misuse, tax evasion, money laundering, futures trading, fraud, and unauthorized currency exchange are just a part of the issues that frequently occur with bank cards. Now, Iran’s banking system stakeholders are determined to address some of these challenges by harnessing the capabilities of artificial intelligence.
According to IDEA, Amin Ali-Abdi, the head of the Risk Monitoring and Control Group and the Supervision Management of Kashef, addressed the topic of identifying patterns of unconventional behavior and suspicious transactions in payment cards during the InnoTech event. He stated, “Given that card-to-card transactions provide customers with the ability for immediate fund exchange, there is a greater potential for misuse compared to other instruments. We are currently in a situation where bank cards are leased, and some individuals misuse the banking system through rented cards.”
He emphasized that instances of misuse of card instruments are on the rise, and artificial intelligence and deep learning assist the country’s banking system in addressing this issue. “We currently have numerous regulations in this field, but fraud and deception are becoming increasingly complex, necessitating technologically advanced tools to identify such misuse,” he added.
(Legislation Differs from Precision or Legislation Differs from Linear Approach)
Abdi continued to discuss intelligent legislation within the banking system, adding that legislation is not merely about drawing lines; it should be approached as a curve that can be addressed with deep learning and machine learning techniques to achieve more flexible regulations.
According to him, tax evasion, money laundering, futures trading, and fraud are all part of these misuses, and by implementing a series of laws and providing data to artificial intelligence, these challenges can be mitigated.
What Is the Solution?
In the subsequent discussion, Abdi presented solutions to these challenges and explained: Initially, by categorizing bank cards based on transaction behavioral patterns and classifying businesses into authorized businesses, criminal enterprises, and regular individuals, we can take the initial step.
In the next stage, identifying entities with unconventional behavioral patterns compared to the patterns of other entities of the same kind, as well as compared to the historical behavioral pattern of the same entity, becomes crucial.
We can employ artificial intelligence to identify misuses. For example, when a bank employee’s transactions are filled with transactions in the billions and similar occurrences, these are data points that artificial intelligence can detect naturally.
Data Privacy:
Continuing, he noted the importance of data privacy in addressing challenges in this field and elaborated: Currently, data privacy is a serious concern that requires regulatory measures to be resolved. However, at present, we are in the process of completing data for artificial intelligence using data from the source card number, transaction type, date and time of the transaction, transaction amount, merchant terminal type, unique merchant terminal code, and destination card number.
No Comment! Be the first one.