Credit decisions in under a second
An ML-powered credit scoring engine that combines credit bureau data, open banking, and alternative data to score every applicant in real time. Approve thin-file and no-file customers you would otherwise turn away, with explainable results and full audit trails.
- 95% prediction accuracy
- Sub-second scoring response
- 40% lower default rates
Technology partners
We build the scoring engine on proven data and machine learning infrastructure, then connect it to the credit and banking sources your underwriters already trust.
Open banking connectivity for transaction and cash flow analysis.
Core language for feature engineering and model pipelines.
Classical models for interpretable, regulator-friendly scoring.
Deep learning for alternative-data and thin-file scoring.
Model tracking, versioning, and performance monitoring.
Cloud infrastructure for real-time, low-latency inference.
Challenges we solve
Traditional scorecards reject good customers, react slowly, and cannot explain themselves. The engine fixes the gaps that cost lenders volume and expose them to risk.
Thin-file rejections
Bureau-only scorecards reject thin-file and no-file applicants who would repay, leaving good volume on the table.
Slow manual reviews
Manual underwriting stretches decisions into days when applicants expect an answer in seconds.
Siloed data sources
Bureau data, banking transactions, and alternative signals sit in separate systems that never inform a single score.
Black-box models
Opaque scores that cannot be explained to regulators or declined applicants create compliance and dispute risk.
Rising default rates
Static scorecards miss changing risk patterns, so defaults climb while approval quality drops.
Fraud and identity gaps
Credit scoring without identity and fraud checks lets synthetic and stolen identities slip through approval.
Our approach
We deliver a scoring engine tuned to your portfolio, your risk appetite, and your regulator, then keep it accurate as your book changes.
Connect your data
We integrate credit bureaus, open banking APIs, and alternative data (utility, rent, e-commerce, telecom) into one scoring pipeline, with identity and fraud checks built in.
Build and train models
We deploy traditional bureau-based scores, alternative-data models for thin-file customers, and custom models trained on your portfolio for maximum accuracy.
Deploy real-time scoring
We expose scores through APIs that return an explainable decision in under a second, so origination systems can approve or decline on the spot.
Monitor and retrain
We track model performance in production, log every decision for audit, and retrain on new outcomes so accuracy holds as your portfolio shifts.
What we do
The engine covers the full scoring stack, from the data that feeds it to the models that decide and the controls that keep it compliant.
Multi-source data integration
We connect credit bureaus, open banking transaction data, and alternative signals like utility, rent, and telecom history into one applicant profile.
Traditional bureau scoring
FICO-style scoring on credit bureau data for established profiles, delivered in the industry-standard 300 to 850 range and accepted by regulators.
Alternative-data scoring
Machine learning models trained on alternative data score thin-file and no-file customers in real time, with explainable results underwriters can defend.
Custom portfolio models
Models trained on your own portfolio data for maximum accuracy, with continuous learning and performance tracking as loans mature.
Identity and fraud checks
Built-in identity verification and fraud screening stop synthetic and stolen identities before an application reaches approval.
Security and compliance
AES-256 encryption, SOC 2 Type II controls, GDPR-aligned privacy, and complete decision logging keep every score auditable and regulator-ready.
Let's build the next release together
Book a discovery call with our team and we'll map the fastest, lowest-risk path from where your technology is today to where your business needs it to be.
