Due to digitalization and increased shift in online banking, Fintech companies and banks are facing various challenges in providing secure customer experiences. Moreover, we have seen a massive increase in online fraud attempts in the last few years. Therefore, fraud detection and prevention is the top priority of banks and Fintech companies. But the good news is AI is helping financial institutions to detect and prevent fraud.
So, if you want to know how AI is transforming fraud detection and prevention in Fintech and banking, stick around with us till the end.
What’s Fraud Detection, and Why Is It Important in Fintech and Banking?
It’s a process of detecting fraudulent activities like scams. These frauds can cause both image and financial losses. Therefore, it’s essential for banks and Fintech companies to detect and prevent them. Fraud detection methods can be different in different industries. For example, some industries solely rely on manual verifications. This type of verification is expensive and time-consuming.
But due to digitalization, the use of manual verification is decreased, especially in the banking sector. Now business owners can use AI-powered tools to detect fraud automatically. No doubt, scammers and fraudsters use complex and sophisticated methods, but at the same time, AI and Machine Learning can help counter these frauds.
So, without wasting any time, let’s find out ways AI can help in banking and Fintech for fraud detection and prevention.
5 Ways AI Is Helping Baking and Fintech in Fraud Detection and Prevention
AI benefits banking and Fintech companies in many ways, but here are the 5 most common use cases of AI in banking.
- Machine Learning Models Can Help Detect Suspicious Transactions
Cybercriminals use various ways to steal bank or credit card details and then use them to make fraudulent transactions from the victim’s account. So, if banks don’t spot such transactions on time, it will be impossible to recover money from fraudsters. Therefore, banks now use ML models to detect and prevent suspicious transactions immediately.
- Detecting Anomalous Transactions
These transactions are different from regular ones, but still, they go unnoticed by bank staff. These transactions are linked to money laundering. But ML models can help detect such transactions and inform users through OTP so that users can confirm or deny the transaction.
- AI Can Help Predict the Possibility of Fraud
AI and ML algorithms provide access to advanced analytics so banks and Fintech companies can use them to predict fraud possibilities and prevent them from occurring. Moreover, when they detect fraud, they take immediate action. These actions can be done manually or automated.
- Fraud Detection Systems Provide Incomparable Security
Frauds can cause massive financial losses to banks. But using AI can help detect fraud and prevent them from occurring in the future. Moreover, banks can identify illegitimate customers. With AI, banks can get the big picture when they evaluate documents and applications.
- Know Your Customer (KYC)
AI-Powered tools can help banks and Fintech companies to KYC better. They can help them verify fingerprints, IDs, and documents and recognize faces immediately. As a result, banks can maintain the balance between customer security and convenience.
Final Words
Nowadays, customers want their banks to grant them access to their accounts and transactions online. Meanwhile, they expect banks to provide them with a secure environment for completing their transactions. So, banks need to use smart tools like IDefy to detect and prevent fraud in a timely manner.
IDefy is an AI-Powered tool that allows banks and Fintech companies to recognize a face, to verify ID and documents in real time. In this blog post, we have covered some ways AI is transforming fraud detection and fraud prevention. So, if you have a Fintech Company or work in the banking sector, you don’t need to look further because innovative tools are always available for help. Start using them today and prevent your organization from financial and reputation losses.