Fintech Security Measures

𝗡𝗲𝘅𝘁-𝗟𝗲𝘃𝗲𝗹 𝗗𝗮𝘁𝗮 𝗚𝗼𝘃𝗲𝗿𝗻𝗮𝗻𝗰𝗲: 𝗗𝘆𝗻𝗮𝗺𝗶𝗰 𝗔𝗰𝗰𝗲𝘀𝘀 𝗖𝗼𝗻𝘁𝗿𝗼𝗹 𝘄𝗶𝘁𝗵 𝗔𝗕𝗔𝗖 𝗶𝗻 𝗗𝗮𝘁𝗮𝗯𝗿𝗶𝗰𝗸𝘀 Hej! 👋 We're all familiar with Role-Based Access Control (RBAC) in Unity Catalog: GRANT SELECT ON a_table TO data_analysts. This works well, but what happens when the rules get more complex? What if only certain users can access columns with PII, or if access depends on the user's department? This is where RBAC reaches its limits and we need a more dynamic approach: Attribute-Based Access Control (ABAC). Instead of hundreds of static rules, ABAC allows us to define universal policies based on metadata—or attributes. How It Works in Practice (Simplified) 1. Tag Data with Attributes: First, we classify our data. We assign a tag to a column, table, or schema. - Example: We tag the email column with the tag pii_data = 'true'. 2. Assign Attributes to Users/Groups: We define attributes for our users or groups. - Example: The group finance_de receives the attribute department = 'finance'. 3. Define Rules Connecting Attributes: Now for the magic. We create a rule that uses these attributes. - Example Rule: "ALLOW access to all data tagged with pii_data = 'true' ONLY for groups that have the attribute clearance = 'level_3'." Why is this important? - Scalability: When a new employee joins the team, we just need to assign them to the right group with the right attributes. We no longer have to execute 20 different GRANT commands. Access rights are determined automatically by their attributes. - Dynamism: If the status of data changes (e.g., from "confidential" to "public"), we only need to change the tag on the table. All access rules adapt immediately and automatically. - Fine-Grained Control: ABAC enables extremely detailed control that goes far beyond table or schema boundaries. It is the key to securely managing sensitive data in large organizations. For me, ABAC is the logical evolution of data governance in the Lakehouse. We're moving from a rigid, object-based permission model to a flexible, policy-based system that grows with the business. Are you already using tags in Unity Catalog to classify your data? Or do you already have initial use cases for ABAC in mind? Share your thoughts! 👇 #Databricks #DataGovernance #UnityCatalog #ABAC #BestPractices #DataInsightConsulting

