In today’s financial landscape, institutions are under increasing pressure to manage risk with agility, transparency, and precision. Regulatory demands, operational complexity, and fragmented systems often hinder the ability to respond quickly and confidently. The SAS Risk Cirrus platform, built on SAS Viya, offers a transformative solution—combining cloud-native architecture, low-code configurability, and integrated analytics to modernize risk management across domains. In this post I am going to examine a few risk related issues and how using SAS Risk solutions can minimize your risk positions.
Examining SAS Model Risk Management
SAS Model Risk Management offers a comprehensive framework for governing the entire lifecycle of models—from development and validation to deployment and retirement. It centralizes model inventory, enforces audit-ready documentation, and supports regulatory compliance with standards like SR 11-7 and OCC guidelines. The platform’s low-code configurability through SAS Cirrus allows users to tailor workflows and interfaces without developer support, while automated workflows streamline approvals and validations. Integrated analytics and dashboards provide real-time visibility into model performance, risk exposure, and governance status, enabling institutions to respond confidently to audits and regulatory inquiries.
Beyond compliance and operational efficiency, SAS MRM enhances collaboration across risk, compliance, and business teams. It supports models built in any language or platform, ensuring flexibility and integration with existing systems. Data integrity is maintained through guided entry and embedded validation checks, while role-based access controls protect sensitive information. The solution empowers organizations to reduce manual effort, improve transparency, and accelerate decision-making, making it a strategic asset for modern risk governance.
Case Study - A multinational bank faced significant challenges in managing its model inventory. Models were scattered across departments, with inconsistent validation practices and limited visibility into lifecycle status. Documentation was often incomplete, and audit readiness was a persistent concern. Teams lacked the tools to customize workflows without developer support, leading to delays and inefficiencies.
Result - By implementing SAS Model Risk Management on SAS Cirrus, the bank centralized its model governance. These tools allowed administrators to configure workflows, page layouts, and field behaviors without writing code, while SAS Workflow Manager automated validation and approval processes.
Key benefits included:
A 67% reduction in validation cycle time.
Full traceability and audit readiness across 100% of models.
A 40% decrease in time spent on manual documentation and approvals.
The solution also improved regulatory compliance and internal transparency. Teams could trace model lineage, monitor performance metrics, and respond to audit requests with confidence.
Examining SAS Stress Testing for Banking
The SAS Stress Testing solution is a comprehensive, cloud-native platform designed to help financial institutions meet regulatory and internal stress testing requirements with speed, transparency, and precision. Built on SAS Cirrus on Viya, it enables organizations to simulate adverse economic scenarios across credit, market, and liquidity risk dimensions. The solution supports a full cycle of stress testing activities—from data ingestion and quality checks to scenario modeling, model execution, and results aggregation. Its in-memory processing and distributed computing architecture allow for high-performance simulations, while its intuitive interface and prebuilt workflows streamline collaboration across risk, finance, and technology teams. Institutions can configure business evolution plans, define segmentation schemes, and apply rule-based adjustments to stress outputs, ensuring both flexibility and control throughout the process.
Beyond compliance, SAS Stress Testing transforms stress testing into a strategic planning tool. It offers centralized orchestration and governance, enabling users to manage multiple stress tests simultaneously and monitor progress in real time. The solution’s robust data management framework ensures auditability and traceability by storing all data versions and interim outcomes. With prebuilt model templates and customizable reporting dashboards, institutions can reduce cycle times, improve operational efficiency, and deepen their analysis across a broader range of scenarios. By integrating with SAS Model Risk Management and other risk solutions, SAS Stress Testing supports enterprise-wide risk alignment and empowers decision-makers to proactively manage capital, liquidity, and portfolio resilience
Case Study - A regional bank struggled to meet IFRS 9 and CECL stress testing requirements due to siloed data systems and rigid scenario modeling tools. Analysts spent over 60% of their time preparing and reconciling data, while simulations took days to complete. Deployment was further complicated by inconsistent documentation and configuration errors.
