How Banks can Protect Sensitive Customer Data

Evil User Stories: Think Like the Enemy User stories are a cornerstone of Agile development. They’re a concise way to capture the perspective and goals of ours users. But what if we flipped the narrative and considered what we DON'T want? "Evil user stories" allow teams to simulate the motivations and methods of malicious actors. These narratives aren't just thought experiments; they're a practical tool to enhance cybersecurity awareness, identify vulnerabilities, and inspire developers to anticipate and mitigate real threats. Enter The Evil User Story (EUS) An EUS assumes the persona of a malicious actor (e.g.,hacker, disgruntled employee, cybercriminal). By discussing their goals and methods, teams can expose security gaps and reinforce defenses. Sample Evil Scenarios #1: MFA Bypasser As a hacker, I want to bypass multi-factor authentication, so I can gain unauthorized access to sensitive data. Countermeasure: Deploy adaptive MFA using risk-based analysis to detect suspicious login attempts to avoid exposure of PII, regulatory fines, reputational damage, and financial losses. #2: Data Exfiltrator As an insider threat actor, I want to download customer data from a poorly monitored database, so I can sell it on the dark web. Countermeasure: Monitor access logs and enforce robust data loss prevention (DLP) policies to avoid reputation damage, compliance penalties, and erosion of customer trust. #3: Ransomware Deployer As a ransomware developer, I want to encrypt an entire corporate network, so I can demand payment in cryptocurrency. Countermeasure: Implement comprehensive backup strategies and endpoint protection to avoid business interruptions, financial losses, and brand harm. #4: Saboteur As a disgruntled employee, I want to introduce malicious code into production, so I can disrupt operations and harm the company’s reputation. Countermeasure: Enforce strict access controls and conduct thorough code reviews to avoid prolonged downtime and loss of customer trust. #5: Corporate Spy As a competitor-sponsored hacker, I want to infiltrate R&D systems, so I can steal trade secrets for a competitive edge. Countermeasure: Segment networks and use advanced threat detection techniques to avoid loss of IP and market advantage. #6: Social Engineer As a social engineer, I want to impersonate a trusted vendor to access internal systems, so I can escalate privileges. Countermeasure: Verify vendor access and enforce least privilege principles to avoid broad internal compromise. Defense Through Adversarial Insight Evil user stories push teams to think like adversaries, uncovering vulnerabilities, strengthening defenses, and enhancing threat modeling. This adversarial perspective fosters a creative, security-first mindset, helping developers address vulnerabilities during development and improve system resilience. It’s more fun to play the bad guy than be the victim. So, if you were the villain, how would you attack - and stop yourself?

Trust isn’t built with slogans in banking…it’s earned in seconds. Especially when fraudsters are operating faster than ever. I’m watching a major shift in how financial institutions are protecting customers: not by adding more steps, but by building smarter, more adaptive systems. 📲 OTP Bank and Andras Kuharszki are one of the clearest examples. With over 65% of their clients now digitally active, they’ve turned their mobile platform into the primary point of interaction and protection. Instead of relying on outdated static rules or legacy detection systems, they partnered with SEON to implement a real-time fraud prevention layer using: •Digital footprint analysis •Device intelligence •Instant, adaptive decisioning across the customer journey The results speak for themselves: 💸 €6M in fraud losses prevented 🔒 Over 1,000 phishing websites taken down 📉 0 friction added to legitimate users (and an increase of successful verifications) They didn’t stop there. OTP also introduced tools that show how much the game has changed: •A panic button that shuts down all digital access with one tap •Cursor and typing behavior anomaly detection •Verified in-app call authentication to prevent social engineering •Embedded QR/NFC instant payments with fraud checks in milliseconds This is the new benchmark. Fraud prevention that doesn’t just detect, but it protects, in real time, without breaking the user experience. As digital banking accelerates, the divide is growing between banks that patch systems and those that build intelligent fraud orchestration from the ground up. 👏 Big congrats to the OTP team on setting the pace for modern financial protection. #FraudPrevention #DigitalBanking #Cybersecurity

