Quantum Decisioning is a Gen-5 credit model API; built on $7B+ in SMB origination data and 15 years of lending performance history. Plug it into your existing workflow and start making better credit decisions in weeks, not months.
Traditional credit models were designed for consumer lending or large commercial relationships.
They underperform on SMB borrowers, thin-file businesses, emerging sectors, and non-traditional revenue models that do not fit neatly into legacy scoring frameworks.
The result is either over-declining good borrowers or under-pricing risk on bad ones.
A competitive credit model needs years of origination and performance data, specialized data science talent, and ongoing model validation infrastructure.
Most institutions lack one or more of these components, leaving them dependent on generic bureau scores or manual underwriting.
SMB borrowers expect fast answers. When decisioning takes days instead of minutes, applicants drop off, go to competitors, or abandon the process entirely. Every hour of delay between application and decision is measurable conversion loss.
Decisioning solves all three: a production-ready Gen 5 credit model API that returns approval decisions, risk tiers, and rate parameters in under 2 minutes, trained on data most institutions
do not have access to.
Multi-variable credit decisioning built on $7B+ in originated loan data and 15 years of SMB lending performance history.
Returns approval/decline outcomes, risk tiering, and configurable rate parameters. The model continuously learns from portfolio performance data.
Sub-two-minute decisioning for standard SMB applications.
API receives application data, runs the credit model, and returns a structured decision with risk tier, recommended terms, and compliance documentation. No manual queue, no underwriter bottleneck.
Set your own guardrails within Quantum’s approved framework. Configure approval thresholds, risk tier boundaries, rate ranges, and product eligibility rules.
The model enforces your parameters while applying Quantum’s credit intelligence.
Every credit decision includes fair lending analysis as a native output, not a bolt-on compliance check.
Adverse action notices, protected class analysis, and model validation documentation are generated automatically with each decision.
As your portfolio grows, the model calibrates to your specific borrower population and performance patterns.
Quarterly model reviews with Quantum’s data science team ensure the model stays optimized for your risk profile and market conditions.
Integrate Quantum Decisioning into your existing origination workflow via REST API. Send application data, receive structured credit decisions. Sandbox access in 48 hours for technical evaluation.
Set approval thresholds, risk tier definitions, rate ranges, and product-level eligibility rules. The model applies your business logic while leveraging Quantum’s credit intelligence and $7B+ data foundation.
Go live with automated credit decisioning. Applications flow through the model in real time. Clean approvals proceed to funding. Borderline cases route to manual review with model-generated context. Full compliance documentation on every decision.
Your decisions are powered by origination and performance data that took 15 years and $7B+ in loan volume to build.
No other standalone decisioning API offers this depth of SMB-specific training data.
2-minute decisioning means borrowers get answers fast. Faster answers mean higher conversion rates, better borrower experience, and competitive positioning against slower alternatives.
Compliance is not a module you add later. Fair lending analysis, adverse action notices, and model validation are native outputs of every decision, examiner-ready from day one.
Deploy as part of Quantum Core, Flex, or Ignite; or integrate as a standalone decisioning API with your own origination infrastructure. REST API works with any platform.
The Gen 5 model learns from portfolio performance data. Quarterly calibration reviews with Quantum’s data science team keep the model optimized for your specific borrower population and market conditions.
Financial institutions launching or scaling SMB lending programs need credit decisioning that outperforms generic bureau scores without the cost and time of building a proprietary model.
Embedded lending providers need API-speed decisioning that integrates cleanly with their application workflow and returns structured, compliant decisions to power the borrower experience.
Specialty and high-volume lenders need decisioning that handles diverse borrower profiles: thin-file businesses, non-traditional revenue models, and multi-product underwriting at scale.
Channel partners need consistent, fast decisioning across their referral network to maintain borrower trust and conversion rates.
Schedule a model evaluation to compare Quantum Decisioning against your current underwriting approach using anonymized application data from your own portfolio.
