Anti-fraud


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how artificial intelligence can help you detect frauds and financial crimes, speeding up legitimate transactions and optimizing your business.

The impact of the fraud is very profound. It can cause financial loss, result in legal fees and affect the reputation of the institution. The IBM solutions help customers take a more proactive approach to avoid fraudulent situations and financial losses.

Among the most common difficulties faced in fraud analysis and detection with traditional solutions, we can identify:

  • Delays in releasing requests from legitimate users, harming their experience and satisfaction;
  • High consumption of time to gather evidence from different sources;
  • Difficulties in managing the investigation process, making responses to frauds slower;
  • Failures in activities that result in major financial losses, liberating services and products for criminal activities, causing moral and material damages to third parties and generating costs with legal fees;
  • Losses, sometimes irreversible, to the Institution image.

What is the difference between a solution that uses artificial intelligence for traditional anti-fraud solutions?

Systems that use machine learning essentially attempt to confirm the credibility of operations and identities by crossing information from several different sources. They analyze the data provided by each segment to create and identify patterns and to detect the profiles that fall outside the rule. As fraud is confirmed or not, the software relearns and adjusts itself automatically in case of failure. This kind of solution can perceive the relations “hidden” between data, that is, that would not be identified by people or systems fed only by definitions created by humans.

Another great differential of antifraud systems with machine learning compared to traditional models is the greater assertiveness. When we put the machine to learn with its own evaluations, the refinement is much greater than when we simply stipulate generic rules. In addition, these solutions can catch more quickly the new techniques that the fraudsters are developing.

These fraudulent schemes are being conducted by individuals and sophisticated criminal organizations, who are technology pioneers and are constantly evolving their tactics. Consequently, the organizations have to base their anti-fraud operations on scalable and dynamic technologies and processes with sufficient intelligence and agility to handle the large volume of occurrences and to continually adapt to new patterns and suspicious activities.