{"schema_version":1,"experiment_id":"eoa_inverse_innovation_exp04_retrieval_first_paired20_20260802","cell_id":"invariant_mode_decomposition_design__economics_finance","hypothesis_id":"H1","search_queries":["bank intraday liquidity buffer optimization eigenvalue modal analysis withdrawals collateral payments","financial institution intraday liquidity management machine learning dynamic modes buffer allocation","patent intraday liquidity risk prediction collateral payment optimization bank","bank liquidity stress testing eigenvalue spectral stability early warning","\"dynamic mode decomposition\" bank liquidity risk","principal component analysis intraday bank liquidity payment flows stress","spectral radius liquidity network bank payment system stability buffer","bank treasury intraday liquidity optimization collateral buffer software"],"sources":[{"source_id":"S1","title":"Monitoring tools for intraday liquidity management","publisher":"Basel Committee on Banking Supervision","url":"https://www.bis.org/publ/bcbs248.htm","source_class":"STANDARD","claims_supported":["BCBS established seven quantitative intraday-liquidity monitoring tools together with stress scenarios, application issues, and reporting requirements.","The standard expressly characterizes these as monitoring tools and notes that the Liquidity Coverage Ratio does not include intraday liquidity in its calibration."]},{"source_id":"S2","title":"Sound practices for intraday liquidity risk management","publisher":"European Central Bank Banking Supervision","url":"https://www.bankingsupervision.europa.eu/press/supervisory-newsletters/newsletter/2024/html/ssm.nl241113_2.en.html","source_class":"OFFICIAL_GUIDANCE","claims_supported":["The ECB states that traditional liquidity indicators do not capture intraday risk caused by payment-timing mismatches.","Observed and recommended practices include granular forecasting, real-time monitoring, automated alerts, active outflow management, collateral and contingency-resource management, and forward-looking stress tests used to quantify intraday buffers.","The ECB reports that sampled major banks already have functioning intraday-liquidity practices, although their maturity varies."]},{"source_id":"S3","title":"Real-Time Liquidity Management Solutions","publisher":"TAS Group","url":"https://www.tasgroup.eu/solutions/real-time-liquidity/real-time-liquidity-management-solutions/","source_class":"COMMERCIAL_FIRST_PARTY","claims_supported":["The product describes an integrated real-time view of cash, collateral, liquid assets, payments, and account positions, with alerting, payment throttling, and automatic replenishment.","Its BCBS 248 module runs incoming/outgoing-cash-flow stress scenarios, defines buffers by individual liquidity asset, and identifies critical counterparties and exposures.","The opened product description does not identify eigendecomposition, unstable modes, spectral gaps, or allocation according to modal loadings."]},{"source_id":"S4","title":"US20150142622A1: System and method for intraday liquidity analytics","publisher":"United States patent publication via Google Patents","url":"https://patents.google.com/patent/US20150142622A1/en","source_class":"PATENT","claims_supported":["The patent aggregates real-time liquidity and transaction data across cash, custody, repo, derivatives, securities-lending, and other financial subsystems.","It describes trend, peak-and-valley, balance, and overdraft analysis that can facilitate payment-process adjustments.","Its disclosed claims center on aggregation and graphical analysis rather than spectral stability classification or buffer allocation by eigenvector exposure."]},{"source_id":"S5","title":"Liquidity stress detection in the European banking sector","publisher":"De Nederlandsche Bank","url":"https://www.dnb.nl/en/publications/research-publications/working-paper-2019/liquidity-stress-detection-in-the-european-banking-sector/","source_class":"PRIMARY_RESEARCH","claims_supported":["The study trains supervised probabilistic classifiers on payment-system features spanning known bank-stress events.","It demonstrates an established neighboring approach for detecting bank liquidity stress from granular payment activity, but not a modal liquidity-allocation policy."]},{"source_id":"S6","title":"Early warning of systemic risk in global banking: eigen-pair R number for financial contagion and market price-based methods","publisher":"University of Essex Research Repository / Annals of Operations Research","url":"https://repository.essex.ac.uk/30689/","source_class":"PRIMARY_RESEARCH","claims_supported":["The research treats global banking-network failure as a dynamical-system stability problem and uses a spectral eigen-pair method to identify an instability tipping point.","It reports early-warning behavior and uses spectral centrality to identify systemically important and vulnerable banking systems.","Its unit of analysis is a cross-border banking network rather than a single bank-hour treasury control loop."]