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feat(aml): ML-based false positive reduction (#394) #446

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152 changes: 152 additions & 0 deletions migrations/20270527000000_aml_ml_optimization.sql
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-- Migration: AML ML Optimization Layer — Issue #394
-- Tables for model versioning, training samples, shadow evaluations, and drift metrics

-- ---------------------------------------------------------------------------
-- Model versions (champion/challenger registry)
-- ---------------------------------------------------------------------------
CREATE TABLE IF NOT EXISTS aml_model_versions (
model_id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
version INTEGER NOT NULL,
weights_json JSONB NOT NULL, -- [f64; 10] weight array
bias DOUBLE PRECISION NOT NULL DEFAULT 0.0,
trained_at TIMESTAMPTZ NOT NULL DEFAULT NOW(),
training_samples BIGINT NOT NULL DEFAULT 0,
validation_precision DOUBLE PRECISION NOT NULL DEFAULT 0.0,
validation_recall DOUBLE PRECISION NOT NULL DEFAULT 0.0,
fp_rate DOUBLE PRECISION NOT NULL DEFAULT 0.0,
is_champion BOOLEAN NOT NULL DEFAULT false,
created_at TIMESTAMPTZ NOT NULL DEFAULT NOW()
);

-- Only one champion at a time
CREATE UNIQUE INDEX IF NOT EXISTS idx_aml_model_versions_champion
ON aml_model_versions (is_champion)
WHERE is_champion = true;

CREATE INDEX IF NOT EXISTS idx_aml_model_versions_version
ON aml_model_versions (version DESC);

-- Seed the default model (prior weights) so the system starts with a champion
INSERT INTO aml_model_versions
(model_id, version, weights_json, bias, training_samples,
validation_precision, validation_recall, fp_rate, is_champion)
VALUES (
gen_random_uuid(),
0,
'[-0.8, -0.6, -0.7, -0.3, 0.5, 0.6, 0.4, 0.9, 0.5, -0.9]'::jsonb,
0.0,
0,
0.0,
0.0,
0.0,
true
)
ON CONFLICT DO NOTHING;

-- ---------------------------------------------------------------------------
-- Training samples — labeled analyst decisions
-- ---------------------------------------------------------------------------
CREATE TABLE IF NOT EXISTS aml_training_samples (
sample_id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
alert_id UUID NOT NULL,
-- Feature columns (normalised 0.0–1.0)
velocity_24h DOUBLE PRECISION NOT NULL,
velocity_7d DOUBLE PRECISION NOT NULL,
amount_ratio_30d DOUBLE PRECISION NOT NULL,
counterparty_diversity DOUBLE PRECISION NOT NULL,
known_counterparty_ratio DOUBLE PRECISION NOT NULL,
kyc_tier_score DOUBLE PRECISION NOT NULL,
account_age_score DOUBLE PRECISION NOT NULL,
historical_fp_rate DOUBLE PRECISION NOT NULL,
geo_consistency DOUBLE PRECISION NOT NULL,
corridor_risk DOUBLE PRECISION NOT NULL,
-- Label
is_false_positive BOOLEAN NOT NULL,
analyst_id UUID NOT NULL,
resolved_at TIMESTAMPTZ NOT NULL DEFAULT NOW(),
created_at TIMESTAMPTZ NOT NULL DEFAULT NOW()
);

CREATE INDEX IF NOT EXISTS idx_aml_training_samples_resolved_at
ON aml_training_samples (resolved_at ASC);

CREATE INDEX IF NOT EXISTS idx_aml_training_samples_alert_id
ON aml_training_samples (alert_id);

