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AI MONTH: AI and Fraud Prevention – A confluence of technology and security
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Businesses and financial institutions face a constantly mutating landscape of fraudulent activities. Traditional systems, once hailed as robust, now frequently lag behind in detecting and preventing contemporary fraud schemes. Enter Artificial Intelligence (AI): a transformative force that’s reshaping fraud prevention by providing real-time, predictive, and adaptable solutions. Here we explore the growing influence of AI in combatting fraud and safeguarding assets, based on input from delegates and suppliers at the Merchant Fraud Summit…

  1. Real-time Transaction Analysis: AI can process vast amounts of data at lightning speeds. This allows it to assess each transaction in real-time, comparing it against patterns of normal behaviour. If a transaction looks suspicious (say, an unusually large purchase made in a foreign country late at night), the AI system can flag it instantly for review or even block it until it’s verified.
  2. Deep Learning for Pattern Recognition: Fraudsters are known for their adaptability, constantly changing tactics to evade detection. Deep learning, a subset of AI, empowers systems to ‘learn’ from vast datasets, recognising patterns and anomalies without being explicitly programmed. This means that even if fraudsters alter their tactics, AI systems trained using deep learning can detect these new patterns, keeping businesses one step ahead.
  3. Predictive Fraud Analysis: Beyond merely detecting known fraudulent tactics, AI leverages predictive analytics to forecast potential future threats. By analysing historical fraud data and blending it with current transaction trends, AI can offer predictions about where and when the next potential fraud might occur. This proactive approach allows businesses to bolster security in vulnerable areas before a breach happens.
  4. Enhanced Authentication Protocols: AI has amplified the capabilities of biometric authentication methods like facial recognition, voice analysis, and fingerprint scanning. By continuously learning and updating individual profiles, AI ensures that only the authentic user can access accounts, thereby drastically reducing identity theft or account takeovers.
  5. Natural Language Processing for Phishing Detection: Phishing emails are a common tool in a fraudster’s arsenal. AI, equipped with Natural Language Processing (NLP), can scan emails and detect subtle linguistic cues that might indicate a phishing attempt, protecting users from potential threats.
  6. Automated Reporting and Decision Making: Post-incident reports are crucial for understanding breaches and strengthening defences. AI can automate this process, collating data, suggesting remedial measures, and even implementing certain protective protocols without human intervention.
  7. Adaptable and Self-learning Systems: One of the greatest advantages of AI is its inherent adaptability. As it encounters new types of fraud or even near-miss events, it learns, refines its algorithms, and becomes even more effective in subsequent detections.

AI is not merely a tool but a dynamic shield adapting and evolving in the face of emerging threats. As businesses and transactions continue their inexorable shift online, AI stands as a sentinel, safeguarding assets and instilling trust in systems. The fusion of AI and fraud prevention is an exemplar of how technology can be harnessed to protect, predict, and prevail against malicious intent.

Are you looking for mobile anti-fraud solutions for your business? The Merchant Fraud Summit can help!

Photo by Possessed Photography on Unsplash

Harnessing artificial intelligence to combat merchant fraud in retail
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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

Bribery and corruption concerns drive 650% increase for Regtech AI KYC checks in banking sector
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A new study from Juniper Research has found that the total number of Know Your Customer (KYC) checks for banking, conducted using AI, will reach almost 175 million globally by 2028; up from just over 23 million in 2023.

The demand for regtech solutions is increasing across not only financial services, but also industries such as healthcare and cybersecurity, as continuous verification of identities becomes fundamental in preventing financial crime and non-compliance.

One example of this is the rise of virtual GPs and ePharmacies. Here, Juniper says it is vital for KYP (Know Your Patient) verification to be employed, in order to prevent fraud, such as identity theft and financial exploitation. By implementing these KYC verifications, businesses can avoid fines for failing to carry out customer assessments.  

The report encourages cross-border businesses to adopt regtech solutions in order to reduce risk across different regulatory jurisdictions. As multinational companies expand into new regions, they are faced with a fragmented regulatory framework comprising jurisdictional differences across varying markets. Failure to meet compliance demands can lead to businesses facing penalties; resulting in serious economic and reputational consequences.

The recent emergence of “Failure to Prevent” offences specifically target organisations to hold them accountable for failures in their compliance system. Implementing regtech solutions enables organisations to defend themselves from this type of allegations.

The report found that innovative vendors are using AI and machine learning to decipher email and phone call data to identify bad actors across organisations. This is vital as lawmakers and regulatory bodies are cracking down on bribery and corruption offences, which severely undermine fair competition and contribute to slow economic growth.

Juniper Research recommends that as businesses expand their operations and move into new regions, they deploy AI-powered regtech solutions to automate monitoring of regulatory compliance; reducing manual checks being required and overall risk.

Image by Gerd Altmann from Pixabay

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