𝟮𝟬 𝗧𝗼𝗽 𝗔𝗣𝗜 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆 𝗧𝗶𝗽𝘀 1. 𝗜𝗺𝗽𝗹𝗲𝗺𝗲𝗻𝘁 𝗦𝘁𝗿𝗼𝗻𝗴 𝗔𝘂𝘁𝗵𝗲𝗻𝘁𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗮𝗻𝗱 𝗔𝘂𝘁𝗵𝗼𝗿𝗶𝘇𝗮𝘁𝗶𝗼𝗻: Make sure only authorized users can access your APIs. Use strong authentication methods, such as OAuth or OpenID Connect, and grant users the least privilege necessary to perform their tasks. 2. 𝗨𝘀𝗲 𝗛𝗧𝗧𝗣𝗦 𝗘𝗻𝗰𝗿𝘆𝗽𝘁𝗶𝗼𝗻: Encrypt all traffic between your APIs and clients to protect sensitive data from being intercepted by attackers. 3. 𝗟𝗶𝗺𝗶𝘁 𝗗𝗮𝘁𝗮 𝗦𝗵𝗮𝗿𝗶𝗻𝗴: APIs should only expose the data that clients need to function. Avoid exposing sensitive data, such as personally identifiable information (PII). 4. 𝗦𝘁𝗼𝗿𝗲 𝗣𝗮𝘀𝘀𝘄𝗼𝗿𝗱𝘀 𝗦𝗲𝗰𝘂𝗿𝗲𝗹𝘆: Hash passwords before storing them in a database. This will help to prevent attackers from stealing passwords if they breach your database. 5. 𝗨𝘀𝗲 𝘁𝗵𝗲 '𝗟𝗲𝗮𝘀𝘁 𝗣𝗿𝗶𝘃𝗶𝗹𝗲𝗴𝗲' 𝗣𝗿𝗶𝗻𝗰𝗶𝗽𝗹𝗲: Give users and applications only the permissions they need to perform their tasks. This will help to minimize the damage if an attacker gains access to an API. 6. 𝗥𝗲𝗴𝘂𝗹𝗮𝗿 𝗨𝗽𝗱𝗮𝘁𝗲𝘀: Keep your API software up to date with the latest security patches. 7. 𝗗𝗶𝘀𝗮𝗯𝗹𝗲 𝗗𝗲𝗳𝗮𝘂𝗹𝘁 𝗘𝗿𝗿𝗼𝗿𝘀: Default error messages can sometimes reveal sensitive information about your API. Configure your API to return generic error messages instead. 8. 𝗦𝗲𝗰𝘂𝗿𝗲 𝗦𝗲𝘀𝘀𝗶𝗼𝗻 𝗠𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁: Use secure methods for managing user sessions, such as using secure cookies with the HttpOnly flag set. 9. 𝗖𝗦𝗥𝗙 𝗧𝗼𝗸𝗲𝗻𝘀: Use CSRF tokens to prevent cross-site request forgery attacks. 10. 𝗦𝗮𝗳𝗲 𝗔𝗣𝗜 𝗗𝗼𝗰𝘂𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻: Your API documentation should not contain any sensitive information. 11. 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆 𝗧𝗲𝘀𝘁𝗶𝗻𝗴: Regularly conduct security testing of your APIs to identify and fix vulnerabilities. 12. 𝗧𝗼𝗸𝗲𝗻 𝗘𝘅𝗽𝗶𝗿𝗮𝘁𝗶𝗼𝗻: Implement token expiration to prevent attackers from using stolen tokens for extended periods. 13. 𝗦𝗲𝗰𝘂𝗿𝗲 𝗗𝗮𝘁𝗮 𝗩𝗮𝗹𝗶𝗱𝗮𝘁𝗶𝗼𝗻: Validate all user input to prevent injection attacks. 14. 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆 𝗛𝗲𝗮𝗱𝗲𝗿𝘀: Use security headers to protect your API from common attacks, such as XSS and clickjacking. 15. 𝗖𝗢𝗥𝗦 𝗖𝗼𝗻𝗳𝗶𝗴𝘂𝗿𝗮𝘁𝗶𝗼𝗻: Configure Cross-Origin Resource Sharing (CORS) to restrict access to your API from unauthorized origins. 16. 𝗧𝗵𝗿𝗼𝘁𝘁𝗹𝗲 𝗟𝗼𝗴𝗶𝗻 𝗔𝘁𝘁𝗲𝗺𝗽𝘁𝘀: Throttle login attempts to prevent brute-force attacks. 17. 𝗔𝗣𝗜 𝗩𝗲𝗿𝘀𝗶𝗼𝗻𝗶𝗻𝗴: Use API versioning to allow you to make changes to your API without breaking existing clients. 18. 𝗗𝗮𝘁𝗮 𝗘𝗻𝗰𝗿𝘆𝗽𝘁𝗶𝗼𝗻: Encrypt data at rest and in transit to protect it from unauthorized access. 19. 𝗟𝗼𝗴𝗴𝗶𝗻𝗴 𝗮𝗻𝗱 𝗔𝘂𝗱𝗶𝘁𝗶𝗻𝗴: Log all API access and activity to help you detect and investigate security incidents. 20. 𝗥𝗮𝘁𝗲 𝗟𝗶𝗺𝗶𝘁𝗶𝗻𝗴: Implement rate limiting to prevent API abuse and overload.

