Our Solution
Our AI Lending Suite
Powering Intelligent Lending Decisions The ai1 Lending Suite—ai1 Secure Lending Agent (frontend POS) + backend ScoreAI—delivers realtime loan and credit assessments. Models blend supervised and unsupervised learning and adapt continuously to micro and macro indicators. This “Live Lending Neural Network” updates decisions with GDP trends, rates, unemployment, and income levels. Loan snapshotting and whatif tools enable scenario testing, policy stress, affordability, and loss analysis as conditions change.
Discover the Future of Responsible AI in Lending.Achieve Unmatched Efficiency and Cost Savings
Automate repetitive tasks to cut labor and cycle time—accelerating reviews and decisions without sacrificing rigor.
Leverage Data Analytics for Smarter Decisions
Surface patterns, trends, and anomalies across portfolios to improve risk selection, earlywarn issues, and uncover new revenue.
Ensure Compliance with Ease
Automated checks, policy guardrails, and complete audit trails minimize noncompliance risk and reduce reporting burdens., reducing the risk of non-compliance and minimizing associated penalties.
Revolutionize Customer Experience
The ai1 Secure Lending Agent provides 24/7 support—answering questions, collecting documents, and guiding applicants with a consistent, unbiased experience.
Anomaly and Fraud Detection
Continuous monitoring detects and prevents suspicious behavior in real time—meeting regulatory expectations.
Hyper-Personalization for Customer Engagement
Use behavior and preferences to present relevant products, terms, and advice—improving conversion and lifetime value.
Stay Ahead with Predictive Analytics
Forecast market shifts and portfolio outcomes with forwardlooking signals to proactively adjust pricing, limits, and policies.
Unparalleled Security and Resilience
Robust cloud backup/DR, strict access controls, and continuous threat monitoring keep systems resilient.
Dynamic Decision-Making
Fuse applicant data with changing economic conditions to flag when previously declined or borderline applications become eligible—and explain why.
nitiative-taking Recommendations
Provide applicants clear, actionable steps—documentation, DTI, collateral, or terms—to meet approval criteria.
What-If Analysis
Manual or automated scenarizing compares historical and current outcomes, stresstests affordability, and evaluates loss curves to unlock opportunities.
Effective ML Models
Under the hood: KANs + specialized stacked ensembles for accuracy and interpretability; active/continuous learning to stay current; pioneering ports to PNNs (e.g., AOC) for nextgen speed and efficiency.