CovenantIQ

🔐 We are pleased to announce that CovenantIQ has successfully completed its SOC 2 Type II examination in accordance with the American Institute of Certified Public Accountants (AICPA) standards. This milestone reflects our continued commitment to maintaining strong controls around security, availability, confidentiality, and the responsible handling of customer data. As a platform supporting borrower financial reporting, covenant monitoring, and portfolio management, earning the trust of our customers is fundamental to everything we do. Completing the SOC 2 Type II examination demonstrates that our security controls are not only appropriately designed, but also operated effectively throughout the audit period. We remain committed to investing in the systems, processes, and operational discipline required to protect sensitive financial information and support the security expectations of banks and private credit firms. Thank you to Prescient Security for their guidance and support throughout the process. Learn how we approach data security and stewardship: https://lnkd.in/gRnz7XYT #SOC2 #InformationSecurity #DataSecurity #Compliance #Fintech #PrivateCredit #LendingTechnology

🚨 𝗡𝗲𝘄 𝗪𝗲𝗯𝘀𝗶𝘁𝗲 𝗔𝗹𝗲𝗿𝘁 The new CovenantIQ website is live. We rebuilt the site to better show how CovenantIQ supports the full loan-monitoring workflow—from collecting borrower data through ongoing portfolio oversight. The new site covers how lenders can: • Standardize borrower financial and operational data • Map reporting to credit agreement requirements • Calculate and track covenants and KPIs • Manage reporting obligations and deadlines • Monitor borrower performance and emerging risk • Build consistent borrower and portfolio-level reporting You will also find new product walkthroughs, platform screenshots, customer testimonials, security information, and a self-guided demo. Our goal remains simple: 𝗵𝗲𝗹𝗽 𝗹𝗲𝗻𝗱𝗶𝗻𝗴 𝘁𝗲𝗮𝗺𝘀 𝘀𝗽𝗲𝗻𝗱 𝗹𝗲𝘀𝘀 𝘁𝗶𝗺𝗲 𝗰𝗵𝗮𝘀𝗶𝗻𝗴 𝗱𝗮𝘁𝗮 𝗮𝗻𝗱 𝗺𝗮𝗻𝗮𝗴𝗶𝗻𝗴 𝘀𝗽𝗿𝗲𝗮𝗱𝘀𝗵𝗲𝗲𝘁𝘀, 𝗮𝗻𝗱 𝗺𝗼𝗿𝗲 𝘁𝗶𝗺𝗲 𝗮𝗻𝗮𝗹𝘆𝘇𝗶𝗻𝗴 𝗿𝗶𝘀𝗸 𝗮𝗻𝗱 𝗲𝗻𝗴𝗮𝗴𝗶𝗻𝗴 𝗯𝗼𝗿𝗿𝗼𝘄𝗲𝗿𝘀. Take a look: covenantiq.io #PrivateCredit #CommercialLending #CreditRisk #LoanMonitoring #CovenantMonitoring #Fintech

⚠️ Most AI demos in private credit start with generic prompts: “Can AI generate the report?” “Can it summarize financials?” “Can it draft the memo?” Useful, but not enough. ✅ The real value comes when AI can answer the questions lenders actually ask: → Where is the synergy add-back coming from, and how does it compare to the underwriting model? → What drove the covenant headroom movement over the last three months? → Which revenue category is causing EBITDA margin compression? → Are borrower-reported KPIs consistent with the underlying financial statements? → Did the latest restatement change leverage, DSCR or liquidity headroom? → Is performance deterioration isolated to one account, one business unit, or a broader trend? These are not generic summarization questions. They require structured borrower data, a consistent financial taxonomy, credit agreement logic, historical comparability, and traceability back to source. That is why data standardization matters. Without it, AI can draft language. With it, AI can help surface actual credit insight. At CovenantIQ, we focus on building the data foundation first: ingesting borrower financials, normalizing them into a consistent taxonomy, mapping them to lender-specific metrics and covenants, and making every calculation traceable. ❌ The future of loan monitoring is not replacing people with AI. ✅ It is giving great teams better infrastructure so they can focus on the work that actually requires expertise. #PrivateCredit #LoanOperations #CreditMonitoring #CovenantCompliance #PortfolioMonitoring #DataStandardization #FinancialData #AIinFinance #FinTech #CreditRisk

⚠️ Most AI demos in private credit start with generic prompts: “Can AI generate the report?” “Can it summarize financials?” “Can it draft the memo?” Useful, but not enough. ✅ The real value comes when AI can answer the questions lenders actually ask: → Where is the synergy add-back coming from, and how does it compare to the underwriting model? → What drove the covenant headroom movement over the last three months? → Which revenue category is causing EBITDA margin compression? → Are borrower-reported KPIs consistent with the underlying financial statements? → Did the latest restatement change leverage, DSCR or liquidity headroom? → Is performance deterioration isolated to one account, one business unit, or a broader trend? These are not generic summarization questions. They require structured borrower data, a consistent financial taxonomy, credit agreement logic, historical comparability, and traceability back to source. That is why data standardization matters. Without it, AI can draft language. With it, AI can help surface actual credit insight. At CovenantIQ, we focus on building the data foundation first: ingesting borrower financials, normalizing them into a consistent taxonomy, mapping them to lender-specific metrics and covenants, and making every calculation traceable. ❌ The future of loan monitoring is not replacing people with AI. ✅ It is giving great teams better infrastructure so they can focus on the work that actually requires expertise. #PrivateCredit #LoanOperations #CreditMonitoring #CovenantCompliance #PortfolioMonitoring #DataStandardization #FinancialData #AIinFinance #FinTech #CreditRisk

