Risk Calculation Methodology

Overview

The Riskify Protocol employs a comprehensive risk assessment system that evaluates risk across different perils and regions. The risk scoring system is designed to be modular, transparent, and adaptable to various risk scenarios.

Risk Score Components

Base Risk Score

The base risk score represents the fundamental risk level for a specific peril in a given region:

struct RiskScore {
    uint256 baseScore;        // Base risk level (0-10000)
    uint256 temporalScore;    // Time-based risk adjustments
    uint256 crossPerilScore;  // Cross-peril interaction effects
    uint256 correlationScore; // Correlation with other risks
    uint256 confidenceScore;  // Confidence in the assessment
    uint256 lastUpdate;       // Timestamp of last update
}

Multi-Peril Risk Assessment

For scenarios involving multiple perils, the system calculates a composite risk score:

struct MultiPerilRisk {
    PerilTypes.Peril[] perils;           // Array of perils
    uint256[] individualScores;          // Individual risk scores
    uint256[][] correlationMatrix;       // Peril correlation matrix
    uint256 compositeScore;              // Combined risk score
    uint256 confidenceScore;             // Overall confidence
}

Risk Calculation Process

Single Peril Risk Calculation

The risk score for a single peril is calculated using the following formula:

RiskScore = BaseScore * TemporalAdjustment * CrossPerilAdjustment * CorrelationAdjustment

Where:

• BaseScore: Fundamental risk level (0-10000)
• TemporalAdjustment: Time-based risk factor (0-10000)
• CrossPerilAdjustment: Cross-peril interaction factor (0-10000)
• CorrelationAdjustment: Correlation impact factor (0-10000)

Multi-Peril Risk Calculation

For multiple perils, the system:

1. Calculates individual risk scores for each peril
2. Computes the correlation matrix between perils
3. Applies correlation adjustments
4. Generates a composite risk score

The composite score is calculated as:

CompositeScore = Σ(IndividualScores * Weight) + CorrelationAdjustment

Risk Model Updates

The risk scoring system can be updated through the updateRiskModel function:

function updateRiskModel(
    uint256 modelVersion,
    bytes calldata parameters
) external;

This allows for:

• Model version control
• Parameter updates
• Risk calculation refinements

Historical Risk Analysis

Historical risk scores can be retrieved using:

function getHistoricalScores(
    PerilTypes.Peril peril,
    bytes32 regionId,
    uint256 startTime,
    uint256 endTime
) external view returns (RiskScore[] memory scores);

This enables:

• Trend analysis
• Risk pattern identification
• Model validation

Risk Correlation

Peril correlations are calculated using:

function getPerilCorrelation(
    PerilTypes.Peril peril1,
    PerilTypes.Peril peril2,
    bytes32 regionId
) external view returns (uint256 correlation);

Implementation Guidelines

Risk Score Calculation

1. Base Score Calculation:

   • Evaluate historical data
   • Consider regional factors
   • Account for property characteristics

2. Temporal Adjustments:

   • Seasonal variations
   • Climate change trends
   • Time-based risk factors

3. Cross-Peril Effects:

   • Peril interactions
   • Compound risk factors
   • Systemic risk considerations

4. Correlation Analysis:

   • Peril relationships
   • Regional dependencies
   • Market correlations

Multi-Peril Assessment

1. Individual Analysis:

   • Calculate per-peril scores
   • Assess individual impacts
   • Determine base risk levels

2. Correlation Matrix:

   • Compute peril relationships
   • Identify dependencies
   • Map interaction patterns

3. Composite Scoring:

   • Weight individual scores
   • Apply correlation adjustments
   • Generate final score

Best Practices

1. Regular Updates:

   • Update risk models frequently
   • Monitor model performance
   • Validate against historical data

2. Data Quality:

   • Ensure accurate input data
   • Validate regional information
   • Maintain historical records

3. Model Management:

   • Version control
   • Parameter validation
   • Performance monitoring

4. Risk Monitoring:

   • Track score changes
   • Monitor correlations
   • Update confidence levels

Integration Guidelines

1. Risk Score Usage:

   • Validate scores before use
   • Consider confidence levels
   • Account for update frequency

2. Multi-Peril Handling:

   • Validate peril combinations
   • Check correlation limits
   • Monitor composite scores

3. Model Updates:

   • Follow version control
   • Validate parameters
   • Test updates thoroughly

Events and Monitoring

The system emits events for key operations:

event RiskScoreCalculated(
    PerilTypes.Peril peril,
    bytes32 regionId,
    uint256 baseScore,
    uint256 compositeScore
);

event MultiPerilRiskCalculated(
    bytes32 regionId,
    uint256 compositeScore,
    uint256 confidenceScore
);

event RiskModelUpdated(
    uint256 modelVersion,
    bytes parameters
);

These events enable:

• Risk score tracking
• Model update monitoring
• System transparency