How AI-powered Social Monitoring Can Help Prevent Payment Fraud

All stakeholders of digital payments - consumers, banks, payment gateway technology partners, fintech companies and regulatory authorities - are constantly looking for newer ways to prevent fraud. Newer methods call for innovations such as artificial intelligence (AI) and social monitoring. Artificial intelligence involves comprehension, assimilation and inferring by machines based on certain data. Social monitoring is tracking content on social media sites, blogs, online forums and websites to understand what people are talking about. Both of these can come together to avoid payment fraud.

Payment fraud is when a person, say, Mr. X, steals the information of Mr. Y and makes unauthorised transactions or purchases. He can execute this by stealing identity or stealing accounts or posing as customer service executives or sending fraudulent emails that look genuine.

Listed below are some ways in which AI-powered social monitoring can help payment fraud prevention:

Real-Time Monitoring

Digital transactions are fast, and there are many transactions. Traditional rule-based fraud detection systems are not fast enough for them but AI-based monitoring is fast and real-time. When financial fraud transactions are reported on social media, the AI collects the details of the people behind them and creates a central repository. It can also give real-time alerts to avoid potential financial fraud. It can also be used to look for certain keywords or hashtags that call out bad players and initiate the necessary action.

Fraud Detection

AI-based social monitoring can use various tools to detect fake accounts on social media by analysing their profile information, activity history and other data points. It can also analyse the trends and patterns in social media that could indicate potential fraud. Only with early detection, prevention is possible.

Customer Behaviour Analysis

The key feature of AI tools is that they can closely watch and analyse customer behaviour. This tool can detect suspicious activities by analysing user behaviour and patterns like say posting of fraudulent schemes or requesting payments.

Predictive Analytics

AI coupled with machine learning has impressive capabilities. Machine learning allows machines to make accurate predictions based on large sets of data. Hence, AI-based social monitoring can process large data and predict user behaviour to flag off potential breaches to payment security. Say the recent frauds all point out to the fraudsters deleting social media accounts prior to committing frauds, the tool can predict this behaviour and apply it to suspicious accounts.

Risk Assessment

AI-based tools can conduct risk profiling for users based on certain criteria. Since its data processing abilities are vast it can run many rules, also the rules can be dynamic. So a risk assessment of the end consumer can be used as a prerequisite to payment processing by the payment gateway.

Sentiment Analysis

This AI tool monitors fintech products by analysing news and reviews from apps, play stores and other data points. This helps in analysing people's overall sentiment towards digital payments, payment and fintech products and their security. Every digital user is leaving a digital footprint, AI-based social monitoring tools are simply studying these footprints and identifying fraudsters.

A good payment gateway can integrate with these AI tools to enhance fraud detection and provide end consumers with a safe payment experience. Check out the secure and reliable Worldline payment gateway that can help your business grow!