The Financial Crime Intelligence Lifecycle
Most vendors isolate detection from investigation or treat model validation as an afterthought. Discover AI connects the entire operational lifecycle through a closed, governed loop.
Governed ingestion, feature engineering, and narrative intelligence
Establish high-fidelity, point-in-time financial crime datasets and unstructured narrative corpora with automated data contracts and privacy controls.
The Discover AI Financial Crime Suite
Seven modular, evidence-backed products engineered for AML compliance, fraud prevention, entity resolution, and quantitative model risk management.
Trigger-Based Tuning
Empirical threshold sensitivity analysis, trigger testing, and out-of-time backtesting to optimize transaction monitoring scenarios while maintaining risk coverage.
- Threshold Sensitivity Modeling
- Out-of-Time Back-Testing
- Capacity & Workload Forecasting
High-Risk Scoring Lab
Dedicated AML model development workbench with temporal leakage guards, entity-aware validation, point-in-time feature engineering, and model risk governance.
- Point-in-Time Feature Engineering
- Entity-Aware Cross-Validation
- Explainable Attribution (SHAP & Factor Weights)
Governed Data Engineering
Enterprise ingestion, schema harmonization, point-in-time dataset construction, and synthetic data generation for regulated financial crime environments.
- Point-in-Time Dataset Construction
- Automated Financial-Crime Data Contracts
- Realistic Synthetic Data Engine
Narrative Analytics & NLP Lab
Specialized unstructured text workbench for parsing alert notes, extracting financial crime typologies, and generating structured SAR/STR narrative drafting assistance.
- Evidence-Grounded SAR Narrative Assistance
- Typology & Predicate Crime Extraction
- Unsupported Claim & Hallucination Guardrails
Case Management System
Enterprise investigation and case management system designed specifically for financial intelligence units (FIUs) and financial crime operations.
- Unified Customer & Entity 360
- Interactive Transaction Timeline & Filtering
- Structured Evidence Dossier & Notes
Quality Management System
Second-line quality assurance and quality control system for financial crime investigations, enforcing audit consistency, objective checklists, and root-cause analysis.
- Stratified & Risk-Based Review Sampling
- Evidence-to-Conclusion Consistency Verification
- Standardized Defect Taxonomy & Severity Scoring
Discover EntityGraph
Multi-lingual entity resolution, sanctions and watchlist screening, and graph-based network analysis for uncovering concealed financial crime rings.
- Probabilistic & Rule-Based Entity Resolution
- Multi-Hop Graph Network Traversal
- Multi-Script & Transliteration Matching
Evidence-First Investigation & Quality
Explore how Discover AI unifies transaction timelines, explainable risk factors, cited SAR narrative drafts, and second-line quality checklists into a cohesive operational workflow.
Engineered for Examination Scrutiny
How Discover AI replaces black-box marketing claims with mathematically defensible, regulator-ready financial crime engineering.
Detection & Decision Output
Unexplained risk scores or opaque "black-box" numbers that investigators cannot defend during regulatory exams.
Factor attribution (tree-SHAP, feature impact) and primary transaction citations attached to every risk signal.
Rule & Threshold Tuning
Subjective threshold guessing with no statistical backtesting, causing massive alert spikes or silent risk omissions.
TBT empirical parameter sweeps, out-of-time backtesting, and automated OCC 2011-12 model risk workpapers.
Data Lineage & Temporal Integrity
Lookahead leakage in feature pipelines where future information accidentally contaminates historical training data.
Bi-temporal point-in-time data contracts ensuring mathematically verifiable reconstruction as of any historical timestamp.
Regulatory Filing & Decision Authority
Overhyped vendor claims of "autonomous SAR filing" that violate BSA/AML regulations and fail examiner scrutiny.
Strict human-in-the-loop governance: AI provides drafted evidence; investigator retains sole adjudication and filing authority.
Quality Assurance & Continuous Improvement
Second-line QA is treated as an isolated checklist with subjective grading and zero feedback loop to detection rules.
QMS statistical sampling, calibrated inter-rater reliability (Cohen’s Kappa), and automated feedback into tuning.
Built for Every Financial Crime Practitioner
From executive oversight to quantitative model validation, Discover AI provides specialized tools tailored to each critical stakeholder in the compliance ecosystem.
Chief Compliance & BSA Officer
Soaring alert processing costs, growing backlogs, and anxiety over examiners finding unsupported scenario tuning or unvalidated AI models.
Reviews executive dashboards connecting risk coverage, FTE capacity forecasts, and OCC-compliant validation workpapers.
Ready to Defend Every Threshold and Model Decision?
Schedule an evaluation walk-through with our quantitative and financial crime specialists. We configure demonstrations using authentic synthetic data aligned with your risk appetite.