Harnessing artificial intelligence to combat merchant fraud in retail

The retail sector has been both blessed and cursed for the fast pace of e-commerce growth and arrival of alternative payments. The boon of online shopping and digitisation has expanded horizons for retailers, but with it comes the bane of increased fraud. Fortunately, Artificial Intelligence (AI) emerges as a stalwart ally in detecting and thwarting merchant fraud. Here’s how AI is revolutionising the fight against fraudulent activities in retail…

  1. Real-time Fraud Detection:
    • Function: AI algorithms can continuously monitor transactions, identifying anomalies and suspicious patterns in real-time, often before a human could even notice them.
    • Benefit: Immediate detection ensures that potentially fraudulent transactions are flagged and investigated swiftly, minimising financial losses and ensuring consumer trust remains intact.
  2. Predictive Analysis:
    • Function: By examining vast sets of historical data, AI can predict potential future fraudulent activities based on past patterns and behaviours.
    • Benefit: Proactively identifying possible fraud before it even occurs puts retailers one step ahead of fraudsters, thereby acting as a deterrent.
  3. Multi-layered Verification:
    • Function: AI can integrate and analyse data from various sources – such as transactional data, customer behaviour, and device ID – to validate the authenticity of a transaction.
    • Benefit: A comprehensive, multi-faceted verification process reduces the likelihood of false positives, ensuring legitimate transactions are not inadvertently blocked.
  4. Natural Language Processing (NLP):
    • Function: AI-driven NLP tools can scan customer communication, feedback, and reviews to identify possible instances or allegations of fraud that might go unnoticed in vast datasets.
    • Benefit: By pinpointing these potential red flags, retailers can proactively investigate and address concerns, bolstering their reputation and trustworthiness.
  5. Deep Learning for Identity Verification:
    • Function: Deep learning, a subset of AI, can be utilised for facial recognition, voice recognition, and other biometric verifications to ensure that a transaction is being made by the legitimate cardholder.
    • Benefit: This level of identity verification significantly reduces instances of identity theft and card-not-present fraud.
  6. Behavioural Analytics:
    • Function: AI can track and analyse the behavioural patterns of users, including browsing habits, purchase history, and even mouse movements, to detect anomalies that might indicate fraud.
    • Benefit: Recognising deviations from a user’s typical behaviour allows for more nuanced fraud detection, reducing both false negatives and positives.
  7. Adaptive Systems:
    • Function: AI systems can learn and adapt. As they encounter new types of fraud or refine their understanding of existing schemes, they can evolve to detect and prevent these new threats more effectively.
    • Benefit: An adaptive system ensures that fraud detection strategies are always up-to-date and equipped to combat the latest tactics employed by fraudsters.

The marriage of retail and AI in the realm of fraud detection and prevention offers a robust shield against malicious activities. While no system can guarantee complete immunity, the capabilities of AI certainly place retailers in a far stronger position to safeguard their assets, reputation, and most importantly, their customers.

You can learn more about the benefits of AI and the anti-fraud benefits it offers at the Merchant Fraud Summit.

Image by Pexels from Pixabay


Stuart O'Brien

All stories by: Stuart O'Brien