detect new types of fraud that are being developed. Companies like Amazon and Uber are currently working on huge innovations supported by big data. 

On the other hand, artificial intelligence also opens a new opportunity for the digital marketing sector. Its utilization makes it possible to profit from investments in digital companies and, at the same time, detect scams on the web to secure the reputation of businesses online. 


There are many examples of using AI to detect crime. Currently, it’s possible to identify simple thefts as well as other more serious offenses. Many banking systems use AI technology to detect fraud or money laundering. Digital companies benefit from computer-aided learning to stop the publication of prohibited content (violence, pornography, etc.). The continual increase of information along with the increasing demands on authorities, combined with the protection and administration of said data, leaves no other option. AI stands out as the quickest and most secure way to follow the rhythms of the most sophisticated cyber-criminals. 

Social media currently identifies and almost immediately eliminates all content that alludes to pre-determined prohibited behaviors (terrorism, discrimination, fake news, etc.). Tools that use AI are the best way to review the most information possible. It is quite possible that over time these tools will no longer be optional, but rather indisputable requirements for the effective operation of large companies

A perfect example of the use of AI in fraud detection is how Visa was able to detect fraud that totaled 25,000 million dollars. Over 12 months (leading up to April 2019), the company analyzed 127,000 million transactions (one per millisecond) between businesses and financial institutions. Without AI, this level of analysis would not have been humanly possible. 

There is no doubt that digital fraud and crime will continue to present significant challenges for businesses and companies. Those who are able will protect themselves as well as their clients, leading to a solid business reputation.