Results - SAS Stress Testing on Cirrus addressed these issues by integrating the SAS Allowance for Credit Loss and SAS Scenario Manager. The platform supported dynamic scenario modeling, master scenario reuse, and automated batch execution. Git-integrated promotion pipelines streamlined deployment across environments.
Benefits realized:
Scenario execution time dropped from three days to under 45 minutes.
Over 1,200 analyst hours saved annually.
Full compliance with IFRS 9 and CECL, supported by versioned scenario histories and audit-ready documentation.
Teams could collaborate more effectively, and risk managers gained the agility to respond to regulatory changes with minimal disruption.
Examining SAS Dynamic Actuarial Modeling for Insurance
SAS Dynamic Actuarial Modeling is a comprehensive, cloud-native solution designed to modernize and streamline the end-to-end actuarial modeling lifecycle. Built on SAS Cirrus on Viya, SAS DAM empowers insurers to automate premium modeling, optimize pricing strategies, and improve decision-making across underwriting, renewals, and portfolio management. The solution integrates advanced analytics, machine learning, and decisioning tools—such as SAS Model Studio, SAS Visual Analytics, and SAS Intelligent Decisioning—to support both traditional and AI-driven actuarial workflows. It enables actuaries to build, test, and deploy models with greater speed and transparency, while maintaining full traceability and governance. With support for open-source integration and explainable ML models, SAS DAM makes sophisticated modeling accessible to actuarial teams without requiring deep programming expertise.
Beyond modeling, SAS DAM enhances operational efficiency and business agility. It reduces time-to-market for new pricing models through automated data preparation, rule-based rate adjustments, and simulation capabilities. The solution’s renewal optimization workflow helps insurers balance profitability and retention by analyzing customer behavior and adjusting premiums accordingly. SAS DAM also supports regulatory compliance by providing audit-ready documentation and firm-wide reporting. By minimizing data redundancies and enabling real-time scenario testing, SAS DAM equips insurers to respond quickly to market changes and maintain competitive advantage in an increasingly dynamic insurance landscape.
Case Study - An insurance provider faced mounting pressure to comply with IFRS 17 and Solvency II while modernizing its actuarial modeling. Existing tools were disconnected, requiring manual validation of hundreds of rules and limiting the use of machine learning. Pricing analysts were burdened by slow deployment cycles and lacked visibility into model performance.
Result - With SAS Dynamic Actuarial Modeling on Cirrus, the insurer unified its modeling, reporting, and compliance workflows. SAS Model Studio and SAS Visual Analytics integrated seamlessly with SAS DAM, enabling end-to-end automation.
The solution delivered:
A 90% acceleration in model deployment time (from four weeks to three days).
An 18% improvement in forecast accuracy.
A 75% reduction in compliance review time through automated rule validations.
Executives gained real-time visibility into capital adequacy and reserve trends, empowering strategic decision-making and improving stakeholder confidence.
Putting it all together with an Integrated Balance Sheet Management (IBSM)
SAS Risk Cirrus also supports Integrated Balance Sheet Management by aligning risk, finance, and treasury functions within a unified data and analytics environment. Institutions can simulate macroeconomic shocks across earnings, capital, and liquidity dimensions, using shared data models and scenario planning tools.
Benefits of SAS Cirrus for IBSM include:
Unified integration of ALM, FTP, liquidity risk, and capital planning.
Real-time analytics for optimizing net interest income, economic value of equity, and liquidity coverage ratios.
Modular scalability with seamless connections to SAS ALM, FTP, and Capital Planning solutions.
One global bank reported a 22% improvement in capital efficiency and a 30% reduction in liquidity buffer requirements after adopting SAS Cirrus for IBSM.
SAS Risk Cirrus is more than a platform—it’s a strategic enabler. Whether managing model risk, executing stress tests, modernizing actuarial workflows, or optimizing balance sheet performance, SAS Cirrus delivers the agility, transparency, and scalability needed to thrive in today’s risk environment.
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