Dual customer risk rating → triple-layer sanctions, PEP, and batch screening → fuzzy-match calibration scoring → layering typology and AMLA transaction risk scoring → ML anomaly detection and structuring pattern detection → final AML programme health scorecard. End-to-end financial crime compliance journey.
customer_risk_rating{
"jsonrpc": "2.0",
"method": "tools/call",
"params": {
"name": "customer_risk_rating",
"arguments": {}
},
"id": 1
}
check_sanctions_programme_health{
"jsonrpc": "2.0",
"method": "tools/call",
"params": {
"name": "check_sanctions_programme_health",
"arguments": {}
},
"id": 1
}
screen_sanctions_batch{
"jsonrpc": "2.0",
"method": "tools/call",
"params": {
"name": "screen_sanctions_batch",
"arguments": {}
},
"id": 1
}
score_fuzzy_match_calibration{
"jsonrpc": "2.0",
"method": "tools/call",
"params": {
"name": "score_fuzzy_match_calibration",
"arguments": {}
},
"id": 1
}
layering_typology_identifier{
"jsonrpc": "2.0",
"method": "tools/call",
"params": {
"name": "layering_typology_identifier",
"arguments": {}
},
"id": 1
}
score_aml_typologies{
"jsonrpc": "2.0",
"method": "tools/call",
"params": {
"name": "score_aml_typologies",
"arguments": {}
},
"id": 1
}
detect_timeseries_anomalies{
"jsonrpc": "2.0",
"method": "tools/call",
"params": {
"name": "detect_timeseries_anomalies",
"arguments": {}
},
"id": 1
}
check_sanctions_programme_health{
"jsonrpc": "2.0",
"method": "tools/call",
"params": {
"name": "check_sanctions_programme_health",
"arguments": {}
},
"id": 1
}