Automation of Compliance Checks

Legal compliance in AI training datasets is becoming increasingly complex, far exceeding the capabilities of traditional manual review. Modern datasets are not simple static collections of data but rather evolving, hierarchical systems where individual components originate from diverse sources and undergo multiple transformations. But compliance efforts have largely remained surface-level, focusing on direct license terms while failing to capture the intricate dependencies that emerge as datasets are redistributed and integrated. The risks associated with AI training data have come into the spotlight due to high-profile legal disputes, such as New York Times Co. v. OpenAI, Inc. and Getty Images (US), Inc. v. Stability AI, Inc. While researchers have attempted to develop legal frameworks for responsible AI data usage, existing methodologies remain inadequate in tracking dataset provenance and assessing the full spectrum of legal risks. A new paper in arXiv introduces the Data Compliance framework, moving beyond simple license verification to conduct a holistic legal risk assessment. By incorporating key aspects of copyright law, personal data protection, and unfair competition law, it evaluates datasets across 18 weighted criteria, considering not just explicit licensing terms but also data provenance, transformation processes, and redistribution pathways. However, given the scale and complexity of modern datasets, manual compliance assessment is no longer feasible. Human experts struggle to track multi-level dependencies, often overlooking critical legal risks. That's why they built an automated AI-driven compliance agent, AutoCompliance, to streamline dataset compliance analysis. By systematically identifying dataset dependencies and retrieving their corresponding licensing terms, AutoCompliance evaluates compliance at multiple levels, aggregating individual assessments into a comprehensive risk analysis. This approach ensures better accuracy, scalability, and transparency compared to manual review. Findings from an assessment of 17,429 datasets and 8,072 license terms illustrate the limitations of current compliance practices. Surface-level license reviews were found to be insufficient: while direct license terms indicated that 2,852 datasets were commercially viable, analysis of their dependencies revealed that only 605 (21.21%) posed a legally permissible level of risk for commercialization. Additionally, human legal experts were found to miss over 35% of critical dataset dependencies, while AutoCompliance reduced this gap significantly, missing fewer than 19%. Given the overwhelming scale of modern datasets, the authors argue that AI-driven approaches such as AutoCompliance offer the only viable path forward for scalable dataset compliance. #AICompliance #DataEthics #LegalTech #AIRegulation #ResponsibleAI

Is your enterprise still drowning in regulatory paperwork and manual compliance checks? AI-driven regulatory compliance automation is transforming how businesses navigate the labyrinth of complex regulations across various sectors. With machine learning and natural language processing, AI is doing what humans simply can’t—automating enforcement and monitoring, assessing regulatory impacts in real-time, and adapting to laws faster than you can say "compliance." A survey by Khinvasara et al. (2024) underscores AI's potential in efficiently tracking and managing ever-changing regulations. AI can swiftly determine regulatory applicability, ensuring rule adherence, and mitigating risks. But this isn't just theoretical. Tools like IBM Watson Compliance, Compliance.ai, and various RegTech companies are already on the market, revolutionizing how enterprises handle compliance. These platforms offer everything from real-time data analytics to monitoring employee behavior, making regulatory compliance more efficient than ever before. However, let’s not get carried away. Ethical considerations, data privacy concerns, and the dire need for transparent AI governance loom large. Are we ready to trust AI with our most sensitive compliance needs? #AI #Compliance

When money moves in seconds, compliance can’t wait days. I’m excited to share a critical Castellum.AI update for institutions under pressure to meet real-time SEPA compliance. This isn't just incremental improvement. It's completely eliminating a structural compliance risk that exists in virtually every financial institution doing business in the EU. The reality is that regulators demand real-time sanctions screening, yet the infrastructure supporting it remains fundamentally outdated. EU sanctions often take 48 to 72 hours (sometimes even weeks) to make their way from Official Journal publication into the EU Financial Sanctions Files (FSF) consolidated list. For institutions processing SEPA instant payments, that delay creates an unacceptably wide exposure window in a regime that demands real-time screening. The problem: Legacy systems aren’t equipped to meet the demands of real-time sanctions screening. They can’t: ❌ Scale to handle 24/7 operation ❌ Update sanctions data in real-time ❌ Handle variable transaction volumes efficiently ❌ Conduct comprehensive screening within 10-second settlement windows Our new EU Official Journal Monitoring update solves this directly: ✅ Updates every 5 minutes vs. the industry standard 48-72 hour delay ✅ Automatically extracts, standardizes and enriches complex regulatory data ✅ Enables immediate screening against newly sanctioned entities ✅ Offers enterprise-grade screening to handle large transaction volumes during peak hours Real-world impact: In a recent critical example, sanctions published in the EU Journal on March 27 (Council Implementing Regulation 2025/631) only appeared in the FSF files on April 10 — creating a dangerous two-week compliance blind spot. During this period, financial institutions relying solely on FSF data or legacy screening systems with 24+ hours data refresh cycles were processing transactions against outdated sanctions lists. This is where Castellum.AI comes in. Our Real-Time EU Journal Monitoring update doesn’t just bridge this gap; it enhances compliance data with superior identification details, complete name variants, and full regulatory references, far exceeding the quality of FSF files. In short, we've automated the SEPA compliance workflow, ensuring real-time coverage and peace of mind for your compliance teams.

