Opensee ranked #1 for Risk Data Aggregation in Chartis RiskTech Quadrant for Market Risk Solutions

Opensee has once again been recognized as a Category Leader in the Chartis RiskTech Quadrant® for Market Risk Solutions for Risk Data Aggregation, achieving the highest completeness of offering score among all vendors in the category leader quadrant. The ranking reflects our high scores across the capabilities evaluated: Scalability, Data Type Coverage, Data Management, Packaging/UX, and Tools/Frameworks.

What Drives Opensee's Leadership

Risk data aggregation is at the core of Opensee. The platform is 100% designed for financial institutions, giving risk managers and front office teams a fundamentally new way to work with risk, finance, and trade data by combining ultra‑fast aggregation with true large‑scale, long‑history storage, instead of forcing a trade‑off between speed, detail, and retention. Opensee is designed to handle billions of rows over many years, while still responding in seconds. This means that metrics such as VaR, FRTB (SA and IMA), P&L explain, stress tests, and liquidity indicators can be recalculated and explored interactively, even during periods of market volatility when positions, scenarios, and regulatory demands are all changing at once.

At the heart of this capability is Opensee’s semantic layer that unifies positions, P&L vectors, sensitivities, and simulation paths (subject to the use case) coming from existing risk engines and trading systems into a single, logical, and coherent model - fast, reliable answers grounded in your data. Models can evolve on the fly without data re-ingestion, and consistency is maintained across all interfaces, whether users access data through Agensee (our agentic layer), Opensee’s UI, Excel, other BI tools, or programmatically. The same layer enables rapid adaptation to regulatory changes.

The underlying architecture is disk-based, cloud-agnostic, and built for scale. Opensee leverages a Massively Parallel Processing (MPP) OLAP engine and is deployable on AWS, Azure, GCP, on-premise, or hybrid environments. It supports billions of rows and high-concurrency workloads with sub-second query response, delivering infrastructure costs up to 90% lower than in-memory solutions. This scalability is especially valuable for regulatory and internal risk use cases. Opensee is built to support high‑volume calculations enabling users to run what‑if analyses or full replays over long histories without resorting to data sampling or offline processes. Because the platform keeps a full versioned history of the data, every number is fully explainable and auditable, which is essential for management, regulators, and internal model validation. Users implement custom aggregation logic using Python UDFs for both linear and non-linear calculations, all fully auditable and extensible. 

AI capabilities are embedded across the platform through Agensee, the agentic intelligence layer of Opensee, which sits directly on top of this semantic and technical backbone. Purpose-built for financial institutions and for any risk, finance, and trade analytics domain, Agensee is designed from the ground up for regulated environments. Every action it takes is transparent, auditable, and reversible. Every query to your data is live, not pre-calculated. And every result, whether a chart, a finding, or a full report, is explainable. Backend intelligence includes symbolic AI for root-cause analysis, neural proxy pricing for data gaps or error corrections, and ML-driven anomaly detection. Agensee extends the platform from low-code to no-code. But it goes further and allows the automation of complex tasks typically taking hours from dozens of people every day. Using your instructions and ways of operating, translated into “skills”, it runs data quality checks, corrects errors, provides full explainability, and produces complete reports ready to be distributed.  

Proven at Scale Across Leading Financial Institutions

Opensee is trusted by leading financial institutions, from GSIBs to regional banks, asset managers, and hedge funds. For these institutions, Opensee serves as the core aggregation and analytics engine for market risk, credit risk, liquidity risk, structural risk, and more generally as an explainability engine for internal and regulatory reporting. Opensee has also won "Best Risk Data Aggregation Initiative" for four consecutive years and received recognition from Chartis for Best Use of AI for Risk Data.

Our platform continues to expand across the global banking landscape. Most recently, KBC selected Opensee to jointly drive next-generation market risk and counterparty credit risk aggregation, analytics, and reporting. Learn more here.

To see our ultra-fast aggregation engine behind these deployments, watch our on-demand webinar, Aggregation at Scale and Millisecond VaR: Fast, Accurate, Explainable.

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