Buy Now Pay Later Credit Performance Claim Verification Dataset

#fact verification #financial metric consistency checking #evidence-based classification #BNPL credit performance analysis #financial claim verification #consumer credit risk assessment

5000
0.3GB
JSON
CATL
MOBIUSI INC

Updated:2026-11-05

AI Analysis & Value Prop

Focused on credit performance disclosures in Buy Now Pay Later (BNPL), this dataset organizes claims about delinquencies, bad debts, write-offs, provisions, and receivables alongside supporting tables, notes, and text from financial reports. Records capture metric names and values, reporting periods, portfolio scopes, alignment between definitions and reporting context, and verification outcomes of supported, contradicted, or unconfirmed. It supports training and evaluation of models that verify credit risk claims in financial reports, including cases where metric definitions, periods, or portfolio scopes do not align.

Dataset Insights

Sample Examples

{}

Technical Specifications

Field	Type	Description
file_name	string	File name
claim_text	string	The original claim about BNPL delinquencies, bad debts, write-offs, provisions, or receivables that requires verification.
confidence	number	A score indicating the reliability of the verification outcome, ranging from 0 to 1.
metric_name	string	The credit performance metric identified in the claim, such as a delinquency rate, write-off amount, or receivables.
claimed_value	string	The metric value or qualitative result stated in the claim, preserving the original wording and unit.
claimed_period	string	The reporting period or measurement date covered by the claim.
evidence_quote	string	A relevant excerpt from the report supporting the verification outcome; leave blank when no usable excerpt is available.
reported_value	string	The corresponding metric value or qualitative result identified in the financial report evidence, preserving the original wording and unit.
reported_period	string	The reporting period or measurement date covered by the evidence.
verification_status	string	Indicates whether the claim is supported by the reported data, contradicted by it, or unconfirmed due to insufficient evidence.
report_evidence_text	string	The original text of a relevant table, note, or passage from a financial report.
period_scope_alignment	string	Describes whether the claim and report evidence use matching periods and portfolio scopes, including any limitations on comparison.
verification_rationale	string	Explains the verification outcome using the values, metric definitions, periods, and portfolio scopes.
claimed_portfolio_scope	string	The product, customer, geographic, or asset portfolio scope covered by the claim.
reported_portfolio_scope	string	The product, customer, geographic, or asset portfolio scope covered by the report evidence.
metric_definition_alignment	string	Describes whether the metric definitions in the claim and report evidence match, and identifies any differences.

Compliance Statement

Authorization Type	Proprietary - Commercial AI Training License (No Redistribution)
Commercial Use	Requires exclusive subscription or authorization contract (monthly or per-invocation charging)
Privacy and Anonymization	No PII, no real company names, simulated scenarios follow industry standards
Compliance System	Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs

Frequently Asked Questions

Which credit performance metrics are covered?: The dataset focuses on BNPL disclosures about delinquencies, bad debts, write-offs, provisions, and receivables. It records claim and report values, periods, portfolio scopes, and related evidence.

How are verification outcomes represented?: Outcomes distinguish claims supported by report evidence, contradicted by reported data, or unconfirmed due to insufficient evidence. The rationale can address metric definitions, values, periods, and portfolio scopes.

Which training or evaluation tasks does it support?: It supports claim verification, financial fact checking, metric comparison, and evidence extraction. It can also be used to evaluate whether models identify differences in metric definitions, reporting periods, or portfolio scopes.

How can I access the dataset, and what usage restrictions apply?: Refer to the access method and license terms on the product page. Before commercial use, research use, or redistribution, check the applicable data license and any citation, copyright, or usage restrictions on report excerpts.

Can't find the data you need?

Post a request and let data providers reach out to you.

Get this Dataset

Verified for Enterprise Use

Cite this Work

@dataset{Mobiusi2026,
  title={Buy Now Pay Later Credit Performance Claim Verification Dataset},
  author={MOBIUSI INC},
  year={2026},
  url={https://www.mobiusi.com/datasets/c4f8cfd1286f85580bf2c674f614606a},
  urldate={2026-10-20},
  keywords={BNPL dataset,credit performance claim verification,BNPL credit risk,financial report fact checking,delinquency rate verification,bad debt and write-off analysis,provision data validation,receivables claim review},
  version={1.0}
}

Using this in research? Please cite us.

placeholder

Scene

Domain

Modality

Task