Pricing Configuration
Overview
The pricing configuration module in timveroOS enables financial institutions to define dynamic pricing algorithms that automatically calculate loan terms and conditions based on customer profiles, product parameters, and business rules. The system supports multiple programming languages and provides testing capabilities to ensure accuracy before deployment.
Offer Engine Architecture
The Offer Engine serves as the core pricing calculation component, processing customer data and product parameters to generate customized loan offers.

Key Components
Algorithm Scripts: Define pricing logic using:
Python
JavaScript
Spell (timveroOS scripting language)
Input Variables: Access to:
Customer profile attributes
Product specifications
Additive parameters
Market reference data
Output Structure: Generate:
Interest rates
Loan amounts
Term options
Fee calculations
Configuration Process
Accessing the Offer Engine
Navigate to pricing configuration through:
Settings → Offer Engine Description
Settings → Credit Products → [Select Product] → Additive Tab
During additive creation process
Creating Pricing Algorithms
The system provides a script editor where you can:
Define Base Logic
Set foundational pricing rules
Establish minimum/maximum boundaries
Configure profitability thresholds
Add Risk Adjustments
Credit score-based modifications
Debt-to-income considerations
Employment stability factors
Include Business Rules
Relationship pricing discounts
Promotional rate periods
Volume-based adjustments
Variables examples
Customer Profile Variables:
creditScore
- Credit bureau scoremonthlyIncome
- Verified incomedebtToIncome
- Calculated DTI ratioemploymentMonths
- Employment durationexistingCustomer
- Relationship flag
Product Variables:
requestedAmount
- Loan amountrequestedTerm
- Desired durationproductType
- Product categoryadditiveCode
- Specific variant
Calculation Variables:
baseRate
- Starting interest rateriskPremium
- Risk adjustmentrelationshipDiscount
- Customer benefits
Testing and Validation
Test Interface
Before deploying pricing algorithms, use the built-in testing tool:
Select Test Parameters
Choose product
Select additive
Pick test participant
Run Test Scenario
Click "Test" button
System executes algorithm
View generated offer
Validate Results
Check calculated rates
Verify amount limits
Confirm term options
Review fee structure
Error Handling
Common test failures and solutions:
Script Errors:
Syntax errors in code
Missing variable references
Logical inconsistencies
Data Issues:
Missing profile attributes
Invalid data types
Out-of-range values
Business Rule Violations:
Below profitability threshold
Outside product parameters
Regulatory compliance issues
Deal Block Integration
The pricing engine integrates with the Deal Block to present offers to customers:

Offer Presentation Flow
Product Eligibility
System evaluates all products
Pricing engine calculates offers
Available products displayed
Conditional Availability
Products requiring collateral highlighted
Missing requirements indicated
Dynamic recalculation upon changes

Offer Details
Interest rate presentation
Payment schedule preview
Total cost disclosure


Pricing Strategies
Risk-Based Pricing
Configure algorithms to adjust rates based on risk factors:
Credit score tiers
Income verification levels
Collateral coverage ratios
Payment history patterns
Relationship Pricing
Implement benefits for existing customers:
Multi-product discounts
Loyalty rate reductions
Payment history rewards
Referral incentives
Market-Based Adjustments
Include market conditions in pricing:
Reference rate integration
Competitive positioning
Portfolio composition goals
Seasonal adjustments
Integration with Other Modules
Product Configuration
Pricing algorithms connect to:
Product parameters for boundaries
Additive settings for specific rules
Documentation requirements
Workflow triggers
Workflow Management
Pricing outcomes influence:
Approval thresholds
Documentation requirements
Collateral specifications
Processing paths
Reporting and Analytics
Track pricing effectiveness through:
Offer acceptance rates
Portfolio yield analysis
Competitive positioning
Profitability metrics
Best Practices
Algorithm Design
Start with simple logic and add complexity gradually
Comment code thoroughly for maintenance
Use consistent variable naming conventions
Build in error handling for edge cases
Testing Protocol
Test with representative customer profiles
Include boundary conditions
Verify regulatory compliance
Document test scenarios and results
Performance Optimization
Minimize complex calculations
Cache frequently used values
Optimize database queries
Monitor execution times
Maintenance
Regular review of pricing effectiveness
Update algorithms based on performance
Maintain version history
Document all changes
Common Use Cases
Personal Loans
Simple interest rate calculations
Risk-based pricing tiers
Term-dependent rates
Fee structures
Auto Loans
LTV-based adjustments
Vehicle age considerations
Down payment requirements
Insurance factors
Mortgage Products
Complex rate structures
Multiple adjustment factors
Regulatory compliance
Long-term considerations
Troubleshooting
No Offers Generated
Check algorithm logic
Verify test data completeness
Review profitability settings
Examine product parameters
Incorrect Calculations
Debug algorithm step-by-step
Verify variable values
Check mathematical operations
Review business rules
Performance Issues
Simplify complex calculations
Optimize data retrieval
Review algorithm efficiency
Consider caching strategies
Next Steps
With pricing configured, proceed to:
Collateral Management - Configure security requirements
Workflow Management - Build approval processes
Loan Servicing - Set up portfolio management
For additional pricing configuration support, consult your implementation team or system documentation.
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