-- ---------------------------------------------------------------------------
-- Shadow evaluations — champion vs challenger comparison
-- ---------------------------------------------------------------------------
CREATE TABLE IF NOT EXISTS aml_shadow_evaluations (
eval_id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
alert_id UUID NOT NULL,
champion_model_id UUID NOT NULL REFERENCES aml_model_versions(model_id),
challenger_model_id UUID NOT NULL REFERENCES aml_model_versions(model_id),
champion_fp_probability DOUBLE PRECISION NOT NULL,
challenger_fp_probability DOUBLE PRECISION NOT NULL,
champion_recommendation TEXT NOT NULL CHECK (champion_recommendation IN ('Suppress', 'Downgrade', 'Retain')),
challenger_recommendation TEXT NOT NULL CHECK (challenger_recommendation IN ('Suppress', 'Downgrade', 'Retain')),
-- Filled in when analyst resolves the alert
analyst_confirmed_fp BOOLEAN,
evaluated_at TIMESTAMPTZ NOT NULL DEFAULT NOW(),
UNIQUE (alert_id, challenger_model_id)
);

CREATE INDEX IF NOT EXISTS idx_aml_shadow_evals_challenger
ON aml_shadow_evaluations (challenger_model_id, evaluated_at DESC);

CREATE INDEX IF NOT EXISTS idx_aml_shadow_evals_champion
ON aml_shadow_evaluations (champion_model_id, evaluated_at DESC);

CREATE INDEX IF NOT EXISTS idx_aml_shadow_evals_feedback
ON aml_shadow_evaluations (analyst_confirmed_fp)
WHERE analyst_confirmed_fp IS NOT NULL;

-- ---------------------------------------------------------------------------
-- Drift metrics — periodic PSI and accuracy checks
-- ---------------------------------------------------------------------------
CREATE TABLE IF NOT EXISTS aml_drift_metrics (
metric_id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
model_id UUID NOT NULL REFERENCES aml_model_versions(model_id),
checked_at TIMESTAMPTZ NOT NULL DEFAULT NOW(),
max_psi DOUBLE PRECISION NOT NULL,
critical_features_json JSONB NOT NULL DEFAULT '[]'::JSONB,
current_precision DOUBLE PRECISION NOT NULL,
current_recall DOUBLE PRECISION NOT NULL,
precision_drop DOUBLE PRECISION NOT NULL DEFAULT 0.0,
recall_drop DOUBLE PRECISION NOT NULL DEFAULT 0.0,
alert_triggered BOOLEAN NOT NULL DEFAULT false
);

CREATE INDEX IF NOT EXISTS idx_aml_drift_metrics_model
ON aml_drift_metrics (model_id, checked_at DESC);

CREATE INDEX IF NOT EXISTS idx_aml_drift_metrics_alerts
ON aml_drift_metrics (alert_triggered, checked_at DESC)
WHERE alert_triggered = true;

-- ---------------------------------------------------------------------------
-- ML scoring audit log — every suppression/downgrade must be auditable
-- ---------------------------------------------------------------------------
CREATE TABLE IF NOT EXISTS aml_ml_scoring_audit (
audit_id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
alert_id UUID NOT NULL,
model_id UUID NOT NULL REFERENCES aml_model_versions(model_id),
model_version INTEGER NOT NULL,
fp_probability DOUBLE PRECISION NOT NULL,
recommendation TEXT NOT NULL CHECK (recommendation IN ('Suppress', 'Downgrade', 'Retain')),
attributions_json JSONB NOT NULL, -- SHAP feature attributions
justification TEXT NOT NULL, -- human-readable for compliance
scored_at TIMESTAMPTZ NOT NULL DEFAULT NOW()
);

CREATE INDEX IF NOT EXISTS idx_aml_ml_audit_alert
ON aml_ml_scoring_audit (alert_id, scored_at DESC);

CREATE INDEX IF NOT EXISTS idx_aml_ml_audit_recommendation
ON aml_ml_scoring_audit (recommendation, scored_at DESC);

COMMENT ON TABLE aml_model_versions IS 'AML ML model registry — champion/challenger versioning';
COMMENT ON TABLE aml_training_samples IS 'Analyst-labeled TP/FP samples for supervised training';
COMMENT ON TABLE aml_shadow_evaluations IS 'Champion vs challenger shadow mode comparison records';
COMMENT ON TABLE aml_drift_metrics IS 'PSI-based feature drift and accuracy degradation checks';
COMMENT ON TABLE aml_ml_scoring_audit IS 'Immutable audit log of every ML suppression/downgrade decision';
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