},{"source_id":"S7","title":"Intraday Liquidity: Risk and Regulation","publisher":"Bank of England","url":"https://www.bankofengland.co.uk/financial-stability-paper/2011/intraday-liquidity-risk-and-regulation","source_class":"GOVERNMENT_OR_REGULATOR","claims_supported":["The paper supports calibrating liquid-asset buffers against normal and stressed intraday needs.","It documents the cost-risk tradeoff and operational interventions including liquidity-saving mechanisms, throughput rules, time-varying tariffs, and collateral-eligibility policy."]}],"proximity":"ADJACENT_PRIOR_ART","closest_analogues":[{"name":"TAS BCBS 248 intraday stress-testing and buffer-definition module","similarity":"Very close operationally: it integrates payments, collateral, and liquid assets in real time, stress-tests flows, identifies critical exposures, and defines asset-level liquidity buffers.","remaining_difference":"The public description does not estimate invariant modes, classify local eigenvalue instability, or allocate buffers according to unstable-mode loadings.","source_ids":["S3"]},{"name":"Eigen-pair R-number early warning for global banking","similarity":"Very close mathematically: it uses a banking stability matrix, eigen-pair analysis, and a spectral tipping point for early warning.","remaining_difference":"It is a system-level contagion diagnostic, not a bank-hour controller that maps unstable-mode exposure loadings into contingent-liquidity allocations.","source_ids":["S6"]},{"name":"ECB sound-practice framework for intraday liquidity","similarity":"It covers the nominated problem and most workflow elements: traditional-ratio blind spots, real-time forecasts, automated alerts, stress-derived buffers, collateral resources, and active outflow management.","remaining_difference":"The guidance is method-neutral and does not prescribe a locally estimated transition operator or modal allocation rule.","source_ids":["S2"]},{"name":"Payment-feature machine-learning liquidity-stress detection","similarity":"It provides event-trained early warning from granular bank payment behavior rather than relying solely on aggregate ratios.","remaining_difference":"It outputs a stress probability rather than interpretable growing modes and does not allocate contingent liquidity to exposures loading on those modes.","source_ids":["S5"]},{"name":"BNY Mellon intraday-liquidity analytics patent","similarity":"It unifies intraday liquidity information across coupled financial subsystems and supports real-time identification of shortages and payment-process adjustment.","remaining_difference":"Its disclosed analysis is balance- and trend-based, without modal stability estimation, spectral-gap monitoring, or eigenvector-based allocation.","source_ids":["S4"]}],"overlapping_components":["Granular intraday aggregation of payments, cash, collateral, repo, margin, and securities-settlement information","Real-time bank-liquidity forecasting, monitoring, and automated alerting","Stress scenarios for coupled incoming and outgoing cash flows","Stress-based calibration of intraday liquidity buffers","Identification of critical counterparties, customers, obligations, and exposures","Active payment throttling, replenishment, collateral mobilization, and contingency-funding actions","Spectral eigen-pair instability measures as early-warning diagnostics in banking networks","Data-driven early-warning models trained on high-frequency payment features"],"remaining_contrastive_claim":"At bank-hour resolution, a locally estimated withdrawal–collateral–payment transition operator can support a closed-loop policy that allocates contingent liquidity by exposure loading on unstable modes and triggers at least one business day earlier than standard ratio thresholds without raising false alarms by more than 10%.","claim_falsifier":"The claim would be falsified by a representative retrospective stress-event benchmark in which the specified modal allocation policy fails either the one-business-day lead requirement or the 10% false-alarm bound, or by pre-existing direct documentation of the same bank-hour eigensystem-to-buffer-allocation loop.","problem_support":"STRONG","recommendation":"RESEARCH","world_novelty_boundary":"Across eight targeted searches and seven opened standards, regulatory, research, commercial, and patent sources, no direct match was found for the complete bank-hour loop of local transition-operator estimation, unstable-mode classification, exposure-loading sensitivity, and contingent-liquidity allocation; this is only a bounded public-web result, and proprietary bank models, vendor internals, unpublished studies, and unindexed patents remain outside the evidence boundary."}