How antifraud systems work

Antifraud systems are today something that no company associated with Internet commerce can do without

Antifraud system is a set of measures that allow you to assess banking or Internet transactions for the degree of fraud probability. To do this, the system tries on certain requirements for each transaction - and if it does not correspond to them, then it considers it more carefully and signals it.

Built-in triggers report the detection of unusual behavior and assess possible risks in the transaction, and then apply measures to complete or refuse the transaction. In situations where the anti-ford system is not able to independently determine the final decision, then this case is passed on to bank employees, who are called fraud analysts.

Today, anti-fraud systems consider many parameters for calculating suspicious transactions, such as:

  • amount of payment

  • IP-address of the device through which the payment is made

  • bank card token

  • user's digital fingerprint

  • history of transactions and transfers on a bank card

  • history of declined payments in the past

Rules and filters and machine learning technologies are applied to detect and prevent fraudulent activity.

Filters used by the anti-fraud system:

  • geographic filters

  • stop lists

  • validators

  • authorization limits

  • parameters matching filters

The number of filters depends on the degree of responsibility and the complexity of the company's field of activity.

Antifraud performs four main tasks: monitoring, detection, decision-making, intelligent learning. Key technologies and capabilities used to address these challenges:

  • Gap testing. Reveals the volume of components in serial data. Detects redundant or missing data.

  • Calculation of statistical parameters. An essential tool for detecting abnormalities and identifying suspicious transactions.

  • Text analytics. Divides information into categories, searches for it and recognizes the data.

  • Machine learning. Builds on previous data and generates transaction templates.

  • Network analytics. Detects patterns in transactions, conducts analysis to process future transactions faster.

  • Selfeducation. Allows you to detect fraud in cases that the system has not encountered before.

  • Confirmation of entry date. Analyzes the date and time of the transaction for suspicion.

Anti-fraud systems usually use payment systems such as MasterCard, Visa, banks, and online stores. Today, anti-fraud technologies can be found in other areas, for example, platforms for video games. This is done to protect in-game transactions.

Today, anti-fraud systems are a necessary tool in almost all IT areas related to online commerce. Despite the almost unlimited potential in the development of this technology, the presence of an anti-fraud analyst on the staff is still required. The system will not always be able to identify a fraudster without human assistance.

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