| --- |
| language: en |
| license: mit |
| tags: |
| - legal |
| - msme |
| - dispute-resolution |
| - tabular-data |
| - india |
| size_categories: |
| - 1K<n<10K |
| task_categories: |
| - tabular-classification |
| --- |
| |
| # MSME Payment Dispute Dataset |
|
|
| ## Description |
| This dataset contains structured case-level information for **MSME payment disputes** in India. |
|
|
| The dataset was constructed from structured extraction of: |
|
|
| - MSME arbitration awards |
| - Commercial court decisions |
| - Public legal case repositories |
|
|
| All records are anonymized and structured for machine learning purposes. |
|
|
| ## Dataset Size |
| - ~4,600 structured cases |
| - 3 outcome classes: |
| - win |
| - settlement |
| - escalation |
|
|
| ## Features |
|
|
| | Column | Description | |
| |---------------------|------------------------------------------| |
| | claim_amount | Monetary claim value | |
| | delay_days | Payment delay duration | |
| | buyer_type | govt / private | |
| | contract_present | Whether formal contract exists | |
| | industry_sector | Sector classification | |
| | claim_imputed | Indicator if claim was imputed | |
| | delay_imputed | Indicator if delay was imputed | |
| | outcome_label | Target outcome (win / settlement / escalation) | |
|
|
| ## Preprocessing Steps |
| - Removed rare labels |
| - Removed invalid zero values |
| - Outcome-based delay imputation |
| - Model-based claim imputation |
| - Missingness flags added (`claim_imputed`, `delay_imputed`) |
|
|
| ## Intended Use |
| - Research in legal AI |
| - Tabular ML benchmarking |
| - MSME risk analysis |
| - Delay & claim prediction modeling |
| - Fairness & bias studies in legal outcomes |
|
|
| ## Limitations |
| - Structured data only (tabular) |
| - No raw legal document text included |
| - Synthetic augmentation applied in some cases |
| - Not an official government dataset |
| - Potential selection bias (only decided/arbitrated cases) |
