Liquidity risk & ALM analytics without blindspots
Monitor, stress test, and explain intraday and structural liquidity across entities and desks - covering cash flow management, regulatory (EBA LCR, NSFR, PRA110, FED FR2052a...) and internal liquidity metrics on a single, transparent platform.
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Why global and regional banks choose Opensee for liquidity risk analytics
Key capabilities of Opensee for liquidity risk analytics
Single liquidity data hub across entities & desks
Ingest and centralize contractual and behavioral cash flows, positions, funding instruments, and reference data across banking and trading books. Aggregate and analyze liquidity exposures by legal entity, branch, business line, desk, product, or currency, with full drill-down to individual transactions and cash flow projections.
Ingestion of contractual and behavioral cash flows for all relevant products
Coverage of loans, deposits, securities, repos, derivatives, and off-balance sheet items
Consistent views across treasury, risk, finance, and regulatory reporting
Multi-entity, multi-currency, multi-book aggregation with versioning and audit trails
Transparent regulatory and internal liquidity calculations
Calculate, monitor, and explain key regulatory liquidity metrics such as LCR, NSFR, and PRA110, alongside internal liquidity indicators used for ALM and risk management. Opensee provides full transparency from reported ratios down to underlying cash flows and assumptions.
Native LCR and NSFR calculations with configurable run-off factors and haircuts
PRA110 and jurisdiction-specific adaptation with evolving data model
Internal liquidity metrics (cumulative gaps, survival horizons, concentration measures, HQLA composition)
Drill-down from ratios and KPIs to positions, instruments, and projected flows
Liquidity stress testing across time horizons
Define and run regulatory and internal liquidity stress scenarios—market-wide shocks, funding stresses, name-specific events, or intraday cash disruptions—and assess their impact on cash flow gaps, liquidity buffers, and regulatory ratios across entities and currencies.
Apply regulatory and internal stress scenarios
Customize scenarios by entity, business line, currency, or product
Visualize impacts on gaps, buffers, and liquidity ratios
Scenario comparison with drill-down to affected instruments and cash flows
AI-driven liquidity data quality and controls
Combine rule-based controls and statistical analysis to identify data quality issues and abnormal movements in liquidity metrics. Visual indicators and alerts allow treasury and risk teams to investigate anomalies and validate data before it is used for regulatory reporting, internal governance, or management decisions.
Automated completeness, consistency, and business checks on incoming data
Statistical outlier detection in cash flows, balances, and liquidity metrics
Workflows for investigation, adjustment, and sign-off
Visual alerts for significant changes in LCR, NSFR, gaps, and internal indicators
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