In the era of the Digital revolution, financial systems and technology go hand-in-hand as they share a common characteristic. The structure of financial management is radically changing as digital platforms serve tens and hundreds of millions of users. Digitalization of money is nothing new, as bank accounts and payments made with their assistance already exist electronically. Due to consumers’ demand for frictionless transactions, real-time access to credit cards, and mobile wallets, has increased. The sheer number of transactions and sophisticated cybercriminal tactics has led many financial institutions to turn to artificial intelligence to combat fraudulent practices.
Artificial intelligence comes into play here. Financial firms use artificial intelligence to improve the security of their online finance systems, identify loopholes, and minimize risks. Through AI and machine learning, fraudulent activities can be easily identified and banks and customers can be alerted. From identity theft to malware, and phishing emails to fictitious accounts, fraud tactics are diverse. Cybercriminals attack weak links in financial systems and frameworks by infiltrating weak links between buyers, sellers, service providers, and banks. Distributed networks, big data, and the dark web have been used to detect vulnerabilities in cyber attacks. As part of our blog series, we will explore how artificial intelligence can help prevent fraudulent practices.
The AI Approach Towards Detecting Fraud
Artificial intelligence (AI) can help organizations recognize fraudulent behavior by reacting in real-time and learning patterns quickly. Leveraging the power of AI to distinguish fraud activities, organizations have been able to improve internal security and safeguard corporate transactions in a variety of ways.
- It stops high-velocity attacks from bots and malicious login attempts — Fraudsters use highly sophisticated mass bot attacks to access sensitive information and stored value. High-velocity attacks can be detected and stemmed by tools with bot prevention capabilities. Real-time fraud detection helps determine abnormal activity when a fraudster is testing credit card details to see if they are valid.
- Prediction of future outcomes and trends: — Using AI, banks can predict future outcomes and trends by analyzing past behaviors. AI-based systems can identify patterns in data that may indicate fraudulent activity, and they can also monitor activity in real-time to identify and block suspicious activity before it occurs.
- Better customer assistance — Automating the process of detecting and analyzing financial crimes help banks respond to customers more quickly by reducing wait time. AI could also enhance the customer experience, by reducing false positives during fraud detection.
- Reduced manual review time — Using automated digital fraud detection algorithms and systems, businesses don’t have to rely on manual reviews to determine if an order is valid or fraudulent. With a fraud detection solution transactions can be automatically approved or declined based on customized policies, drastically reducing the time and cost associated with manual reviews.
A Glance at Fraud detection using AI in financial firms
Traditional paper-based institutions requiring in-person transactions have evolved into Automated Teller Machines (ATMs) and online and mobile banking. Banks and other financial institutions are facing new challenges when it comes to creating safe and secure customer experiences as a result of this online shift in the industry.
Furthermore, 64% of financial institutions believe AI can prevent fraud before it occurs. Leveraging AI to detect financial crimes has improved internal security and streamlined banking processes by enhancing internal security. Here are some of the leading ways financial firms are using AI to tackle with fraudulent activities:
- Building purchase profiles — To detect fraud accurately, financial institutions must first understand typical customer behavior. By analyzing data from past monetary and non-financial transactions, banks can create and slot customers into different profiles using machine learning. Accounts can be categorized into hundreds of different profiles based on their activity, with the profiles being updated in real-time after each transaction. During transactions, AI determines whether they deviate enough from the norm to warrant being flagged.
- Developing fraud scores — The financial institution can assign a fraud score to every transaction by analyzing information about past legitimate transactions, fraud incidents, and risk parameters. Based on variables such as transaction amount, time, frequency of card use, IP address of purchase, and others, the fraud risk associated with that particular transaction is calculated. Fraud scores are used to approve transactions automatically, flag them for review, or reject them altogether.
- Fraud Investigation — A machine learning algorithm is capable of analyzing hundreds of thousands of transactions per second. With neural networks, this capability is taken a step further by making real-time decisions. These technologies successfully reduce the number of flagged transactions to a manageable number and provide a concise list of those requiring further investigation. The investigation and prosecution of fraud claims can be extremely time-consuming, so ensuring agents have the right tools to increase efficiency is essential. The use of augmented intelligence can help teams prioritize and streamline their investigations.
- Know Your Customer — Artificial intelligence-based KYC measures can verify IDs and documentation, match fingerprints, and even recognize faces almost instantly. It strikes the right balance between customer convenience and security.
Bringing It All Together
In a fast-paced financial environment, AI plays an increasingly vital role in fraud detection because it facilitates the processing of data faster, learns continuously from new transactions, and reduces false positives. Several companies are turning to AI technology, including Master Card, which recently announced its AI security platform. Although certain challenges and high demand for seamless and speedy transactions still exist, AI will play a significant role in preventing fraud in the future.