Automated underwriting for small business lenders
Consilience automates small business underwriting by turning the data lenders already hold — bank transactions, accounting records, bureau files — into compliance-ready credit models. Models are built in under a day inside your own cloud, with feature lineage, adverse-action codes, and validation reporting generated on every build.
The problem
Small business credit is the hardest underwriting problem in lending
Consumer models get deep bureau files and huge sample sizes. Small business lenders get neither — just heterogeneous businesses, thin credit histories, and data scattered across bank feeds and accounting systems.
Thin files, messy data
Small businesses rarely have deep bureau histories. The real signal lives in bank transactions, accounting records, and payment behavior — data most underwriting models never touch because the feature engineering is too expensive.
Manual review doesn’t scale
When the model can’t decide, an analyst does. Every application routed to manual review adds days of delay and real cost — and small-dollar commercial loans can’t carry that overhead.
Models go stale fast
Small business performance shifts with the economy faster than consumer credit does. A model refreshed every 12–18 months is a model that spends most of its life out of date.
The approach
A model factory, not a scoring API
Consilience doesn’t sell you a score. It builds underwriting models from your own portfolio data, inside your own cloud — and your team owns the result.
01
Connect the data you already have
Bank transaction feeds, accounting records, bureau files, application and repayment history. Native connectors for Snowflake, BigQuery, Databricks, Redshift, Postgres, and S3 — no data leaves your environment.
02
Discover the signal automatically
Automated feature engineering searches across sources for the predictors that matter for small business repayment — cash-flow patterns and payment behavior, not just bureau scores. Thin-file applicants become scorable.
03
Ship a model your regulators can read
Every build produces the model plus its audit trail: versioned feature definitions, lineage, importance scores, validation reporting, and adverse-action mappings. Refresh it whenever performance data warrants — in days, not quarters.
Want the full picture? Explore the Consilience platform or see every model type we build.
Compliance-first
Built for lenders who answer to regulators
Speed means nothing if the model can’t clear model risk review. Consilience treats governance artifacts as build outputs, not afterthoughts — and runs SOC 2-aligned infrastructure inside your own AWS VPC with zero data egress.
Model governance, generated per build
Feature lineage, importance scores, and validation reporting are produced automatically with every model — the documentation package your model risk team needs for review under SR 11-7.
What SR 11-7 requiresExplainable declines
Every score maps to adverse-action reason codes, so declined applicants get specific, defensible reasons — not a black-box number.
How adverse action codes workFair lending, tested not asserted
Candidate models can be evaluated for disparate impact before deployment, so fair-lending review happens during model development instead of after launch.
Disparate impact testing explainedSmall business underwriting FAQ
What data does Consilience use to underwrite small businesses?
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Whatever data you already have: bank transaction feeds, accounting records, bureau files, application data, and repayment history. Consilience automates the feature engineering across these sources — including the unstructured ones — and discovers which signals actually predict repayment for your portfolio, rather than relying on bureau scores alone.
How fast can a small business credit model be built?
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Consilience goes from raw data to a validation-ready model in under a day, roughly 10x faster than manual feature engineering. That speed also changes refresh economics: instead of a 6–12 month rebuild project, a refresh is a re-run of the same factory on new performance data.
Where does our applicant data live?
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Inside your own cloud environment, end to end. Consilience deploys into your AWS VPC, so application data, bank transaction data, and model artifacts never leave your infrastructure. There is no vendor data ingestion and no third-party data processing.
Can the models pass model risk and fair lending review?
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The platform is built compliance-first: every model ships with versioned feature definitions, lineage, validation reporting, adverse-action reason-code mappings, and support for disparate impact testing before deployment. Model governance documentation is an output of every build, not a separate project.
See it on your portfolio
Bring a sample of your small business lending data and we’ll show you what an automated build looks like — from raw tables to a validation-ready model.
Book a Demo