Financial institutions are reluctant to use fraud detection systems.
According to the activists of this field, although the regulator has encouraged banks and payment networks to use online systems in the field of fraud detection, but since the platforms and frameworks necessary for this issue have not yet been determined, these systems are not used properly.
According to the Iran digital economy annotation, experts in this field believe that fraud detection systems work properly when banks and credit institutions share their data with each other, but as long as this data is not shared between banks, it will actually take longer for fraud detection systems to reach their results.
Fraud detection systems in banking are sophisticated tools that use various technologies and methodologies to identify and prevent fraudulent activities in real-time. These systems are increasingly important due to the rise of digital banking and online transactions, which have expanded the opportunities for fraudulent activities. Here’s how fraud detection systems typically work within the banking system:
1. Data Integration: The system collects data from various sources within the bank. This includes transaction data, account information, user behavior patterns, and more.
2. Real-time Monitoring: Transactions are monitored in real time. This helps to quickly identify suspicious activities that deviate from a customer’s usual behavior patterns.
3. Machine Learning Algorithms: Many modern fraud detection systems utilize machine learning algorithms that can learn from past instances of fraud to better identify similar patterns in the future.
4. Rule-based Systems: These systems use predefined rules set by the bank, which could be based on regulatory requirements or internal policies. Transactions that violate these rules are flagged for review.
5. Anomaly Detection: The system constantly looks for anomalies in transaction behavior. This can include unusually large transactions, rapid increases in transaction volume, or logging in from a new location.
6. Risk Scoring: Transactions and user behavior can be given a risk score. If the risk score crosses a certain threshold, the system may flag the activity as potentially fraudulent.
7. Alerts and Notifications: When suspicious activity is detected, alerts are generated. Depending on the system setup, this can lead to automatic blocking of transactions, freezing of accounts, or notifications sent to security personnel.
8. Case Management: The system will have a case management tool where fraud analysts can review and investigate alerts, decide on the action to be taken, and record the outcomes for improving future fraud detection.
9. Continuous Learning: Good systems adapt by learning from the outcomes of investigated alerts. False positives can be used to refine the system and reduce incorrect flags.
10. Customer Verification: Additional verification steps can be triggered when suspicious activity is detected, such as two-factor authentication or security questions.
11. Cross-Channel Analysis: Fraud detection systems increasingly work across various channels (ATM, online banking, mobile, etc.) to get a holistic view of customer activity, aiding in the detection of fraud that occurs across multiple platforms.
As fraud tactics evolve, so too do the technologies and strategies behind fraud detection. Banks are investing heavily in AI-powered systems, big data analytics, and biometric verification methods to improve the accuracy and efficiency of their fraud detection capabilities.
The fraud detection system is independent
Systems development requires labeled data, and obtaining data is not an easy task. On the other hand, the system should be able to receive different data and be able to analyze the data and provide low-error reports with all kinds of scenarios.
Masoud AliAkbarzadeh, the CEO of Dade kavan Houshmand Tusan, believed that financial and credit institutions, of which banks are a part, are an attractive platform for fraudsters in this field because fraud is inevitable due to the complexity of their systems.
Referring to the importance of this area, AliAkbarzadeh explained: the need to prevent these incidents is to be equipped with processes that block access to fraud by producing optimal and analytical reports. Considering the high speed of electronification of banking products and processes as well as encouraging people to use it, the need to use fraud detection systems for the financial industry and especially banking is already evident.
According to the CEO of Dade Kavan Houshmand Tusan, due to the fact that the fraud detection system is of a security type and this field is never 100% certain, complete prevention of fraud and violations is a long wait.
Emphasizing the use of artificial intelligence technology in this field, AliAkbarzadeh said that it seems that the fraud detection system has been developed and with intelligence and the use of data, it can find the points of violation more accurately. The introduction of artificial intelligence-based technologies also significantly helps in optimizing system processes.
For example, if the cases that indicate the occurrence of fraud and violations are referred to companies like us that are active in the field of fraud detection, so that through these reports, an intelligent model can be obtained and used to prevent similar incidents in other institutions.
He said about the main difference between online and offline fraud detection that the online fraud detection system, unlike offline systems that reveal the news of fraud after some time, issue a warning in the moment and prevent the fraud from happening at the same moment.
According to AliAkbarzadeh, recently the regulator of the bank and the payment network has encouraged the use of online systems in the field of fraud detection, but since the necessary platforms and frameworks for this issue have not yet been prepared, as a result, the above system does not have a clear status.
Regarding the challenges in this area, he said that the lack of communication between banks and other financial and credit institutions is the most important. In fact, there is no interest in sharing their cheats.
Also, not creating security and accountability of banks against phishing and fraud on their users’ accounts is another shortcoming that diminishes the use of the tools of this system. It is thought that if the responsibility and risk is on the side of the bank, the conditions will be adjusted.
