PCI COMPLIANCES by Udi Levin, AI Risk PCI and Cybersecurity

Tag: credit card

  • AI and Identity Management

    AI and Identity Management

    MBTI in the Age of AI: From Static Labels to Dynamic Cognitive Mapping

    For decades, tools like MBTI helped organizations understand personality preferences — how people decide, process information, and lead.

    But AI is about to fundamentally reshape that model.

    Why?

    Because personality classification has always been based on self-reported answers in controlled questionnaires.

    AI, however, can now analyze:

    • Decision patterns over time

    • Communication style in emails and chats

    • Risk tolerance in real operational environments

    • Stress response in incident situations

    • Collaboration behavior in distributed teams

    Instead of a static 4-letter type, AI can build a dynamic cognitive-behavioral profile — continuously updated.

    ⸻

    What does this mean for Cyber & Risk Leaders?

    In cybersecurity and risk management, personality traits influence:

    • Incident response under pressure

    • Escalation timing

    • Control interpretation

    • Threat prioritization

    • Governance vs innovation bias

    An AI model trained on SOC behavior, audit decisions, or policy exceptions could identify:

    • Who detects anomalies fastest

    • Who over-calibrates risk

    • Who under-reacts

    • Who is best suited for zero-day response vs compliance governance

    This is similar to how AI now reads radiology scans — sometimes outperforming experts by detecting subtle patterns invisible to the human eye.

    In cyber, AI may soon detect cognitive blind spots better than managers can.

    ⸻

    The Identity Manager Impact

    Identity and Access Management (IAM) has traditionally focused on:

    • Roles

    • Policies

    • Entitlements

    But AI introduces a new dimension:

    Behavioral identity.

    Future IAM systems may adjust access dynamically based not only on role — but on behavioral deviation, stress signals, anomaly in cognitive patterns, or risk posture changes.

    Zero Trust could evolve from:

    “Never trust, always verify”

    to:

    “Continuously evaluate human cognitive behavior.”

    ⸻

    The Big Question

    If AI can profile cognitive patterns better than self-assessment tools…

    Do we still need MBTI?

    Or does personality become:

    • Real-time

    • Contextual

    • Measured through action rather than declared preference?

    The opportunity is enormous.

    The ethical implications are even larger.

    What happens when AI knows how you decide — better than you do?

    #AI #CyberSecurity #RiskManagement #ZeroTrust #IAM #Leadership #FutureOfWork

  • Credit Card Processor Risk of Attack

    Credit Card Processor Risk of Attack

    There have been successful attacks on credit card processors in the past. Credit card processors, which are responsible for handling payment transactions between merchants, banks, and card issuers, can be targeted by attackers seeking to steal payment data or disrupt payment processing operations.
    One notable example is the 2014 cyberattack on JPMorgan Chase, which is one of the largest processors of credit card transactions in the world. In this attack, hackers gained access to the bank’s computer systems and stole the personal and financial information of over 83 million customers, including credit card data.

    Another example is the 2018 breach of the payment processing company, First Data. In this attack, hackers gained access to a web application used by First Data and stole payment card information of customers from a number of merchant websites.

    These attacks highlight the need for credit card processors to implement robust security measures and constantly monitor their systems for vulnerabilities and suspicious activity. They also demonstrate the importance of maintaining a strong security posture throughout the payment processing ecosystem, including merchants, banks, and card issuers, to prevent attacks and protect sensitive payment data.