Credit Policy
Automatically generate and iterate candidate risk rules.
Magic Engine
Financial Risk Control Solution
ML risk models are difficult for business teams to understand. High technical barriers, and black-box results make it hard to respond to changing risk conditions.
Business Decision AI Platform
With the Business Decision AI Platform, teams can quickly build high-accuracy, explainable machine-learning risk scoring models and rules, generate deployment-ready SDK packages, and accelerate model rollout.
Use pre-screening and marketing response models to identify high-response, lower-risk customers.
Generate sequential rules and differentiated review paths by risk segment. Combine policy rules, credit models, and fraud models in progressive review, and tailor policies by lending product.
Build application scorecards (A-card), interest-rate models, and credit-limit models.
Build behavioral scorecards (B-card) and collections models.
From rule generation to explainable model development.
Automatically generate and iterate candidate risk rules.
Build accurate, explainable models and deploy them faster.
Five connected decisions across the credit lifecycle.
Identify responsive, lower-risk prospects.
Use rules and models to detect fraud.
Set policies by product and risk tier.
Support scoring, limits, and pricing.
Enable early warning and collections.
Practical Applications
Combine expert rules and machine-discovered patterns to intercept suspicious applications before approval.
Estimate credit outcomes and provide transparent drivers for approval or manual review.
Set differentiated limits and pricing while balancing expected risk, approval, and portfolio value.
Detect deterioration from account, repayment, transaction, and behavioral signals.
Route cases by repayment willingness and recovery probability to focus collection resources.