Get to know how fraud detection works in banking & how AI can play a significant role in reducing the same.
Fraud is a big problem for banks and financial institutions. Every year, billions of dollars are lost to fraudsters who find ways to exploit weaknesses in the system. That's why it's important to have strong fraud detection measures in place. There are various fraud detection methods used in banking, but some of the most common include suspicious activity reports, transaction monitoring, and data analytics.
Digital fraud is the banking sector's primary challenge, leading to immense losses every year. As per McAfee's reports, cyber fraud currently damages the economy by USD 600 billion of GDP on a global basis.
Fraud detection in banking describes the tools and processes that banks use to monitor transactions and payments for suspicious activity. When a transaction or pattern of behavior throws up a red flag, the bank’s fraud team can intervene.
Banks have to be vigilant in order to detect frauds in baking systems. There are various fraud detection methods that they use, but some of the most common include suspicious activity reports, transaction monitoring, and data analytics.
Suspicious Activity Reports (SARs) are one of the primary ways that banks detect fraud. If a bank employee suspects that fraud is taking place, they will file a SAR. The SAR will then be reviewed by the bank's fraud department. If the fraud department determines that there is enough evidence to suggest that fraud has taken place, they will take appropriate action.
Data analytics is also increasingly being used by banks to detect fraud. By analyzing large data sets, banks can look for patterns that might indicate fraud. For example, if a customer suddenly starts making a lot of small transactions that are all just below their daily limit, this could be a sign that they are trying to avoid triggering fraud detection measures.
Transaction monitoring is another fraud detection measure that is commonly used by banks. Under transaction monitoring, banks will flag any transactions that seem unusual or out of the ordinary. For example, if a customer who usually only spends $50 per day suddenly starts spending $5,000 per day, this would be considered an unusual transaction. The transaction would then be flagged and reviewed by the fraud department to determine if fraud has taken place.
There are several fraud trends that banks are watching out for. A few common ones include-
In the past decade, there has been a dramatic increase in mobile and digital fraud. This fraud can take many forms, from identity theft to credit card fraud. As a result, banks and other financial institutions have been forced to invest heavily in fraud detection and prevention. One of the most popular methods of fraud detection is to use machine learning algorithms. These algorithms are able to detect patterns of fraudulent behavior and flag questionable transactions. Another common method is to use two-factor authentication, which requires users to confirm their identity with a second factor, such as a PIN or fingerprint. By using these and other fraud prevention measures, banks and other financial institutions can protect themselves and their customers from fraudsters. Mobile and digital are one of the biggest fraud trends at the moment. As more and more people use mobile devices and online banking services, fraudsters are finding new ways to exploit these channels. One common type of mobile fraud is known as "smishing," where fraudsters send text messages that appear to be from a legitimate bank or financial institution. The message will usually contain a link that leads to a fake website, where the fraudster can then steal the victim's login credentials.
Credit card fraud is a serious problem that affects both cardholders and businesses. Fortunately, there are a number of measures that banks and businesses can take to detect and prevent fraud. For example, many banks now use fraud detection software to flag suspicious activity on customer accounts. This software looks for patterns that may indicate fraud, such as sudden changes in spending patterns or unusual charges in high-risk locations. Businesses can also take steps to prevent fraud, such as requiring employees to verify customer information before processing a transaction. By taking these measures, banks and businesses can help protect their customers from fraudsters and keep their own losses to a minimum.
ATMs are particularly vulnerable to fraud because they are often located in public places and are accessible 24 hours a day. As a result, fraudsters have a wide window of opportunity to steal cards and PIN numbers. Debit fraud is a major factor in the increase in overall ATM fraud as people typically access ATMs with their debit cards. In order to prevent fraud, banks and ATM operators can implement a number of security measures, such as encryption, two-factor authentication, and fraud detection software. By taking these measures, banks and ATM operators can help protect their customers from fraudsters and keep their own losses to a minimum.