In sensitive environments such as banking applications, balancing security and user privacy is paramount. While many CAPTCHA solutions excel at identifying bots and protecting websites with a seamless user experience, they often rely on collecting extensive user data, including IP addresses and browser information, which can raise significant concerns under stringent regulations. Traditional CAPTCHA solutions provide an effective defense against automated threats by analyzing user interactions. However, their effectiveness often comes at a cost to user privacy: 🚩Data Collection: Many CAPTCHA systems require extensive data collection to function correctly. 🚩Third-Party Sharing: User data may be transmitted to and processed by external entities, potentially exposing sensitive information. 🚩Regulatory Compliance: Compliance with privacy regulations becomes challenging, as organizations must ensure explicit user consent and transparent data handling practices. 🟦🟪🟥A Privacy-Respecting Alternative: Self-Hosted Custom CAPTCHAs and BUA🟦🟪🟥 For applications where privacy is a primary concern, such as banking channels, a more compliant and respectful solution involves combining self-hosted custom CAPTCHAs with Behavioral User Analysis (BUA). 🟦Self-Hosted Custom CAPTCHAs Developing and deploying a custom CAPTCHA solution internally allows organizations to maintain control over user data, eliminating the need to share it with external parties. This approach ensures: • Data Sovereignty: Full control over data collection, storage, and processing. • Customization: Tailoring CAPTCHA challenges to specific security needs without compromising user experience. • Regulatory Compliance: Easier alignment with privacy regulations by keeping data within the organization’s infrastructure. 🟪Behavioral User Analysis (BUA) Integrating BUA with self-hosted CAPTCHAs further strengthens security by analyzing user behavior patterns to differentiate between legitimate users and bots. BUA offers several advantages: • Non-Intrusive: Works in the background without interrupting the user experience. • Enhanced Security: Utilizes advanced metrics such as mouse movements, typing patterns, and interaction timings to detect anomalies. • Privacy Protection: Analyzes behavior internally, ensuring user data remains within the organization and reducing privacy risks. For privacy-conscious applications, especially in sectors like banking, the combination of self-hosted custom CAPTCHAs and Behavioral User Analysis provides a robust, compliant, and privacy-respecting security solution. By retaining full control over user data and minimizing third-party dependencies, organizations can ensure robust protection against automated threats while maintaining user trust and adhering to regulatory requirements.

For companies that have strict data locality and compliance requirements, the ability to secure PII during data replication is crucial. A few ways that companies can handle PII effectively when it comes to data replication: 1️⃣ Column Exclusion: safeguard sensitive information by excluding specific columns from replication entirely, ensuring that they do not appear in the data warehouse or lake for downstream consumption. 2️⃣ Column Allowlist: utilize an allowlist to ensure only non-sensitive, pre-approved columns are replicated, minimizing the risk of exposing sensitive data. 3️⃣ Column Hashing: obfuscating sensitive PII into a hashed format, maintaining privacy while allowing for activity tracking and data analysis without actual data exposure. 4️⃣ Column Encryption: encrypt PII before replication to ensure that data is secure both in transit and at rest, accessible only via decryption keys. 5️⃣ Audit Trails: implement comprehensive logging to track changes to replicated data, which is essential for monitoring, compliance, and security investigations. 6️⃣ Geofencing: control data replication based on geographic boundaries to comply with laws like GDPR, which restricts cross-border data transfers. By integrating these strategies, companies can comply with strict data protection regulations and enhance their reputation by demonstrating a commitment to data security. 🔒 One of our customers is a B2C fintech platform. They use Artie (YC S23) to replicate customer and transaction data across platforms to analyze and monitor changes in risk scores. To ensure compliance with financial regulations and safeguard customer data, the company uses column hashing for sensitive financial details and customer identifiers. This way, they are able to identify important PII changes without exposing sensitive data to their analysts. Additionally, they implemented audit trails (our history mode/SCD tables!) to monitor and log all data changes. Geofencing is utilized to restrict data processing to specific regions, to remain compliant with regulations like GDPR. How is your organization managing PII in data replication? Are there other strategies you find effective? #dataengineering #datareplication #data

Fraudsters continue to exploit vulnerabilities in banking practices using advanced technology and AI, posing a significant threat to financial institutions and customers. From Identity Theft to Business Email Compromise, the risks are diverse and ever-evolving. To combat these challenges and safeguard against fraud, here are 5 actionable steps banks can implement: - Create a strong Anti-Fraud operational system with a Customer holistic approach and run-time decisioning AI models with a feedback loop. - Establish a robust analytical system with continuous enrichment of data attributes and Anti-Fraud models. - Implement a layered approach with Step-up Authentication based on the risk profile of the party & transaction, and ensure continuous monitoring of risk controls at all touchpoints. - Continuously infuse new data attributes & technology through partnerships with aggregators, startups, and consortiums, prioritizing based on data latency & impact. - Provide Financial Education to Customers. By proactively addressing these vulnerabilities, banks can protect their brand reputation, enhance customer trust, and ensure a secure banking environment for all stakeholders. #Banking #FraudPrevention #CustomerExperience #SecurityMeasures #AI

Your bank’s biggest security risk isn’t hackers. It’s weak cybersecurity oversight! The Reserve Bank of India (RBI) just sent a strong warning: Banks must tighten cybersecurity or risk massive fraud. Cybercriminals aren’t just targeting individuals. They’re exploiting weak banking systems to steal millions. RBI is now pushing banks to: 🔹 Strengthen digital fraud prevention 🔹 Monitor third-party vendors closely 🔹 Build robust cybersecurity frameworks How Banks Can Stay Secure: → Stricter third-party security checks Weak vendors = weak security. → Zero-trust approach Verify everything, trust nothing. → Continuous cybersecurity training Employees are the first line of defense. → Real-time fraud detection systems Spot threats before they spread. → Regulatory compliance audits Stay ahead of risks, not behind them. Bonus Point: 🔹 Cybersecurity is no longer an IT issue. It’s a business survival issue. Banks don’t just hold money. They hold trust. And trust is built on security. P.S. Do you think banks are doing enough to prevent cyber threats? Let’s discuss! Repost it to spread more!