⚠️ In Private Credit and Banks alike, credit analysts spend too much time rebuilding the same reports every month or quarter. Credit memos. Borrower updates. Covenant summaries. Portfolio reviews. LP reporting packages. The format may change, but the workflow is often the same: gather files, normalize data, calculate metrics, update tables, write commentary, and reconcile everything back to source data. We built CovenantIQ Custom Reports to make that process faster, more consistent, and more auditable. With CIQ, teams can generate borrower-level and portfolio-level reports using trusted financial data, lender-defined calculations, KPI charts, covenant outputs, EBITDA adjustments, and AI-assisted summaries: All with traceability back to source data. The goal is not to replace analyst judgment. It is to eliminate the repetitive preparation work so analysts can spend more time on the work that matters: understanding performance, identifying risk, and communicating insights clearly. Read more here: https://lnkd.in/gEZ_ykyA #PrivateCredit #CreditMonitoring #CreditRisk #PortfolioMonitoring #CreditAnalysis #LendingTechnology #FinTech #CovenantMonitoring #CovenantIQ #CreditMemo

⚠️ In Private Credit and Banks alike, credit analysts spend too much time rebuilding the same reports every month or quarter. Credit memos. Borrower updates. Covenant summaries. Portfolio reviews. LP reporting packages. The format may change, but the workflow is often the same: gather files, normalize data, calculate metrics, update tables, write commentary, and reconcile everything back to source data. We built CovenantIQ Custom Reports to make that process faster, more consistent, and more auditable. With CIQ, teams can generate borrower-level and portfolio-level reports using trusted financial data, lender-defined calculations, KPI charts, covenant outputs, EBITDA adjustments, and AI-assisted summaries: All with traceability back to source data. The goal is not to replace analyst judgment. It is to eliminate the repetitive preparation work so analysts can spend more time on the work that matters: understanding performance, identifying risk, and communicating insights clearly. Read more here: https://lnkd.in/gEZ_ykyA #PrivateCredit #CreditMonitoring #CreditRisk #PortfolioMonitoring #CreditAnalysis #LendingTechnology #FinTech #CovenantMonitoring #CovenantIQ #CreditMemo