Identity fraud occurs when someone uses another person's personal information, such as their name or Social Security number, to commit fraud. This type of fraud can be used to open new accounts, make purchases, or even file for tax refunds. Identity fraud is a serious problem that can have a lasting impact on the victim's finances and credit rating and banks today are taking steps to prevent identity fraud. For example, many now require customers to provide additional documentation, such as a driver's license or passport, when opening a new account. They are also using fraud detection software to flag suspicious activity, such as unusual account activity or attempts to open multiple accounts in a short period of time. By taking these measures, banks and other financial institutions can help protect their customers from identity fraud.
Banks monitor transactions and comb through transaction data to identify patterns of behavior or suspicious activity that might indicate fraud has taken place or is about to take place. Ideally, the bank’s fraud detection system will detect fraud before money can leave a customer’s account. That fraud detection system is what monitors transactions for any unauthorized activity or access to sensitive data. Transaction monitoring relies on specific tools, techniques and strategies for detecting fraud, which include:
We could think of banks’ fraud challenges as mainly falling under three categories:
Part of adding new customers, digital onboarding is risky for banks, because of regulations such as KYC (know your customer) and AML (anti money laundering). These are legal requirements to confirm user identities and ensure they will not commit financial crimes.Fraudsters use fake or synthetic IDs to fool the process and open bank accounts. Confirming IDs is expensive, with costs rising to $35.2 billion in 2020. It’s also especially difficult for neobanks and challenger banks, who need to acquire new customers fast with as little friction as possible.
Issuing banks should know when a suspicious transaction or withdrawal takes place. Spotting patterns is difficult because they have limited access to data points, only seeing the currency, amount, category, and name of the merchant. If they try to block fraudulent payments based on these parameters, they may create high rates of false positives, which are frustrating for good cardholders. There are also legal requirements such as Strong Customer Authentication (SCA), and ensuring the source of funds is legitimate.
Account takeovers (ATOs) happen when fraudsters acquire the login details of a legitimate user. They use the account as their own, which has terrible consequences for banks’ relationship with customers, and enables several other types of fraud and crime. This is why banks must do everything they can to protect their users’ accounts. The wider problem, of course, is that fraud is adaptive. That is to say, fraudsters will quickly notice when their actions are blocked, and try another tactic. Thus, solutions such as AML software and KYC tools have to be versatile as well as efficient.
While fraudsters are getting smarter with their techniques, they can be kept in check by following some fraud detection recommendations that have been listed below:
Charity, they say, begins at home. And so, if you must fight fraud effectively, start by screening and auditing your company’s employees. Some of your supposed “trusted” employees might be selling customers’ account details on the dark web. You should take this seriously, as Microsoft research shows that groups like LAPSUS$, a growing team of cybercriminals, are increasingly gaining access to target organizations through recruited employees in return for money. With research published on Clari5 indicating that 70% of banking fraud is successful because of insiders, it’s more obvious than ever that monitoring internal fraud should be a top priority.
Making customers aware of the risks they face, what to look out for, and safe transaction tips is a sure way to reduce fraud risks like Account Takeovers (ATOs). Even more so, this strategy makes your customers trust your bank more. For instance, banks or financial institutions can introduce an online campaign to warn customers about takeover attempts.
In certain contexts, transaction monitoring to prevent money laundering and terrorism financing is a requirement, and includes filing suspicious activity reports when something is amiss. However, keeping an eye on how customers use the website or app of a fintech or traditional institution can go a long way not just to avoid fines and be compliant but to detect and investigate potential cases of fraud.
By definition, AI or Artificial intelligence makes it possible for robots or machines to acquire knowledge from experience, fine-tune to fresh inputs and execute human-like tasks through automation. AI in the finance domain plays a vital role in the current scenario. The more financial data AI has to work with, the more in-depth analytics and insights the financial industry can get from their AI technology. Already, we are seeing the crucial role of Artificial Intelligence in the Banking sector that assists with fraud detection from a progressive viewpoint instead of waiting for frauds to occur and then act. Artificial Intelligence technology is highly result-oriented in detecting scams, with 63 percent of financial institutions conveying that AI is proficient in avoiding cyber fraud before it happens.
Fraud is a serious problem that affects banks, businesses, and consumers alike. Fortunately, there are a number of measures that can be taken to detect and prevent banking fraud. By using technologies such as machine learning algorithms, two-factor authentication, and fraud detection software, banks and businesses can help protect themselves and their customers from fraudsters.
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