Clearwater Analytics Embeds AI into Beacon Risk Platform to Accelerate Model Validation and Exposure Analysis

Key Terms

tail risk modeling financial

Tail risk modeling is the practice of estimating the chance and potential size of rare, extreme losses at the far end of an investment’s risk distribution — like planning for an unusually severe storm rather than everyday weather. It matters to investors because it helps quantify worst-case scenarios, set appropriate reserves or hedges, and design portfolio safeguards so a single rare event doesn’t wipe out gains built over many years.

value at risk (var) financial

Value at risk (VaR) is a statistical estimate of the maximum potential loss an investment or portfolio could face over a set time period, given a specific probability level (for example, 95% or 99%). Think of it as the size of the storm you would expect to survive most of the time; it matters to investors because it summarizes downside exposure in a single number for setting risk limits, sizing capital, and comparing strategies, while not guaranteeing actual losses won’t be larger.

credit risk financial

Credit risk is the chance that a borrower or debt issuer will fail to make agreed interest or principal payments, leaving lenders or bondholders with reduced or lost money. For investors it matters because higher credit risk usually means higher expected returns to compensate for that danger, greater chance of losses or sudden drops in market value, and more scrutiny of ratings and cash-flow strength—like lending a friend money and weighing the odds they'll pay you back.

stress tests financial

Stress tests are simulated scenarios that check how a bank, insurer or other financial institution would handle extreme but plausible shocks—like a deep recession, market crash or sudden rise in loan losses. They matter to investors because they reveal whether a firm has enough capital and risk controls to survive bad times, similar to checking a bridge’s strength under heavy traffic before trusting it with commuters.

agentic ai technical

Agentic AI refers to computer systems that can make their own decisions and take actions without needing someone to tell them what to do each time. It's like giving a robot a degree of independence to solve problems or achieve goals on its own, which matters because it could change how we work and interact with technology in everyday life.

cloud-native architecture technical

Cloud-native architecture is a way of building and running software so applications are made from small, independent pieces that run in the cloud rather than on a single physical server—think of it like a set of LEGO blocks that can be rearranged, repaired, or scaled on demand. For investors, this matters because it usually enables faster product updates, lower infrastructure costs, and better ability to handle spikes in demand, which can improve a company’s growth prospects, reliability, and profit margins.

regulatory reporting regulatory

Regulatory reporting is the regular submission of financial, operational and compliance information that companies must provide to government agencies and industry regulators. It matters to investors because these filings act like a company’s inspection and service records—revealing financial health, legal risks and accuracy of management’s claims—so late, missing or troubling reports can signal problems, trigger fines, or change a company’s value.

real-time calculations technical

Continuous computer-driven number crunching that updates prices, risk measures, valuations and other financial metrics the moment new data arrives. Like a GPS recalculating your route as traffic changes, these calculations give investors up-to-the-second information needed to place trades, manage exposure and spot problems before they grow. Faster, accurate updates matter because delays can change the value of a decision or leave risk unnoticed.

Production-grade AI transforms quantitative workflows—from scenario analysis to tail risk modeling—inside investment risk operations engine

BOISE, Idaho & CHICAGO & NEW YORK & LONDON & HONG KONG--(BUSINESS WIRE)-- Clearwater Analytics (NYSE: CWAN), the most comprehensive technology platform for investment management, today announced breakthrough embedded agentic AI capabilities within Beacon by CWAN, its enterprise risk and quantitative analytics platform, enabling risk teams to accelerate model validation, exposure analysis, and decision-making.

As regulatory scrutiny intensifies and portfolio complexity reaches unprecedented levels, traditional risk platforms are failing institutional investors when they need answers most. Built specifically for quantitative developers and risk professionals managing complex institutional portfolios, CWAN’s embedded AI operates within Beacon’s calculation engine itself, training the agents our clients deploy on data grounded in a firm’s actual positions, validated models, and real-time calculations.

This breakthrough architecture processes live positions and validated models in real-time, eliminating the manual export, analysis, and re-input cycles that plague traditional solutions. The result: continuous AI-powered risk analysis that scales from individual trades to enterprise-wide exposures, enabling teams to validate assumptions, stress test portfolios, and explain exposures to stakeholders without leaving their core risk modeling environment.

With these new capabilities that transform institutional risk operations, clients can conduct:

• Model validation at lightning speed: Validate VaR models, credit risk frameworks, and custom analytics against multiple instrument types and market scenarios reducing validation from weeks to hours. Generate model documentation adapted for different audiences ranging from technical validation reports for quants to executive summaries for CROs, while maintaining full audit trails and assumption transparency.

• Instant exposure intelligence and scenario analysis: Break down portfolio risk instantly by currency, tenor, asset type, rating, strategy, or any custom dimension. Run “what-if” scenarios and stress tests with natural language queries, then drill down to underlying positions and sensitivity drivers on demand. All outputs trace directly back to Beacon’s calculation engine.

• Operationalized risk workflows: Deploy specialized AI agents for recurring tasks such as limits monitoring, regulatory reporting preparation, tail risk analysis, and cross-portfolio exposure aggregation. These agents execute multi-step processes end-to-end within Beacon’s governed environment, not just generating suggestions, but completing workflows that previously required manual coordination across teams.

“Risk management requires precise and deterministic models. Our risk architecture and APIs are designed with AI in mind to enable agentic workflows and explainability to allow you to trace the analysis back to underlying positions and validation models,” said Kirat Singh, President, Risk & Alternative Assets at Clearwater Analytics. “The extensible nature of our platform allows you to create your own agents, tools and workflows leveraging our powerful cross asset risk analytics.”

Enterprise-grade security and governance meet AI capabilities

The embedded AI capabilities operate entirely within each customer’s cloud environment, ensuring bank-grade security and complete data isolation. CWAN’s architecture enables quantitative teams to build validated agentic workflows once and deploy them across the organization. Traders can query exposures in real time, risk managers can generate scenario analyses for committees, and operations teams can automate recurring reports.

“This release extends CWAN’s broader AI platform strategy announced in November of 2025, which made 800+ AI agents available for deployment across more than $10 trillion in client assets,” added Singh. “Within 24 months, AI-native risk platforms will be table stakes for institutional investors. We’re rearchitecting that future with AI embedded into risk, institutional-grade governance, and a cloud-native architecture that delivers real-time insights across the entire investment lifecycle.”

To learn more about Beacon by CWAN, speak to an expert today.

About CWAN

Clearwater Analytics (NYSE: CWAN) is transforming investment management with the industry’s most comprehensive cloud-native platform for institutional investors across global public and private markets. While legacy systems create risk, inefficiency, and data fragmentation, CWAN’s single-instance, multi-tenant architecture delivers real-time data and AI-driven insights throughout the investment lifecycle. The platform eliminates information silos by integrating portfolio management, trading, investment accounting, reconciliation, regulatory reporting, performance, compliance, and risk analytics in one unified system. Serving leading insurers, asset managers, hedge funds, banks, corporations, and governments, CWAN supports over $10 trillion in assets globally. Learn more at www.cwan.com.

View source version on businesswire.com: https://www.businesswire.com/news/home/20260127075319/en/

Media Contact:
Claudia Cahill, Head of Communications and PR | +1 208-433-1200 | press@cwan.com

Source: Clearwater Analytics