𝗛𝗼𝘄 𝗺𝘂𝗰𝗵 𝘁𝗶𝗺𝗲 𝗶𝘀 𝘆𝗼𝘂𝗿 𝘁𝗲𝗮𝗺 𝗿𝗲𝗮𝗹𝗹𝘆 𝘀𝗽𝗲𝗻𝗱𝗶𝗻𝗴 𝗷𝘂𝘀𝘁 𝗽𝘂𝗹𝗹𝗶𝗻𝗴 𝗱𝗮𝘁𝗮 𝘁𝗼𝗴𝗲𝘁𝗵𝗲𝗿?! Across most private credit teams we speak with, per borrower: ⚠️ 10–15 hours consolidating financials across entities and formats ⚠️ 6–8 hours recalculating EBITDA and adjustments from credit agreements ⚠️ 6–8 hours updating covenant models and validating outputs ⚠️ 10–12 hours preparing internal or LP-ready reporting ‼️ That’s ~30–45 hours per borrower — before any real credit work begins. And this is happening every quarter. Now zoom out. The latest The Private Markets Forum report confirms this isn’t just inefficiency — it’s structural: • 45% 𝘰𝘧 𝘧𝘪𝘳𝘮𝘴 𝘴𝘢𝘺 𝘢 𝘶𝘯𝘪𝘧𝘪𝘦𝘥 𝘥𝘢𝘵𝘢 𝘮𝘰𝘥𝘦𝘭 𝘪𝘴 𝘵𝘩𝘦 #1 𝘱𝘳𝘰𝘣𝘭𝘦𝘮 𝘵𝘰 𝘴𝘰𝘭𝘷𝘦 • 𝘋𝘢𝘵𝘢 𝘪𝘯𝘨𝘦𝘴𝘵𝘪𝘰𝘯 𝘢𝘯𝘥 𝘮𝘰𝘯𝘪𝘵𝘰𝘳𝘪𝘯𝘨 𝘳𝘦𝘮𝘢𝘪𝘯 𝘴𝘰𝘮𝘦 𝘰𝘧 𝘵𝘩𝘦 𝘮𝘰𝘴𝘵 𝘮𝘢𝘯𝘶𝘢𝘭 𝘸𝘰𝘳𝘬𝘧𝘭𝘰𝘸𝘴 • 71% 𝘰𝘧 𝘧𝘪𝘳𝘮𝘴 𝘩𝘢𝘷𝘦 𝘣𝘶𝘪𝘭𝘵 𝘪𝘯𝘵𝘦𝘳𝘯𝘢𝘭 𝘵𝘰𝘰𝘭𝘴 𝘵𝘰 𝘧𝘪𝘭𝘭 𝘨𝘢𝘱𝘴 • 𝘓𝘗𝘴 𝘢𝘳𝘦 𝘥𝘦𝘮𝘢𝘯𝘥𝘪𝘯𝘨 𝘧𝘢𝘴𝘵𝘦𝘳, 𝘮𝘰𝘳𝘦 𝘨𝘳𝘢𝘯𝘶𝘭𝘢𝘳, 𝘢𝘯𝘥 𝘳𝘦𝘢𝘭-𝘵𝘪𝘮𝘦 𝘥𝘢𝘵𝘢 𝘢𝘤𝘤𝘦𝘴𝘴 𝗪𝗵𝗮𝘁 𝘁𝗵𝗶𝘀 𝗿𝗲𝗮𝗹𝗹𝘆 𝗺𝗲𝗮𝗻𝘀: Analysts aren’t just analyzing credit. They’re acting as the 𝗶𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻 𝗹𝗮𝘆𝗲𝗿 across fragmented systems and data. ✅ At CovenantIQ, the goal isn’t to replace analysts — it’s to give that time back. So instead of spending hours gathering and stitching data: → Analysts can focus on movements in AR aging and early warning signals → Dig into what’s actually driving Adjusted EBITDA and coverage ratios → Spend time validating covenant performance, not rebuilding it → Move from quarterly check-ins to monthly (or continuous) tracking → Turn LP reporting into borrower-level insights, not just templates Under the hood, that shift comes from: → ingesting borrower financials directly from source systems → standardizing them into a consistent structure → mapping covenant logic once, and applying it consistently → continuously updating performance and compliance 𝗧𝗵𝗲 𝗿𝗲𝗽𝗼𝗿𝘁 𝗳𝗿𝗮𝗺𝗲𝘀 𝗶𝘁 𝘄𝗲𝗹𝗹: 𝗣𝗿𝗶𝘃𝗮𝘁𝗲 𝗰𝗿𝗲𝗱𝗶𝘁 𝗱𝗼𝗲𝘀𝗻’𝘁 𝗵𝗮𝘃𝗲 𝗮 𝘁𝗼𝗼𝗹𝗶𝗻𝗴 𝗽𝗿𝗼𝗯𝗹𝗲𝗺. 𝗜𝘁 𝗵𝗮𝘀 𝗮 𝗱𝗮𝘁𝗮 𝗳𝗼𝘂𝗻𝗱𝗮𝘁𝗶𝗼𝗻 𝗽𝗿𝗼𝗯𝗹𝗲𝗺. Fix that — and the role of the analyst becomes a lot more valuable. Curious how others are thinking about this — where does your team spend the most time today: gathering data or actually analyzing it? Marc Andrew https://lnkd.in/dnj94Mdp

Most AI conversations in Private Credit start at the wrong place. “Can AI generate a report?” “Can it summarize financials?” The better question is: what is the analyst actually spending time on today? In lower middle market lending, the answer hasn’t changed much: → Gathering borrower files → Normalizing inconsistent data → Rebuilding the same reports every month ⚠️ That’s not analysis. That’s preparation. At CovenantIQ, we’ve always focused on structuring and normalizing borrower financial data first—because AI is only as good as the data it sits on. Now, with our AI Agent Platform, we’re addressing the next bottleneck: Analyst Time. 🧠 Instead of starting from scratch every cycle, analysts can: • Automatically summarize borrower financials • Identify trends and anomalies across cash flow and liquidity • See projected impacts to key covenants and metrics • Start with insights—not spreadsheets And importantly, this all runs when new data is available—not weeks later. ❌ The goal isn’t to replace analysts. ✅ It’s to remove the repetitive work so they can focus on what actually matters: risk, performance, and forward-looking decisions. Our very own Brandon Mason captures this well using a simple analogy: AI tools are like walking into Home Depot. CovenantIQ is the contractor that turns those tools into finished work. Worth a read 👇 https://lnkd.in/g_kpk26B #PrivateCredit #DirectLending #CreditRisk #FinTech #AI #CovenantMonitoring #MiddleMarket

A lot of focus goes into underwriting and deal structure, but the real test begins after the deal closes. Aggressive EBITDA adjustments can widen the gap between projected performance and actual cash flow. That’s why ongoing borrower monitoring and covenant discipline matter. 👇Curious what others have seen — what’s the most creative EBITDA adjustment you’ve encountered? #PrivateCredit #MiddleMarket #CreditRisk #CommercialLending #DirectLending #Covenants