{"id":"W7106850773","doi":"10.34989/swp-2025-35","title":"AI Agents for Cash Management in Payment Systems","year":2025,"lang":"en","type":"article","venue":"Bank of Canada Research","topic":"FinTech, Crowdfunding, Digital Finance","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bank of Canada","funders":"","keywords":"Market liquidity; Payment; Settlement (finance); Cash; Liquidity risk; Payment system; Key (lock); Liquidity crisis","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004554546,0.0006271151,0.0004293128,0.0003446119,0.0008917758,0.001995911,0.001715991,0.001615626,0.006568461],"category_scores_gemma":[0.01999496,0.0003897841,0.0004849822,0.000317124,0.001540214,0.002528461,0.001484385,0.002651947,0.000847529],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002087527,"about_ca_system_score_gemma":0.002200753,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01018374,"about_ca_topic_score_gemma":0.008293257,"domain_scores_codex":[0.9977068,0.001524571,0.0001148767,0.0002542114,0.0002829876,0.0001166132],"domain_scores_gemma":[0.9853637,0.01209903,0.0005683628,0.0009374965,0.0005987927,0.000432519],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002217316,0.001839879,0.01154807,0.0007587163,0.000178366,0.00054604,0.004289495,0.7071108,0.02532506,0.09923971,0.009223385,0.1377231],"study_design_scores_gemma":[0.0002063201,0.000223429,0.000577486,0.00002901924,0.00003046781,0.00005238819,0.0002630171,0.9645824,0.003751183,0.02525679,0.004996331,0.00003110663],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5043251,0.0003616449,0.4595669,0.003551153,0.0002418236,0.001164266,0.0004681733,0.007618593,0.02270233],"genre_scores_gemma":[0.8670132,0.0001013693,0.1292964,0.0004975246,0.00001946816,0.0002993943,0.0002152777,0.000103066,0.00245437],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01018374,"threshold_uncertainty_score":0.02408701,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05004276844047445,"score_gpt":0.3308811157710443,"score_spread":0.2808383473305699,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}