datasynth-eval

Evaluation framework for synthetic financial data quality and coherence.

Overview

datasynth-eval provides automated quality assessment for generated data:

Statistical Evaluation: Benford's Law compliance, distribution analysis
Coherence Checking: Balance verification, document chain integrity
Intercompany Validation: IC matching and elimination verification
Uniqueness Analysis: Duplicate detection across datasets

Evaluation Categories

Category	Description
Statistical	Benford's Law, amount distributions, temporal patterns
Coherence	Trial balance, subledger reconciliation, FX consistency
Intercompany	IC matching rates, elimination completeness
Uniqueness	Document ID collisions, duplicate transaction detection

Usage

use datasynth_eval::{Evaluator, EvaluationConfig};

let evaluator = Evaluator::new(EvaluationConfig::default());
let report = evaluator.evaluate(&generated_data)?;

println!("Benford compliance: {:.2}%", report.benford_score * 100.0);
println!("Balance coherence: {}", report.balance_check.passed);

Evaluation Report

The evaluation produces a comprehensive report including:

Pass/Fail Status: Overall and per-category
Scores: Numerical scores for statistical measures
Warnings: Potential issues that don't fail validation
Details: Specific findings and recommendations

License