130 employees. 1 IT security person. A phishing attack. No, this isn't a horror movie. It's a Tuesday at a fast-growing fintech startup. When they reached out, they were in crisis mode. One overworked security professional was trying to protect an entire company from phishing attacks. Hiring a CISO would cost $250K+ annually. Complex security tools would take months to implement. We stepped in. Within 48 hours, we transformed their employees into active defenders. When someone clicked a simulated phishing email, they received immediate, personalized training. The math is simple: effective training = stronger security culture = fewer breaches. Within 90 days, their click-through rate on phishing attempts dropped by 87%. Likely, this story has a happy ending. The lesson? Stop seeing security training as compliance. Start seeing it as your competitive advantage. --------------------------------------------------- I'm Mary, making cybersecurity training accessible and engaging for everyone. Follow for practical tips to protect yourself and your organization from digital threats. Let's make security second nature, not second priority!

🚨Inside Indian fintech's new AI playbook: Why Model Context Protocol is gaining popularity Indian fintechs like Zerodha, Razorpay, and Fi Money are building a new layer of infrastructure that lets AI tools act on real financial data securely, in real-time, and with context. It’s called Model Context Protocol (MCP), and it's quietly emerging as the bridge between AI assistants like ChatGPT and internal company systems.* Instead of using dashboards or navigating APIs, users can now talk to AI agents in plain language to check their portfolio, ask for spending summaries, or even initiate payment workflows. “AI tools have become so good that you don’t need a UI anymore,” Zerodha CEO Nithin Kamath wrote in a recent post, sharing screenshots of users querying their investments via AI assistants on the Kite platform. MCP is what makes that possible. It acts as a secure protocol layer, a wrapper over existing APIs, that lets AI assistants access company data or perform actions, but only with user authentication and full control. Think of it as plugging your private data into a smart, conversational interface, but without the privacy risks of just pasting information into large language models like ChatGPT or Gemini. Companies like Razorpay, PayU, and Cashfree are among the early adopters. They are integrating AI assistants to handle tasks ranging from generating payment links to initiating refunds, all with just a simple prompt. "To have intelligent, personalised financial recommendations, you need two things: powerful AI and live, accurate data. That’s why fintechs are building MCPs,” said Tanuj Bhojwani , an independent technology expert. At Zerodha, India’s largest stockbroker, investors can now query their portfolio using natural language through AI assistants like Claude and Cursor, running backtests or analysing stock movements in conversation-like exchanges. According to Bhojwani, MCP does not require deep AI expertise or large infrastructure investments. “Very honestly, it doesn't cost much. It's just a wrapper around existing APIs, with AI coding, a developer can set it up in less than a day or two,” he said. “You can ask AI any personalised question about your financial data,” said Sumit Gwalani, co-founder of Fi Money. “People are calling it their CFO or their CA.” Caution and guardrails As MCP becomes more mainstream, the risk of sensitive data exposure has raised red flags. Zerodha CTO Kailash Nadh cautioned against over-reliance on AI-driven decision-making, especially when users begin delegating trading actions to opaque AI systems. By Bhavya Dilipkumar https://lnkd.in/gd2XBzgi

