Nehal B.’s Post

This blog delves into how BI systems empower financial institutions to transform raw data into actionable insights, enhancing their ability to navigate regulatory landscapes and mitigate risks effectively. Discover how Anaptyss’ Factum BI dashboard can elevate your compliance strategy and enable smarter, data-driven decision-making. Read More:https://lnkd.in/eFdd7_NH #BI #dashboard #Factum #Anaptyss #compliance #risk #DigitalServices

My top 5 reasons why financial firms are still using batch systems in their Risk Management Systems—and what they must do to fix it 👇 Many trading firms and financial institutions still rely on batching systems to calculate risk. But why? It’s not because they don’t see the limitations—it’s due to complex legacy systems and the challenges of upgrading. Here’s why they’re stuck with batching, and what they can do to change it: 1️⃣ Legacy Systems Are Too Deeply Embedded Many firms have legacy systems that are so linked to operations that replacing them seems impossible without disrupting the whole business. 💡 Add Real-Time Layers on Top of Your Existing System Instead of overhauling everything, add modular real-time layers to your current system. This lets you move some functions to real-time processing without breaking the system. Over time, you can transition more areas without major disruptions. 2️⃣ Poor Connectivity Between Internal and External Systems Firms struggle to connect their risk management systems with market data or internal tools like OMS/EMS. This makes real-time updates difficult. 💡 Use APIs for Real-Time Data Integration Replace batch data with API-driven integrations to get real-time data from market feeds and internal systems. This keeps your risk team updated and enables quicker reactions to market changes. 3️⃣ Fear of Disruption and High Costs Switching to a real-time system seems expensive and risky, and firms worry about operational interruptions. 💡 Take a Phased Approach Start by moving critical risk functions like volatility-sensitive calculations or real-time exposure monitoring to real-time. This reduces disruption and shows the value of the shift. Gradually, expand real-time processing to other areas. 4️⃣ Overwhelmed by Too Much Data The sheer volume of data—market data, trades, and external feeds—can overwhelm batch systems designed for simpler data flows. 💡 Use Stream Processing Stream processing allows your system to handle data continuously, keeping your risk models updated in real-time and helping you stay on top of fast-moving markets. 5️⃣ Performance Bottlenecks During High-Volume Trading Batch systems may handle regular trading, but they slow down when trade volumes spike, leading to delays in risk calculations. 💡 Use Adaptive Scaling for Real-Time Risk To avoid slowdowns during market volatility, use adaptive scaling with cloud or distributed systems. This helps your RMS adjust to high volumes, keeping risk calculations fast and accurate even during market stress. If you have other interesting ideas, I’d love to hear them and discuss more. #RiskManagement #risk #RMS #financial #markets

Did you know that these data science scores will improve your confidence in your valuation risk analysis?  Learn How: https://lnkd.in/gNKgyMbr #valuationrisk #dataquality #decisionscience #fintech #financialindustry

Have you read PeerNova Inc's latest blog post "How These Data Science Scores Improve Confidence in Your Valuation Risk Analysis"?

Our latest insight, "Focusing Your BCBS 239 Effort: 10 Considerations in Risk and Data Compliance for Banking Leaders," is now available. This article offers a strategic look into enhancing compliance with BCBS 239 standards, addressing key areas for banking leaders to prioritize for effective risk management and data governance. Read more: https://lnkd.in/dx5hTimw

My article "Leveraging Business Intelligence Tools for Risk Analytics in the Financial Sector" has been published by internalaudit360. Big thanks to Zeynep Melisa Taşdemir, Jonathan Agius FCCA, CPA, MBA (Maastricht) Stephany Dalli FCCA, CPA, Deborah Tabone and Joseph McCafferty for their review and feedback.

How Big Data is Shaping the Future of Finance Big Data is transforming the finance industry, enabling real-time insights, predictive analytics, and enhanced risk management. Stay competitive and compliant with data-driven strategies. 📊 🔗 Read more: https://ow.ly/14sp50Trso8 #bigdata #finance #dataanalytics #fintech #riskmanagement #compliance #getondata

Navigating the complexities of risk management? Check out our latest article on how financial organizations can create consumable and explainable datasets by integrating the rigor of BCBS 239 with the flexibility of Data Mesh principles. 💡 Learn how to: - Strengthen risk data aggregation and reporting with BCBS 239 - Leverage Data Mesh's decentralized, self-serve approach to data ownership - Implement a compliant, scalable, and flexible analytics framework for risk, treasury, and trade execution #RiskManagement #DataAnalytics #BCBS239 #DataMesh #FinancialRisk Read more here👇

Data governance is not optional, it’s essential. And as you can see, having it done correctly (at any scale of organization) is critical and can look completely different depending on organizational complexity and imposed regulations. Would love to share some of our core considerations for effective governance over a quick call for anyone who needs guidance in this area.