Telecommunication network fraud has become a widespread and extremely harmful criminal behavior. Among them, bank cards and phone cards are the most commonly used tools by fraudsters. These cards are not only used for online and offline fraud activities, but also rented or purchased by criminals through various means. The national public security organs have launched a large-scale crackdown, and continued to carry out the "card-cutting" operation, severely cracking down on the behavior of renting and selling "two cards".
The behavior of illegal renting and selling is not a simple phenomenon. Behind it, it directly leads to the production of a large number of bank cards and phone cards that are "real-name but not real-person". What is more serious is that many unsuspecting individuals not only sacrifice their own bank cards for sale, but also suffer legal punishment or credit sanctions as a result.
Bank Cards: What are rented or sold bank cards used for?
The criminals who get the rented or sold bank cards are likely to use them for fraud, money laundering, tax evasion, opening fake stock accounts and other illegal activities. These will eventually be traced back to the card owner, resulting in personal credit damage, or even legal liability.
Used for fraud. Four years ago, Mr. Liu applied for an Industrial and Commercial Bank card, which was not used frequently after several bank system upgrades and card replacements, and was put aside. Through a neighbor's introduction, Mr. Liu joined a WeChat group called "Xiao Wang Opens Cards", and through the group's connections, the bank card soon found a buyer. It was then used by others to commit online fraud. After the crime, Mr. Liu was criminally detained by the public security organs for allegedly assisting in information network criminal activities.
Used for money laundering by gangs. Short of money, Xiao Li rented out his "full set" of identity card, bank card, online banking U shield, and phone card to make some quick money. The criminals opened mobile banking for the bank card and used it for money laundering. The victim transferred the money to the account designated by the scammer, which was Xiao Zhao's bank card, and then it was quickly divided into multiple small amounts and transferred to several bank cards, and then the gang members distributed across the country took away the stolen money. A few months later, the police found Xiao Li and he learned that his bank card was involved in multiple online fraud cases. What awaited Xiao Li was legal punishment.
Used to evade taxes. Xiao Zhou heard that bank cards could also be sold for money, so he sold his idle bank card. After buying Xiao Zhou's bank card, the other party used it to evade taxes. Money in various names such as "salary" and "service fee" was deposited into the bank card, and then quickly withdrawn, thus achieving the purpose of tax evasion by the criminals. And Xiao Zhou had to report his taxes to the tax bureau himself because his "personal annual income" reached a "certain standard".
Law: What are the penalties for users who rent or sell bank cards?
Credit punishment. The People's Bank of China will transfer the relevant information to the financial credit basic database, and the illegal records will affect the loan and credit card applications of the relevant personnel for a certain period of time in the personal credit report.
Business restriction. Non-counter business of related units and individuals' bank accounts and all business of payment accounts are suspended for 5 years. That is to say, the relevant units and individuals cannot use bank cards to deposit and withdraw money at ATMs, cannot use online banking and mobile banking to transfer money, cannot swipe cards for shopping, cannot use quick payment through shopping websites, cannot register Alipay accounts, and cannot use Alipay, WeChat to send and receive red envelopes, and scan code payment.
Account restriction. Banks and payment institutions shall not open new accounts for related units and individuals within 5 years. If they apply for opening an account after the punishment period expires, banks and payment institutions will increase their review efforts.
In addition to the above punishments, they may also be suspected of crimes such as assisting information network criminal activities, obstructing credit card management, buying and selling state organ certificates, concealing or concealing criminal proceeds, and even fraud, which will bring imprisonment to individuals.
Article 31, paragraph 1 of the Anti-Telecommunication Network Fraud Law stipulates: No unit or individual shall illegally buy, sell, rent, lend telephone cards, Internet of Things cards, telecommunication lines, SMS ports, bank accounts, payment accounts, Internet accounts, etc., or provide real-name verification assistance; nor shall they impersonate others or fabricate agency relationships to open the above cards, accounts, accounts, etc.