The US Department of the Treasury has released a report on best practices for Financial Institutions to manage AI-specific #cybersecurity risks. Based on discussions with representatives from FIs, there are a few great learnings from the report which I have tried to condense below: Focus and challenges - The report focused on the use of AI for cybersecurity and fraud management as being the implementations with importance to banks' operations. - Collaboration in the fraud protection space is less coordinated than cyber protection, with smaller FIs struggling to have sufficient data to build predictive capabilities. Firms have highlighted that data-anonymisation techniques could help to mitigate some of these issues. - FIs that have moved data and services to the cloud have the advantage of leveraging AI more rapidly, and will have more time to experiment and refine their AI systems. - However, generative AI models are still developing, costly to implement, and difficult to validate for high-assurance applications. Hence most applications of it are for internal productivity initiatives and using RAG related implementations. - Most implementations have opted for enterprise solutions deployed on their own virtual cloud network or tenanted environments. Risk management approach - Some of the frameworks used by FIs in enhancing their existing risk management practices are NIST RMF, OWASP AI Security and Privacy Guide, OECD AI Principles, and the FSISAC guide for the evaluation of AI vendor risks. - Embedding the management of AI risks into existing policies around model risk, technology risk, cybersecurity risks, and third-party risk management processes. - There will be an expanding role of the Chief Data Officer (or equivalent) to support the innovation and risk management in the integration data supply chain. - There will be an increasing emphasis on effective third-party risk management due to the reliance on third-party providers of data and technology (often extending beyond third-parties). This is definitely worth a read to glean insights from the survey that had been done to create the report. #TrustworthyAI

Fraud is evolving fast. Fortunately, so is the tech behind fighting it In a recent McKinsey & Company interview, Featurespace founder Dave Excell shared how the future of #fraud detection is no longer about spotting known patterns — it’s about understanding behavior What does that mean in practice? Imagine a customer who always shops from Dubai. One day, there’s a purchase from Lagos at 3 AM — followed by a second one, just minutes later, for a high-end TV. That’s not just unusual — it’s behaviorally impossible. Instead of waiting for damage, Featurespace’s AI flags the behavior itself — not just the transaction — and intervenes in real time. That’s the power of behavioral analytics. And it’s already delivering results. Banks using Featurespace’s ARIC platform report up to 75% fewer false positives — meaning fewer blocked good customers, and faster action on real threats. The takeaway? #AI is no longer just a fraud filter. It’s a reputational moat. In a world of faster payments and higher stakes, trust depends on staying one step ahead. Curious how this could reshape fraud protection in our region? #FraudPrevention #Fintech #PaymentsInnovation #CyberSecurity #RiskManagement #Leadership #Innovation #Payments #Digital https://lnkd.in/eEeUjwHD

Data access isn’t just a technical challenge; it’s a foundation for responsible innovation across the enterprise. As organizations scale data, AI, and analytics initiatives, the ability to balance agility, security, and compliance becomes a boardroom conversation. RBAC (Role-Based Access Control) has been the workhorse for access management, straightforwardly granting permissions based on defined roles, think “Finance Analyst” or “HR Manager.” It’s clear, easy to audit, and effective for static user groups and simple business logic. But the real world rarely fits within fixed roles. This is where ABAC (Attribute-Based Access Control) in Databricks makes a difference. ABAC uses dynamic attributes such as time, geographic region, and data classification to govern access in real time. Suddenly, granting temporary collaboration rights for a cross-border team or restricting access to confidential records based on sensitivity becomes seamless, reducing the risk of overexposure and manual error. For data practitioners, this means less firefighting and more time building. For executives, it means a governance model that adapts to change, whether responding to new regulations, organizational shifts, or growth into new markets. The interplay between RBAC and ABAC in platforms like Unity Catalog gives organizations the best of both worlds: clarity, accountability, and agility. In practice, RBAC establishes the baseline (“who can access what”), while ABAC adds context and flexibility (“under what conditions”). This layered approach not only future-proofs data and AI governance, but it also unlocks new possibilities enabling secure data sharing, collaborative AI, and compliant innovation at scale. #ABAC #RBAC #DataGovernance #UnityCatalog #Databricks