AI-Powered IT Controls: In today’s world, IT risks are evolving rapidly, and manual control processes often fall short—time-consuming, error-prone, and inefficient. But what if we could automate audits, streamline compliance, and detect risks in real time? AI-powered automation is the game-changer, transforming IT controls into proactive, intelligent, and effortless processes. Let’s explore how AI-driven prompts can make this vision a reality. Reimagining IT Audits with AI What if you could ask AI a question, and it instantly analyzes logs, identifies risks, and provides actionable insights? That’s exactly what custom AI models can do with the right prompts. Instead of sifting through thousands of access logs or manually verifying control effectiveness, AI can: ✔ Scan user access logs for unauthorized privileges ✔ Detect unapproved system changes in seconds ✔ Analyze segregation of duties (SoD) conflicts ✔ Generate instant audit reports with risk ratings This isn’t just about automation—it’s about making IT controls proactive, smarter, and more effective. Real-World AI in IT Controls Let’s take some real-world use cases where AI-powered prompts are transforming IT audits: 1. Automating User Access Reviews 🚀 Before AI: Reviewing user access for hundreds of employees manually—time-consuming and error-prone. ✅ With AI: "Analyze the user access logs for SAP and highlight any violations against the least privilege principle." AI Response: "User X has admin access but is not part of the IT team. User Y has financial access despite being in HR. 5 inactive users still have system access. Recommend immediate action." 2. Detecting Unauthorized Changes 🚀 Before AI: Scrutinizing change management logs for unapproved . ✅ With AI: "Identify any changes in the ERP system that bypassed the change approval process between Jan–Mar 2025." AI Response: "3 changes were deployed without CAB approval. 2 emergency changes lacked post-implementation validation. Recommend stricter enforcement of change controls." 3. Spotting SoD Violations Instantly 🚀 Before AI: Manually checking if a user has conflicting roles in an ERP system. ✅ With AI: "Find users in Oracle Cloud who have both ‘Vendor Creation’ and ‘Payment Processing’ roles." AI Response: "User A and User B have conflicting roles that violate SoD policies. Immediate role adjustments recommended." Why AI is a Game-Changer for IT Audits ✅ Faster, Smarter Audits – AI processes data in seconds, reducing manual effort. ✅ Proactive Risk Detection – Instead of finding issues during audits, AI helps identify risks before they escalate. ✅ Stronger Compliance – Automated reports ensure organizations stay compliant with SOX, GDPR, and other regulations. ✅ Empowered Audit Teams – Instead of spending hours on repetitive tasks, auditors can focus on strategic risk management. AI is transforming IT audits—simplifying compliance, reducing risks, and driving smarter controls. Are you ready to embrace the future?