Article 28, paragraph 3 of the Measures for the Administration of Bank Card Business stipulates: Bank cards and their accounts shall only be used by the cardholder approved by the issuing bank, and shall not be rented or lent.
Fraud Prevention: How to accurately identify bank card rental and sale behavior?
First, strengthen customer identity verification and authorization management. By adopting multi-factor authentication, advanced authentication technology and other measures, improve the security of accounts, increase the reliability of identity verification, and prevent accounts from being stolen or abused by criminals. At the same time, update customer information regularly, ensure the accuracy of information, and establish a complete customer profile, ensuring that only legitimate customers can access and use accounts.
Second, effectively identify abnormal account behavior. Based on Dingxiang Defense Cloud and Dingxiang Dinsight, through big data matching and tracking, conduct multi-dimensional and in-depth analysis, accurately identify abnormal operations, and discover abnormal behaviors of renting and selling.
Dingxiang Defense Cloud Business Security Intelligence Center experts analyzed that bank cards that are rented or sold mainly have the following risk characteristics:
Account opening anomaly: large-scale remote account opening, concentrated account opening in a short time.
Device anomaly: in a short time or sensitive time, obvious registration & login operations on the device, and multiple accounts login on a single device.
Transaction anomaly: batch occurrence of concentrated multiple transfers, multiple large transfers, multiple cross-bank transfers to non-same-name accounts, transaction account geographic locations are the same, can be analyzed from the frequency of behavior.
Financial institutions need to formulate and implement monitoring rules based on the risk control system, pay attention to specific types of transaction behavior, such as large transactions, frequent fund transfers, etc. This system can effectively monitor the characteristics of renting and lending bank cards, such as a large number of remote account openings, concentrated account openings in a short time, etc. When an account or transaction reaches the set abnormal threshold, the risk control system can issue an alarm in time.
In addition, mine hidden renting and selling behaviors. In order to evade the review and anti-fraud mechanism of financial institutions, criminals will use various technical means to increase the difficulty of identifying abnormal behaviors. In order to mine the potential risks of renting and selling bank cards, Dingxiang Xintell intelligent model platform can be used to mine hidden and complex renting and lending behaviors.
By collecting a large number of normal transaction sample data and using supervised learning algorithms for training, a model is established to learn the characteristics of normal transactions. Classification algorithms in supervised learning methods, such as support vector machines, can be used to train models, learn normal transaction patterns, and judge whether new transactions are abnormal. Combined with rule engine, it can real-time warn obvious abnormal transactions, while machine learning model tends to detect hidden abnormal patterns.
The model can give the probability of abnormality for each transaction based on the actual new transactions. For transactions that are predicted to have a high probability of abnormality, manual review can be conducted to determine whether they are fraudulent transactions. Then feedback the manually confirmed fraudulent transaction samples to the model and continuously let the model learn and optimize on new samples. In addition regular use of new data to retrain the model can make it better detect new fraudulent transaction patterns. In short by using machine learning and data analysis techniques identify and analyze transactions that do not match normal behavior patterns thereby discovering hidden hidden renting and lending abnormal behaviors.
In addition to the above-mentioned measures regular internal and external compliance reviews are essential to ensure that banking business complies with laws and regulatory requirements. This includes conducting in-depth investigations into possible problems and establishing a compliance review system. By adopting anti-fraud system monitoring and artificial intelligence technology screening combined with manual review it can effectively improve fraud detection capabilities reduce compliance and risk management costs for banks.
Through a series of means banks can better comply with relevant laws and regulatory requirements improve fraud detection capabilities reduce the impact of fraud on banks and customers protect fund security enhance customer experience.
Dingxiang has provided a series of professional anti-fraud services for more than 100 important financial institutions such as Bank of China Bank of Communications China UnionPay Minsheng Bank Hua Xia Bank Yongfeng Bank Jih Sun Bank Starlight Bank Wing Lung Bank Far East Bank Yuan Da Bank Kaohsiung Bank etc. Enhance the risk control capabilities of financial institutions improve customer satisfaction and promote the smooth progress of digital transformation.