MoneyThumb has many customers who are online lenders that use our PDF financial file converter, PDF Insights, to make quicker and better-informed lending decisions. Many of those same online lenders are beginning to convert to AI, (Artificial Intelligence) to help secure the online payments that borrowers make to their loans.
In recent years, the world has seen a transformation of all industries to a digital world. For the financial sector, this transformation involves Artificial Intelligence. Though many people view AI as very difficult, AI concepts are fairly simple to understand. AI is basically just the ability of computers and machines to perform tasks and solve problems by replicating human behaviors of learning and decision making. The finance sector is one of the most invested industries in Artificial Intelligence and it is expected to see exponential growth in the coming years. Artificial Intelligence has many benefits to offer to the finance industry. But in this Rules of Thumb blog post, we will only be discussing how AI can ensure secure payments across financial transactions, for the benefit of our readers who are online lenders and are seeking a more secure way for borrowers to make online payments.
Securing Payments Intelligently
The traditional fraud-detection systems have become obsolete with significant advancement in payment technology. As payments are now real-time, they need real-time security management. But with the large number of transactions that take place every day, it is humanly not possible to detect fraud and transaction errors for each transaction. This is why online lenders are particularly interested in how artificial intelligence can be used to keep payment systems secure. AI can help online lenders monitor transaction data in real-time and eliminate or reduce the occurrence of payment frauds committed by professional cybercriminals. It can also help spot suspicious or illegal transactions.
Artificial Intelligence algorithms study and analyze data and use it to identify fraudulent transactions. It can help a system to learn from every single transaction, improve as it learns, and solves problems effectively. By automating the analysis of the behavior pattern of borrowers, online lenders can flag any fraudulent activity almost instantly.
Specifically, the ability of Artificial Intelligence to get insights based on trend analysis through machine learning, along with new knowledge obtained from unsupervised algorithms, is reducing the occurrence of payment fraud. By joining the two approaches together, AI can determine if a financial activity is fraudulent or not, and alert fraud analysts immediately.
Let us look at some reasons why Artificial Intelligence plays an important role in securing payments from fraud.
Payment Frauds are now more sophisticated and cannot be detected with rules-based systems anymore. They have different patterns or digital footprints, structure, and sequence, and are not detectable with predictive modeling and rules logic only. It might have been possible in early eCommerce days, but now AI is needed to confront complex payment fraud schemes.
AI provides real-time fraud prevention. Lenders with AI-based secure payments have an immediate advantage over those who don’t, since the fraudulent payments are detected almost instantly with real-time analysis of payments data. As AI companies compete with each other to provide faster solutions, the response rate for risk calculation is increasing.
Predictive Analytics of AI and Machine Learning combined can find discrepancies in large data sets within seconds. As a machine learning algorithm works more accurately with more data, it provides better predictive values. While ensuring secure payments, AI algorithms can distinguish fraudulent and legitimate transactions with greater accuracy.
Bottom Line With the advancement in technology and sophisticated cybercriminals, online lenders are now leveraging the use of Artificial Intelligence to ensure secure payments and improve customer experience. Though some small online lenders may not be able to move to advanced analytics and AI immediately, they can begin by analyzing existing data and building the expertise required to start as early as possible.