Why DevSecOps is Non-Negotiable for Financial Services? Let me paint you a picture: Imagine a bank launches a new mobile app. Great UI, fast transactions, good reviews etc. But three months later? Chaos. A vulnerability exploited, thousands of accounts compromised. The culprit? A simple oversight in the development process. 🔒 Why DevSecOps is your shield: - Proactive Defense: By baking security into every stage of development, we catch vulnerabilities before they catch us. - Rapid Response: With the right processes in place, I've seen teams cut incident response time by 60%. - Compliance by Design: In FinServ's regulatory minefield, DevSecOps ensures compliance is in the DNA of your software. - Cost Efficiency: Fixing a security flaw in production can cost up to 100 times more than catching it in development. - Innovation Enabler: Counter-intuitive, but true. When security is integrated, teams can innovate faster, knowing they're building on a secure foundation. 🛠️ Real-world strategies I've seen work: - Automated security testing in CI/CD pipelines - Regular threat modeling sessions (yes, even for that "small" feature) - Security champions program across development teams - Continuous security training (because that phishing email is getting smarter) The stakes in financial services are too high for security to be a checkbox. To all FinServ leaders - If DevSecOps isn't on your priority list, it's time to rewrite it. Pro tip - Just DevSecOps alone is not going to help either. This needs to be paired with secure SDLC, TDD and shift left approaches to testing. #DevSecOps #FinancialSecurity #SecureSDLC #FinTech

The architecture of cross-border payments is shifting — and it’s no longer just about speed. It’s about programmability, transparency, and compliance by design. Circle newly launched Payments Network (CPN) is not a minor enhancement to legacy systems — it’s a fundamentally different model. One where regulated stablecoins (USDC, EURC) act as digital cash, settlement is near-instant, and participants are governed by enforceable standards. How does CPN stand apart? • Value transfer, not just message exchange • Settlement finality in seconds, not days • No reliance on correspondent banking chains • Full transparency with on-chain audit trails • Compliance-embedded — KYC, AML, cybersecurity built into the network design It’s a network where every transaction is verifiable, programmable, and borderless — opening new possibilities for real-time treasury, trade, and payments innovation. As someone deeply engaged with ISO 20022, structured data, and the future of regulated payments infrastructure — this evolution is both timely and necessary. The question isn’t whether these networks will coexist. It’s whether traditional rails will keep pace with programmable money. Biju Nicolas Pinto Sam Boboev #payments #financialservices #swift #stablecoins #cbdc #treasury #iso20022 #blockchain

Yesterday, AMLA - the new European Anti-Moneylaundering Agency - started its work. AMLA is a big opportunity to fix what’s broken in Europe’s fight against financial crime. If I had 6 wishes for them (from a fintech, RegTech and digital banking lens), here’s what I’d ask: 1️⃣ One consistent AML rulebook for Europe: End the patchwork. No more national gold-plating. Let fintechs and banks operate cross-border with one clear, risk-based standard. 2️⃣ Accelerate RegTech adoption: Encourage the use of AI, network analytics and modern transaction monitoring tools - not just in banks, but also in supervision. Fraudsters adapt fast. Regulators and financial institutions need to move even faster. That means better frameworks for onboarding new technologies, including sandbox environments for fast testing and validation. 3️⃣ Proportionality for new and small players: A 10-person fintech shouldn’t face the same compliance burden as a Tier-1 bank. Let’s enable innovation without killing it through regulation. 4️⃣ Real-time, cross-border intelligence sharing: Financial crime doesn’t stop at borders. AMLA should drive seamless data sharing between FIUs and supervisors - and encourage standardized APIs that fintechs can connect to. 5️⃣ Clear guidance for crypto and digital assets: Let’s stop the grey zones. Fintechs need clear, actionable rules on travel rule compliance, VASP supervision and DeFi-related risks. Digital assets are here to stay. 6️⃣ Stronger public-private partnerships Banks and fintechs see the patterns first. AMLA should foster joint typology development and real-time risk signal sharing - beyond just filing suspicious transaction reports. 7️⃣ Fix the staffing crisis at national FIUs: Financial crime prevention doesn’t end with the banks. Too many FIUs remain understaffed and overwhelmed. Banks get fined for SAR filing delays - but even when they file on time, FIUs are often too overloaded to act. Let’s fix that. If AMLA delivers on this, it won’t just reduce financial crime - it’ll also make Europe a safer and more innovation-friendly place to build compliance innovation. I wish them all the best! >> What are your thoughts on this? #banking #fintech #compliance #amla