Automate Your Regulatory Monitoring and Save 80%+ Time Regulatory monitoring is essential for MDR compliance. Tracking updates to legislation, standards, and guidance documents can be a massive task. For some manufacturers, the list spans dozens—or even hundreds—of items. Relying solely on newsletters or LinkedIn posts for updates? It’s tempting, but risky and inefficient. Many teams manually track updates in Excel, which works but consumes valuable time. What if you could automate it? Here’s a 5-step method to automate monitoring and significantly reduce your workload. Before you start: Set up your Excel sheet with these columns: → Link to each regulatory element’s public page → Cut-off date for a month or quarter you want to observe → Last valid date for each element Now, follow these steps: → Scrape public sites to gather data on each regulatory item (requires code). >>>What is scraping? Scraping is a technique to extract data from websites automatically. With the right code, it can pull information (like dates or updates) directly from specified web pages.<<< → Extract the most recent date associated with each document or regulation. → Compare the last recorded date in your sheet with the new date. → Update your sheet’s “last valid date” column if there’s been a change. → Highlight any item where the new date falls between the previous date and cut-off date. Does this require coding skills? Yes. But once set up, it will save countless hours of manual work. If you’re new to coding, consider collaborating with a colleague in development or a peer with programming experience. By automating, you turn a manual, time-consuming process into an efficient one. And remember—always validate your new approach to ensure it’s working correctly! P.S. Would you automate your monitoring or stick with the manual approach? BONUS: Programming languages for scraping: → Python: Popular and beginner-friendly, with libraries like BeautifulSoup and Scrapy for efficient web scraping. → JavaScript (Node.js): Great for dynamic content, with libraries like Puppeteer that work well for scraping. → R: If you’re familiar with R for data analysis, packages like rvest can handle scraping, too. ⬡⬡⬡⬡⬡⬡⬡⬡⬡⬡⬡⬡⬡⬡⬡⬡⬡⬡⬡⬡⬡⬡⬡⬡⬡⬡⬡⬡⬡⬡⬡⬡⬡⬡⬡⬡⬡⬡⬡⬡⬡⬡ The MDR journey is challenging, but there are smart ways to streamline compliance; with the right insights, tools, and guidance. I’m Tibor, passionate about helping you navigate the MDR with confidence! Let’s connect and make regulatory affairs smoother for everybody. #mdr #regulatoryaffairs #medicaldevices

We helped a $10B+ company launch an AI agent for Sanction alert handling in 3 days. It saved them 423 hours in their first month alone. While we tested, tuned and validated it before launch, it's incredible to see how fast the ROI of automating L1 compliance reviews can be. This is specifically for our Sanctions AI - an agent that automates L1 reviews of PEP, adverse media, sanction and watchlist alerts. It closes low risk false positives with extremely high auditability and escalates the 1-5% that need a risk based decision. The best part? Agents work with your existing systems. You don't need to "rip and replace" your current tools to benefit from this type of automation. While a lot of AI work is still in proof of concept land, we're seeing real ROI and improved compliance in production by automating L1 compliance reviews. What do you think?

For 50 Years, Cross-Border Compliance Has Been Stuck in the Past In the world of cross-border payments, compliance and risk checks have traditionally been a slow, manual grind. For decades, the process has looked like this: A payment instruction comes in. A human decides, based on the size of the payment, whether they need a bill of lading, a customs declaration, or an invoice. Then they request the documents from the customer. They read and analyze them. They check if they’ve been altered, forged, or are legitimate. And one of the most critical steps, they scan page after page (sometimes two, sometimes thirty) to look for red flags: sanctioned vessels, sanctioned ports, prohibited goods. It’s slow. It’s expensive. And because we’re human, mistakes happen. Our software changes that. It’s the first-ever system to digitize every part of the cross-border compliance process. From document intake to analysis to sanctions screening, it’s all automated, allowing risk and compliance functions to run up to 98% faster than the old manual way. Faster execution. Lower costs. Fewer errors. This is what the future of cross-border compliance looks like.

Automagic Insight 🪄 Automating Legal Compliance for Wine Orders 🍷 Power Automate Tip of the Day! Did you know? You can automate even government-logged downloads - if you understand how authentication works behind the scenes. I recently helped Free Grape Society (a company I’m proudly invested in) solve a key compliance issue. In Sweden, it’s legally required to verify that a restaurant holds the proper alcohol license before shipping wine to them. We sell wine directly from producers to both businesses and consumers, so streamlining this check was essential. Here’s how I automated it: 🔐 Step 1: Authenticate Securely We identified the identity provider (a Swedish government agency) and confirmed they support basic authentication via HTTP requests. ✅ Store credentials securely (think Azure Key Vault or a custom environment variable in Power Automate) 🔄 Make it easy to update if the password changes Then we simply send an HTTP POST to the login endpoint with the username and password. The response includes an access token. 🎫 Step 2: Use the Access Token In our follow-up HTTP request to download the file, we include: Authorization: Bearer [your-access-token] 🕵️♂️ Step 3: Find the Real URL This part is a classic dev trick: 🔎Open the browser Inspector 🔎Go to the Network tab 🔎Click the “Download” button manually ✅Copy the actual request URL That’s the endpoint we call in Power Automate. No guessing. Just clean reverse engineering. 💾 Step 4: Store It Where You Want The response body? A beautiful Excel payload ready to go. In my case, I pushed it directly to SharePoint – but this could just as easily go to OneDrive, Azure Blob Storage, or email. 💡 This small automation ensures we comply with Swedish law - without slowing down the business. Cheers to automating legal checks before the first sip! 🥂 #PowerAutomate #WorkflowAutomation #Microsoft365 #Productivity #WineTech #ComplianceAutomation