Risk Models That Build Themselves

Consilience turns raw data into high-performance credit and fraud models.

Our AI-native platform discovers optimal features and parameters automatically with full auditability and regulatory compliance built in.

Purpose-built for credit & fraud teams
10×
Faster than manual feature engineering
< 3 days
Raw data to validation-ready model
+5%
Average AUC improvement over existing models

How It Works

We Automated Model Building

Turn raw data into high-performance models, with banking compliance and auditability built-in.

01

Connect Your Data

Connect your data warehouse or upload training data directly. We support complex JSON and credit report formats out of the box.

SnowflakeBigQueryS3PostgresDatabricksRedshift

Data connections

Snowflake
credit_applications47,234 rows
S3
bureau_reports_json47,234 rows
Redshift
payment_history312,891 rows
BigQuery
applicant_metadata47,234 rows
Loading records✓ Schema validated

829,593 records loaded · 14 field types detected

02

Build Optimized Model

Our platform explores thousands of potential predictors from your data — signals too expensive or time-consuming for any team to find manually. It selects only the features that genuinely improve the model, trains, and iterates until performance peaks. Every feature is intentionally built to meet banking compliance requirements.

Automated feature discoveryIterative optimizationCross-validationHyperparameter tuning

Feature evaluation — iteration 4/5

avg_months_since_delinq
+0.009
trade_utilization_ratio
+0.007
inquiry_velocity_30d
+0.005
raw_credit_limit_sum
−0.001

Model AUC

0.771 → 0.777

Features kept

69 / 4,200 candidates

03

Validate and Audit

Receive a model with a complete feature audit trail, SHAP analysis, explainable feature definitions, and training scripts you own. Built for banking compliance from day one.

AUC improvementFull audit trailExplainable features

Feature importance

Model ready ✓
avg_trade_age_months+0.012
pct_zero_balance_trades+0.008
recent_inquiry_count_90d+0.006
max_delinquency_severity+0.005

0.777

AUC

+9.4%

vs baseline

< 3 days

Time

Impact

The ROI of Automated Model Building

Build better models that approve more, optimize pricing, and cut losses. See what Consilience can do for your business.

Time Savings

ML Model Team Size3 people
115

Model build time

6–12 months3 days

Model validation

1–2 months~2 weeks

Model refresh cycle

3–6 months< 1 week
Engineering weeks saved annually30

Revenue Impact

Portfolio Size$500M
$100M$5B

Consilience Credit Model

+1% approval at same loss rate

+$5.0M

Consilience Pricing Model

Discover where to optimize APRs and increase take-up

+$1.5M

Consilience Fraud Model

15% reduction in fraud losses

+$375K
Estimated Annual Impact+$6.9M

Time savings based on 2 new models, 3 model refreshes, and 5 feature engineering sprints per year. Manual sprints average 8–12 weeks each vs. 3 days with Consilience.

The Platform

Everything you need to build world-class models

One platform covering the full lifecycle — from raw data to compliant ML model.

Automated Feature Engineering

Our platform systematically explores thousands of potential predictors from your financial data — surfacing signals that manual engineering would never find, at a fraction of the time.

Iterative Model Optimization

Models are trained, evaluated, and refined automatically. Only the features that genuinely improve predictive performance make the cut — everything else is eliminated.

Full Feature Auditability

Every feature comes with a human-readable definition, importance score, and version history. Built for bank-grade model risk management and regulatory review.

Complex Data, Parsed Automatically

Understands complex JSON and unstructured data out of the box. Builds feature engineering functions that extract and parse signals from nested objects, tradelines, and multi-level credit report structures.

Multi-Warehouse Integration

Native connectors for Snowflake, BigQuery, Databricks, Redshift, Postgres, and S3. Connect your data where it lives — no ETL required.

Deploys in Your AWS Environment

Runs inside your own AWS VPC. Your data never leaves your environment — no third-party ingestion, no shared infrastructure. SOC 2 compliant, fully airgap-compatible.

Use Cases

Every model your business needs

Credit, fraud, pricing, forecasting — whatever model your risk team needs, Consilience builds it in days, not quarters.

Credit Underwriting

Approve more of the right customers and lose less. Discover borrower segments your current model misses.

Fraud Detection

Reduce false positives without sacrificing approval rates. Surface behavioral signals that rule-based systems can't see.

Loan Pricing Models

Build risk-based pricing models that optimize for margin and volume simultaneously.

Model Refresh

Keep models current as borrower behavior evolves. Plug in new performance data and get a retrained, improved model — without months of manual work.

New-to-Credit Customers

Build models for thin-file customers using alternative data signals. Expand your addressable market without increasing portfolio risk.

Loss Forecasting

Hit quarterly targets reliably. Build portfolio-level loss models with leading indicators that give your team time to act.

Security & Compliance

Built for banks and fintechs

On-premises deployment, fair lending tooling, and full model auditability — designed to meet the security and compliance expectations of financial institutions.

Deploys in Your AWS Environment

Consilience runs inside your own AWS VPC. Your data never leaves your environment — no third-party ingestion, no shared infrastructure. SOC 2 compliant and fully airgap-compatible.

Fair Lending Built In

Disparate impact testing and adverse action code generation are built into every model run — designed to align with Reg B and CFPB fair lending guidance.

Designed for Regulatory Alignment

Built with model risk management in mind — designed to align with industry model validation standards and bank examiner expectations. Encryption at rest and in transit throughout.

Full Model Transparency

You own the models. Every feature has a human-readable definition. Every training run is logged and versioned. No black boxes — ever.

Backed By

BoxGroup

Leading investor behind Stripe, Ramp, and Plaid

Ready to build your best model?

Join leading lenders using Consilience to build faster, more accurate ML models — with full compliance built in.