Financial Services

Understanding AI Fraud Detection and Prevention Strategies

As businesses worldwide embrace digital technologies, their vulnerability to financial fraud increases. Data reveals that in 2024, 25% of financial organisations experienced USD 1 million in fraud losses and consumers reported more than USD 10 billion in cumulative financial losses. These numbers are a cause for concern and this is the reason that businesses have ramped up their investment in fraud detection and prevention. The Fraud Detection and Prevention market size which stood at $ 28.8 billion in 2024 is expected to reach a staggering $ 63.2 billion by 2029 at a CAGR of 17%.

Several factors have made people and organisations vulnerable to financial fraud

• As transactions move online, fraudsters can easily target users' online credentials. Consequently, data theft has become one of the fastest-growing financial crimes today.
• Fraudsters target end users and organisations through malware. Malware is being used to extract digital identities and commit fraudulent activities.
• Another factor contributing to the increase in online fraud is that most internet users use a small set of usernames and passwords to secure multiple accounts. This increases the risk that fraudsters can steal data from one source and use it to hack other accounts.
• People today interact through multiple channels with businesses, manage accounts and make transactions. Hence, each channel is vulnerable to fraud.
• Customers desire a seamless journey and are discouraged from transacting with businesses that have onerous visible security procedures. Therefore, many companies in their bid to offer a great customer experience,  may not follow the required steps for secure transactions. This makes customer data vulnerable to cybercrime.

Payment fraud is one of the most common online frauds that is committed by fraudsters. In payment fraud, false or stolen payment information is used to obtain money or goods. This information is stolen through different types of online fraud.

Types of online fraud

Phishing: Refers to the use of email and online messaging service to extract personal data, financial details and login credentials.

Data breach: Stealing confidential or protected data from users or organisations and moving it into insecure environments.

Denial of Service (DoS): This is when the access of traffic to an online service, system or network is interrupted with a malicious intent.

Malware:This is a type of fraud where the users’ devices are damaged by malicious software to access personal or sensitive information.

Ransomware: Ransomware is malware that prevents users from accessing critical data and demanding payment to restore access.

The surge in online fraud alongside the increasing complexity of fraud has driven organisations to turn to technology for fraud detection and prevention. Artificial Intelligence (AI) has emerged as the leading technology for developing fraud detection and prevention strategies.

AI in fraud detection and prevention

Machine Learning (ML) algorithms are trained to identify patterns and anomalies that indicate fraudulent transactions. Algorithms establish a baseline for typical user behaviour and transaction patterns. This data is continuously monitored to detect anomalies and patterns that deviate from this standard. If any abnormal data is encountered, the ML algorithms can highlight possible spurious activities. ML is a self-learning technology that constantly keeps learning from new data and enhances its predictive abilities and adapts to evolving fraudulent activities.

Let’s dig a little deeper into secure payment solutions with AI.

AI has fueled the trend away from cash transactions by boosting speed, safety and expandability at payment processing. As the thrust on digital payment methods increases, the effectiveness of AI systems in fraud prevention increases. AI systems instantly process transactional data to prevent fraudulent activities before they occur. This paves the way for secure payments for both buyers and sellers. AI makes fraud detection and prevention systems scalable by enabling payment systems to process numerous transactions securely and quickly. 

AI-based payment processing can deliver immediate fraud detection, transaction monitoring and compliance checks. It can perform real-time translation of transaction details and communications ensuring seamless transactions with minimal delays. Image recognition technology can verify the authenticity of documents and payment proofs. AI algorithms can process vast amounts of data, identify patterns, and predict outcomes.

In conclusion

The future of payments is digital and AI is the backbone that supports this change. Artificial Intelligence enhances the value of cashless payments making them secure, efficient and customised to the needs of individual users. AI will continue to be the prime mover that supports the transformation to digital payment systems. By leveraging the power of AI, businesses can boost operational efficiency, enhance customer experience and get a competitive edge in the market.

How can Infosys BPM help?

Infosys BPM offers financial services to clients to improve their business models, standardise processes and enhance overall business performance. We provide secure payment processing solutions by implementing cutting-edge AI systems that streamline operations, optimise payment systems and boost security.