Decision and Data Configuration
Overview
This section covers how TimveroOS automates credit decisions and integrates external data. The platform combines visual workflow design with data source integration to enable automated assessment while maintaining manual review capabilities for complex cases.
Core Capabilities
Decision Automation
Design and execute credit assessment logic through visual workflows:
Workflow Tool for decision flow design
Automated scoring and risk categorization
Threshold-based decision outcomes (Approve, Decline, Manual Review)
Manual review routing for edge cases
Data Integration
Connect to external systems for credit assessment:
Data Source connections (credit bureaus, banking data, third-party services)
Mappings for data transformation (JavaScript/Python scripts)
Feature extraction and storage
Real-time and batch data retrieval
Analytics and Reporting
Monitor portfolio performance and generate reports:
BI dashboards for portfolio analytics
Delinquency and performance tracking
Regulatory reporting
Ad-hoc analysis capabilities
How It Works Together
Complete Assessment Flow:
Application Submitted → Workflow triggered
Data Retrieval → Data Sources called via Workflow nodes
Data Transformation → Mappings extract relevant attributes into Features
Profile Formation → Features saved to Participant Profile
Decision Execution → Workflow evaluates criteria and produces outcome
Result Action:
Green Zone (Approve) → Automated approval, proceed to offer
Red Zone (Decline) → Automated decline, notify applicant
Yellow Zone (Review) → Route to Manual Underwriting department
Analytics Capture → Decision data flows to BI Dashboard for reporting
Section Contents
Workflow Tool Visual workflow designer for creating decision logic with nodes, conditions, and routing rules
Data Sources External system connections for credit bureaus, banking data, and third-party services
Mappings JavaScript/Python scripts that transform Data Source responses into Features for decision workflows
Manual Review Manual underwriting process for cases requiring human evaluation
Analytics and Reporting Portfolio monitoring, performance tracking, and regulatory reporting capabilities
Decision Configuration Patterns
Pattern 1: Automated Straight-Through Processing
Use Case: Standard consumer loans with clear risk profiles
Configuration:
Preliminary workflow executes with internal data
Credit bureau Data Source called if needed
Mapping extracts credit score into Feature
Workflow evaluates score against threshold
Green zone (score ≥ 700) → Auto-approve
Red zone (score < 600) → Auto-decline
Yellow zone (600-699) → Manual review
Result: 70-80% straight-through processing
Pattern 2: Multi-Stage Assessment
Use Case: Complex credit products requiring progressive evaluation
Configuration:
Stage 1 (Application): Preliminary workflow with basic checks
Internal data only
Quick pass/fail decision
Low-cost, high-speed assessment
Stage 2 (Assessment): Detailed workflow if preliminary passes
Multiple Data Source calls (credit bureau, banking, employment)
Complex Mappings for Feature extraction
Comprehensive scoring logic
Profile formation for offer generation
Result: Cost-effective tiered assessment
Pattern 3: Hybrid Automated + Manual
Use Case: High-value loans or regulated products
Configuration:
Workflow executes automated scoring
Yellow zone threshold broader (catches more cases)
Warning Facts generated for specific conditions
Manual Underwriting department receives cases via FormBuilder
Specialist reviews automated results and makes final decision
Profile completion if additional data needed
Result: Automation benefits with human oversight
Configuration Workflow
Step 1: Define Decision Requirements
Document credit policy rules
Identify data needs
Define decision criteria and thresholds
Specify manual review triggers
Step 2: Set Up Data Sources (SDK + Admin Panel)
Framework: Configure Data Source connections
Admin Panel: Test connections and validate responses
Create sample requests for development
Step 3: Create Mappings (Admin Panel)
Write JavaScript/Python scripts
Extract relevant data into Features
Handle edge cases and errors
Test with real Data Source responses
Step 4: Design Workflows (Admin Panel)
Use Workflow Tool to create visual decision flows
Add Load Data Source nodes
Add Expression nodes with Mappings
Add Decision Tables or Switch nodes
Add Save to Profile nodes for Feature storage
Define outcomes (Green/Yellow/Red zones)
Step 5: Configure Manual Review (if needed)
Set up departments in Admin Panel
Create FormBuilder forms for review
Define routing rules
Test review workflows
Step 6: Test End-to-End
Run test applications through workflows
Verify Data Source calls
Check Mapping execution
Validate decision outcomes
Test manual review routing
Step 7: Monitor and Optimize
Track automation rates
Monitor Data Source performance
Analyze decision distribution
Refine thresholds based on results
Implementation Resources
Through Admin Panel (Step 2)
Decision Configuration:
Workflow Management - Workflow creation and management
Decision Automation - Automated decision setup
Manual Review Process - Manual underwriting configuration
Workflow vs Business Process - Understanding the difference
Data Configuration:
Data Sources - External system connections
Feature Store - Feature management
Metrics Engine - Calculated metrics
Analytics Configuration:
BI Dashboard - Portfolio monitoring setup
Through SDK (Step 1)
Framework Setup:
Workflow Integration - Workflow engine setup
DataSource Integration - External system connections
Entity Statuses - Status and workflow triggers
Key Considerations
Data Quality:
Validate all Data Source responses
Handle missing data gracefully
Test Mappings thoroughly
Monitor Feature quality
Decision Accuracy:
Start with conservative thresholds
Monitor approval/decline rates
Track default rates by decision zone
Refine based on performance data
Compliance:
Document all decision logic
Maintain complete audit trails
Ensure consistent application of rules
Support regulatory reviews
Performance:
Optimize Data Source call frequency
Cache frequently-used data
Monitor workflow execution time
Balance automation rate with accuracy
Related Topics
Loan Origination - How decisions fit into origination
Product Management - Product-specific decision rules
System Entities - Participant and Application data structures
TimveroOS: Automated decisions with external data integration
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