{"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 allocation optimization eigenvalue modal stability","bank liquidity risk early warning principal components eigenvalues deposit outflows collateral haircuts","financial network spectral radius liquidity contagion early warning eigenvalue banks","patent intraday liquidity risk monitoring buffer allocation bank payments","\"intraday liquidity\" \"principal component\" bank payments","\"liquidity buffer\" allocation bank stress testing optimization collateral payments","site:bok.or.kr \"Network Indicators for Monitoring Intraday Liquidity in BOK-Wire+\"","site:bankingsupervision.europa.eu \"Sound practices for intraday liquidity risk management\""],"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":["Basel establishes quantitative monitoring tools and stress scenarios for banks' intraday liquidity risk.","The framework covers payment obligations, available intraday liquidity and collateral but does not specify eigendecomposition or allocation by unstable-mode loadings."]},{"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":["ECB reports that conventional start- and end-of-day liquidity indicators can miss material intraday risk.","Its review supports real-time monitoring, stress testing, automated alerts and management of interacting payment, collateral and funding drivers, without describing an eigenmode-based allocation rule."]},{"source_id":"S3","title":"Internal Liquidity Adequacy Assessment Process for Deposit-Taking Institutions – Guideline (2027)","publisher":"Office of the Superintendent of Financial Institutions Canada","url":"https://www.osfi-bsif.gc.ca/en/guidance/guidance-library/internal-liquidity-adequacy-assessment-process-ilaap-deposit-taking-institutions-guideline-2027","source_class":"OFFICIAL_GUIDANCE","claims_supported":["OSFI directs institutions to assess intraday payment timing, client flows, securities settlement, collateral requirements and stressed haircuts at granular account, currency and business-unit levels.","It expressly connects intraday stress-test results to buffer calibration, exposure limits, escalation triggers and remediation, but does not prescribe spectral modes or eigenvector-weighted buffer allocation."]},{"source_id":"S4","title":"Early warning of systemic risk in global banking: eigen-pair R number for financial contagion and market price-based methods","publisher":"Annals of Operations Research / IDEAS-RePEc","url":"https://ideas.repec.org/a/spr/annopr/v330y2023i1d10.1007_s10479-021-04120-1.html","source_class":"PRIMARY_RESEARCH","claims_supported":["The paper treats banking-network failure as a dynamical-stability problem and uses a spectral eigen-pair measure to identify a tipping point and vulnerable banking systems.","Its operator is a cross-border bilateral-exposure network and its intervention context is systemic oversight, not hourly allocation of one bank's contingent liquidity."]},{"source_id":"S5","title":"Network Indicators for Monitoring Intraday Liquidity in BOK-Wire+","publisher":"Bank of Korea","url":"https://www.bok.or.kr/imerEng/bbs/E0002902/view.do?menuNo=600342&nttId=197455&pageIndex=20&type=List","source_class":"PRIMARY_RESEARCH","claims_supported":["The study combines payment-network analysis with continuously updated estimates of banks' remaining expected payment inflows, outflows and liquidity requirements.","It provides institution-level intraday early-warning and systemic-importance indicators, but not a local transition-operator stability classification or modal buffer-allocation policy."]},{"source_id":"S6","title":"Estimating Financial Institutions’ Intraday Liquidity Risk: A Monte Carlo Simulation Approach","publisher":"Banco de la República","url":"https://www.banrep.gov.co/es/publicaciones-investigaciones/borradores-economia/estimating-financial-institutions-intraday-liquidity","source_class":"PRIMARY_RESEARCH","claims_supported":["The paper simulates minute-by-minute payment arrivals and timing mismatches to identify non-resilient institutions and estimate intraday liquidity buffers.","It establishes dynamic, institution-specific buffer estimation as prior practice, but uses a stochastic payment model rather than unstable eigenmodes spanning withdrawals, collateral haircuts and obligations."]},{"source_id":"S7","title":"US20260038047A1 — Systems and methods for liquidity matching","publisher":"JPMorgan Chase Bank, N.A. / Google Patents","url":"https://patents.google.com/patent/US20260038047A1/en","source_class":"COMMERCIAL_FIRST_PARTY","claims_supported":["The patent describes liquidity snapshots, graph representations, thresholds and minimum-cost maximum-flow optimization for real-time funding and reallocation across accounts and credit facilities.","It overlaps operational liquidity allocation and graph-based decision automation, but addresses client funds control and balance sharing rather than bank-run instability or eigenmode loadings."]}],"proximity":"ADJACENT_PRIOR_ART","closest_analogues":[{"name":"Spectral eigen-pair early warning for banking-network instability","similarity":"Uses a banking-state operator, dominant eigen-pair and stability threshold to detect amplification and identify vulnerable components before conventional market indicators.","remaining_difference":"It operates across banking systems using bilateral exposures and capital thresholds, not within one bank at bank-hour resolution, and does not allocate contingent liquidity to withdrawal-collateral-payment exposures by mode loading.","source_ids":["S4"]},{"name":"Stress-driven intraday buffer calibration and granular exposure limits","similarity":"Official practice already links real-time intraday monitoring and multi-driver stress tests to buffer calibration, limits, triggers and remediation.","remaining_difference":"The located guidance uses scenarios, flows and limits rather than estimating a local transition operator, partitioning stable and unstable modes, and steering buffers by eigenvector composition.","source_ids":["S1","S2","S3"]},{"name":"Continuous payment-network and Monte Carlo intraday-liquidity indicators","similarity":"Existing research forecasts remaining intraday inflows and outflows, detects non-resilient institutions and estimates institution-specific liquidity needs or buffers.","remaining_difference":"These methods model payment timing and network position without the nominated coupled state of depositor withdrawals, collateral haircuts and payment obligations or a modal intervention map.","source_ids":["S5","S6"]},{"name":"Graph-optimized real-time liquidity matching","similarity":"Implements live liquidity snapshots and algorithmic allocation of liquidity across accounts, facilities and payment requests under limits and priorities.","remaining_difference":"Its optimization is funds-control and minimum-cost-flow matching, not instability detection from eigenvalues or allocation according to unstable eigenvector loadings.","source_ids":["S7"]}],"overlapping_components":["Granular intraday state and liquidity-source monitoring","Payment-flow and network representations","Stress scenarios combining funding, payment and collateral drivers","Forecasting of remaining intraday inflows and outflows","Dynamic early-warning indicators and escalation thresholds","Intraday liquidity-buffer estimation and calibration","Exposure limits and contingent management actions","Graph-based operational liquidity allocation","Spectral stability measures for banking contagion"],"remaining_contrastive_claim":"The remaining distinction is a validated single-bank policy that repeatedly estimates a bank-hour transition operator over depositor outflows, collateral haircuts and payment obligations, detects locally unstable eigenmodes, and allocates contingent liquidity to exposures in proportion to their modal loadings while satisfying the stated lead-time and false-alarm benchmark.","claim_falsifier":"The contrastive claim would be falsified by a pre-existing bank deployment, research paper, patent or supervisory case study that performs that same bank-hour eigenmode estimation and eigenvector-loading-based liquidity allocation, or by retrospective tests showing it cannot trigger one business day earlier than standard ratios without increasing false alarms by more than 10%.","problem_support":"STRONG","recommendation":"RESEARCH","world_novelty_boundary":"This was a bounded ordinary-web search across standards, official guidance, research and patents; it does not establish, imply or support a world-novelty conclusion, and undisclosed bank practices, non-indexed patents, proprietary treasury systems or differently named methods may contain a closer match."}