Another thing that AliAkbarzadeh mentioned as a challenge was the reluctance of financial institutions to use the fraud detection system. It seems that financial institutions by themselves do not want to use the fraud detection system and are forced to use it only because of the regulatory presence and the requirement to comply with the rules and regulations. According to him, the importance of detecting fraud will remain in the shadows until economic institutions and the banking industry change their views on this issue.
AliAkbarzadeh believed that the importance of fraud and violation detection systems on the financial industry is clear, and failure to change the intellectual paradigm of business owners in not using the systems in question correctly can cause a lot of damage in the age of intelligence and data.
Transparency makes it easy for users to use electronic tools
Ali Zare, the owner of Datin’s fraud detection solutions, said about the reasons why users don’t want to use Internet banks: Seeing the issue of financial crimes online causes some people to use mobile and Internet bank accounts less. In such a situation, there should be an online fraud detection system so that by injecting transparency, the users will feel comfortable in using those tools. Due to the high volume of transactions, such security cannot be created without online systems.
Fraud is of two types; One case is caused by people’s mistakes. For example, a person makes a card-to-card transaction through the Instagram page or converts money into cryptocurrency and his money is lost; According to Zare, in this situation, it is not possible to control the situation, but it is possible to increase the educational activities for users.
The next type of fraud is systematic violations. Zare said that good things have started and are developing in this area, in such a way that wherever financial institutions like banks were the basis of work, we were able to give a good answer. For example, we identified gambling transactions with an accuracy of over 98% and stopped the transaction. Also, we identify business accounts with better algorithms than the declaration procedure, and we can respond to the needs of the ecosystem.
The cost of fraud detection research and development is huge
The owner of Datin’s fraud detection solutions, referring to the huge cost of fraud detection, said: “The challenges in this field are diverse; Behind some cheat streams is a huge research, development and investment process. This means that we face new scenarios every day and we must always look for new solutions and scenarios. On the other hand, identifying new scenarios is not an easy task.
It is said that the financial conditions, inflation and the economic situation have increased the desire of people to do some work that is considered a violation, and on the other hand, equipping hardware has become a difficult task. In fact, collections are forced to spend huge funds for this area.
Also, one of the main problems in all areas is the lack of human capital, because the wave of immigration that has happened makes it difficult to get human capital and advice.
According to Zare, the field of fraud detection is an exclusive field and unlike other fields, it is not easy to find up-to-date articles. Also, institutions are not very willing to give information to each other. This has made it difficult to exchange information.
On the other hand, there is also a legal challenge, because the process of criminalization in the country is slow, and for this reason, it will take some time for this process to happen.
Banks need smart infrastructure
Pointing to the importance of equipping banks with this system, Datin’s product manager explained: Banks are welcoming and concerned about credit due to their limitations, so they proceed with this issue consciously.
Also, the issue of the credit of banking and tax institutions is involved, and no one wants this to happen to them. Financial-credit institutions like to spend money in this area to protect their reputation and not endanger their customers; For example, medium-sized banks have more than 6 million card transactions, so they need such significant and intelligent infrastructure to create security.
According to Zare, the fraud detection system is an independent system, so a person can put it in the way of switching or carbon banking, or use it in related businesses such as insurance or tax.
According to Iran digital economy annotation research, the amount of money a bank should spend on smart infrastructure is not a one-size-fits-all answer and can vary widely based on several factors:
1. Bank Size: Larger banks with more assets, customers, and transactions likely need to invest more in smart infrastructure than smaller banks.
2. Transaction Volume: Higher volumes of transactions generally require more robust systems to handle the data, requiring a larger investment.
3. Risk Profile: Banks with a higher risk profile, perhaps due to their customer base or the nature of their transactions, may need to invest more in advanced security measures.
4. Regulatory Requirements: Compliance with local and international banking regulations can impose certain technological standards that require investment.
5. Digital Transformation Goals: Banks that aim to transform their customer experience through digitization will need to invest more in smart infrastructure.
6. Current State of IT Systems: Banks with outdated systems may need to spend significantly to upgrade their legacy systems before implementing newer smart technologies.
7. Cost-Benefit Analysis: Banks should conduct a thorough cost-benefit analysis. The cost of smart infrastructure should be justified by the return on investment, in terms of enhanced security, cost savings, customer satisfaction, and revenue growth.
8. Market Competition: Depending on the competitive landscape, a bank might need to invest more in smart infrastructure to maintain market share and customer loyalty.
9. Innovative Solutions: Investment in innovative technologies can be expensive upfront but can provide significant cost savings and revenue opportunities in the future.
Generally, smart infrastructure spending should be balanced with expected benefits. Banks typically allocate a certain percentage of their annual budget to IT spending, which can range from 7% to 15% depending on the bank’s strategy and needs. According to some industry benchmarks, banks spend on average about 10% of their annual revenue on IT.
Before committing to any specific number, it’s critical for a bank to consult with experts, analyze their specific needs, and align their investments with their strategic objectives and capacity for change management. This way, they can ensure that any investment in smart infrastructure brings about the desired results in efficiency, customer service, and risk management.
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