Why Credit Card Companies Must Deploy AI for Fraud Prevention?
As per Shift processing, “ The most common identity theft type is credit card fraud and sumps up to 41.8%.”
Banks and financial institutions are deploying technologies like Artificial Intelligence (AI) and Machine Learning (ML) to detect any fraud in credit card usage. AI & ML works on an algorithm that recognizes the spending and transactions of individual users. If things go out of the ordinary then AI flags an alert and credit card stops working. The user can only get the card running back by calling and verifying the transaction. Thus, it is safe to say that AI & ML collectively educate the machine with pre-recorded data and trains them in identifying patterns, anomalies, and user behavior.
How Integrated Artificial Intelligence Models Prevents Fraud?
As per FTC, “There were 143,992 fraud reports during COVID 19 pandemic out of which 5100 were related to a credit card.”
The next-gen fraud detection technique involves supervised and unsupervised AI models.
Under the supervised model, transactions are tagged as fraud and non-fraud to train the machines. The model goes through a massive amount of tagged transactions to identify behavior and patterns. This builds an accurate model.
Under the unsupervised model, there is more self-learning involved. The model detects or surfaces the patterns, which are not visible in other kinds of analytics. There is no tagged data or transactions fed to the model. The AI detects anomalies or outlier transactions based on the previous self-learning.
The anomaly detection system in place prevents fraud from accessing a user’s credit card profile. Integrated AI processes the enormous Big Data and provides a competitive edge to the financial institutions. The customers may feel annoying when the card stops working but for credit card companies it’s a blessing who otherwise would have been in an uncomfortable situation where the hackers would have drained the user’s account completely.
Role Of Behavior Analytics In Fraud Prevention
Behavior analytics uses Integrated AI to record and analyze behavior even at the smallest level. The behavior is with respect to the user, its account, devices used for transactions, etc. The user profile is updated in real-time whenever a transaction is carried out and AI uses it to predict future behavior. The profile may include monetary (spending velocity, days & hours of transactions, geography, etc.) and non-monetary (address change, password reset, etc.) transactions. Thus, behavior analytics is a key component to consider when credit card companies execute fraud prevention strategies. Also, it is crucial in avoiding a false positive, which may unnecessarily block the user’s card and prevent them from making a transaction.
With high emphasis by the government for people to adopt online, digital transactions are increasing every day including payments through credit cards. The companies that offer these services and other financial institutions have no other option but to rely on big data and technologies like Artificial Intelligence to prevent fraud from happening. For more information on the above solutions contact our experts today.