datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Multi-Turn-Insurance-Underwriting
Dataset Card for Multi-Turn-Insurance-Underwriting
Dataset Summary
This dataset includes sample traces and associated metadata from multi-turn interactions between a commercial underwriter and AI assistant. We built the system in langgraph with model context protocol and ReAct agents. In each sample, the underwriter has a specific task to solve related to a recent application for insurance by a small business. We created a diverse sample dataset covering 6 distinct types… See the full description on the dataset page: https://huggingface.co/datasets/snorkelai/Multi-Turn-Insurance-Underwriting.Multi-Turn-Insurance-Underwriting-Code-Gen
Dataset Card for Multi-Turn-Insurance-Underwriting-Code-Gen
This dataset is a variant of the Multi-Turn-Insurance-Underwriting dataset, in which models do not get access to any tools except a code interpreter and a pointer to the relevant file system.
This helps us analyze how well models explore their environments.
Environment Creation
This diagram shows the architecture of how we create the dataset, with assistant responses interleaved with questions, ending with a… See the full description on the dataset page: https://huggingface.co/datasets/snorkelai/Multi-Turn-Insurance-Underwriting-Code-Gen.credit-underwriting-preview
Credit Underwriting Benchmark
A 1387-task RL environment for financial document understanding. Agents are provided with business documents (bank statements), and asked
to assess the risk associated by using a context-rich classification taxonomy for each transaction . The agent's output is programmatically graded
against the ground truth labelled by domain epxerts with over 10+ years of experience in the risk assessment field.
Scale
1387 qualifying cases (Businesses… See the full description on the dataset page: https://huggingface.co/datasets/metaphilabs/credit-underwriting-preview.underwriting-dataset-blocks
Dataset Card for underwriting-dataset-blocks
This dataset has been created with distilabel.
Dataset Summary
This dataset contains a pipeline.yaml which can be used to reproduce the pipeline that generated it in distilabel using the distilabel CLI:
distilabel pipeline run --config "https://huggingface.co/datasets/JETech/underwriting-dataset-blocks/raw/main/pipeline.yaml"
or explore the configuration:
distilabel pipeline info --config… See the full description on the dataset page: https://huggingface.co/datasets/JETech/underwriting-dataset-blocks.insurance-underwriting-loss-coherence-risk-v0.1What this repo is for
Detect misalignment between underwriting assumptions and real losses.
Focus
pricing vs exposure
risk score vs claim trend
early signals before loss spikes
Why it matters
Insurers often discover pricing mistakes too late.
This dataset tests whether systems can detect coherence loss early.
gcc-insurance-underwriting-riskMulti-Turn-Insurance-Underwriting
Dataset Card for Multi-Turn-Insurance-Underwriting
Dataset Summary
This dataset includes sample traces and associated metadata from multi-turn interactions between a commercial underwriter and AI assistant. We built the system in langgraph with model context protocol and ReAct agents. In each sample, the underwriter has a specific task to solve related to a recent application for insurance by a small business. We created a diverse sample dataset covering 6 distinct types… See the full description on the dataset page: https://huggingface.co/datasets/dennis-panos/Multi-Turn-Insurance-Underwriting.Multi-Turn-Insurance-Underwriting
Dataset Card for Multi-Turn-Insurance-Underwriting
Dataset Summary
This dataset includes sample traces and associated metadata from multi-turn interactions between a commercial underwriter and AI assistant. We built the system in langgraph with model context protocol and ReAct agents. In each sample, the underwriter has a specific task to solve related to a recent application for insurance by a small business. We created a diverse sample dataset covering 6 distinct types… See the full description on the dataset page: https://huggingface.co/datasets/AliDjl/Multi-Turn-Insurance-Underwriting.aprm-snorkelai_multi_turn_insurance_underwritinggcc-insurance-underwriting-riskbanking-loan-underwriting-default-coherence-risk-v0.1What this repo is for
Detect when underwriting assumptions stop matching default reality.
Focus
borrower risk grade vs leverage and coverage
pricing vs risk
early delinquency as first coherence break
Why it matters
Banks learn too late when risk grading drifts.
This dataset forces early detection.
gcc-insurance-underwriting-riskunderwriting-decision-training
Underwriting Decision Training
Training dataset for underwriting decision models. Contains risk assessments and approval decisions.
Dataset Details
Records: 10,000
Features: 19
Organization: GCC Insurance ML Models Hub
Features
Column
Type
Description
application_id
object
Feature for ML training
policy_type
object
Feature for ML training
applicant_age
int32
Feature for ML training
credit_score
int32
Feature for ML training
annual_income… See the full description on the dataset page: https://huggingface.co/datasets/gcc-insurance-ml-models/underwriting-decision-training.credit-underwriting-commercial
Credit Underwriting Benchmark (PII-Scrubbed)
Bank statement PDF extraction and transaction categorization benchmark.
All PDFs are PII-redacted — account details, personal identifiers removed.
504 cases: 1-7+ PDFs per case, ~3,077,200 total transactions
Ground truth: extraction (structured JSON) + categorization (transaction labels)
Primary metric: Extraction F1 (transaction matching by date+amount)
Source: Migrated from production credit underwriting platform
gcc-insurance-underwriting-risk
