Banking transactions, loan data, market analysis
Detailed records of requests, approvals, and payments
This dataset provides a comprehensive view of enterprise procurement transactions, including detailed records of requests, approvals, and payments. It enables in-depth spend analytics, process mining, compliance monitoring, and vendor management, supporting organizations in optimizing procurement workflows and controlling costs.
Order placements, modifications, cancellations
This dataset provides a granular, timestamped record of order book events—including order placements, modifications, cancellations, and trades—across multiple equity markets and exchanges. With microsecond-level precision and comprehensive event attributes, it is ideal for quantitative research, backtesting high-frequency trading strategies, and analyzing market microstructure dynamics.
Employee and approver details, expense categorization, payment methods
This dataset provides a detailed, structured log of corporate expense reimbursement requests, including employee and approver details, expense categorization, payment methods, and audit flags. Designed for audit automation and fraud detection, it enables granular analysis of spending patterns, policy compliance, and exception handling across departments and projects.
Real-time snapshots of financial instrument prices, volumes
This dataset provides granular, real-time snapshots of financial instrument prices, volumes, and bid/ask spreads across global markets. Each record includes detailed pricing, volume, and market context, making it ideal for quantitative trading strategies, AI-driven forecasting, and market microstructure analysis. The data is structured for high-frequency, low-latency applications and supports robust financial analytics.
Volatility, risk scores, drawdowns
This dataset provides detailed, simulated and real portfolio-level risk metrics, including volatility, risk scores, drawdowns, and asset class allocations for asset managers and fintech teams. It supports robust risk analysis, performance benchmarking, and scenario modeling, making it ideal for financial analytics, compliance reporting, and investment strategy development.
Bank loan origination, repayment, default, and prepayment patterns
This dataset provides detailed, anonymized records of bank loan origination, repayment, default, and prepayment patterns, enriched with borrower demographic and employment information. It is ideal for developing and validating credit scoring models, analyzing risk factors, and exploring repayment behaviors across diverse borrower segments. The data structure supports advanced analytics and machine learning applications in financial risk management.
Sender and receiver information, transaction amounts, statuses
This dataset provides detailed, synthetic records of peer-to-peer payment transactions, including sender and receiver information, transaction amounts, statuses, device types, and fraud indicators. It is ideal for analyzing user payment behaviors, developing risk models, and designing fintech products, offering a robust foundation for segmentation and predictive analytics.
Sender and recipient information, transaction amounts, currencies
This dataset provides detailed, simulated records of international payment transactions, including sender and recipient information, transaction amounts, currencies, risk scores, and AML/fraud flagging. It is ideal for developing, testing, and benchmarking anti-money laundering, fraud detection, and risk assessment models in cross-border financial environments.
Transaction categories, payment methods, recurrence patterns
This dataset provides detailed, household-level records of income and expenses, including transaction categories, payment methods, recurrence patterns, and basic household demographics. It enables comprehensive budgeting analysis, supports financial literacy initiatives, and can power personalized financial recommendations and research into household spending habits.
Applicant demographics, application details, decision outcomes
This dataset provides detailed records of credit and loan applications, including applicant demographics, application details, decision outcomes, and annotated decision logic trails. It is designed to enable research in fairness, bias detection, and explainable AI by capturing both the reasoning behind decisions and any subsequent appeals. The dataset is ideal for developing and evaluating transparent, equitable credit decision systems.
28 cols
Network of financial transactions, detailing entities, transaction flows
This dataset provides a comprehensive synthetic network of financial transactions, detailing entities, transaction flows, and inter-entity relationships for advanced anti-fraud and network analytics. With labeled fraud instances and relationship metadata, it enables the development and benchmarking of anomaly detection, graph learning, and risk assessment models in financial contexts.
Financial statement records for public and private companies
This dataset simulates detailed financial statement records for public and private companies, enriched with fraud risk indicators and audit outcomes. It is designed for developing and benchmarking machine learning models to detect financial statement fraud, with comprehensive fields for financial metrics, suspicious activity counts, and risk scoring. The dataset is ideal for forensic analysis, risk assessment, and audit research in the finance industry.
Transaction types, amounts, merchant categories, account details
This dataset provides detailed, chronological transaction records for retail banking customers, including transaction types, amounts, merchant categories, account details, and geolocation data. Designed for advanced analytics, it enables modeling of spending patterns, customer segmentation, and risk assessment for financial institutions. The comprehensive structure supports both behavioral analysis and operational monitoring.
18 cols
High-resolution, synthetic minute-by-minute OHLC price
This dataset provides high-resolution, synthetic minute-by-minute OHLC price and trading volume data for multiple cryptocurrencies across various simulated exchanges and trading pairs. It is ideal for developing, testing, and benchmarking algorithmic trading strategies, as well as for financial modeling and market microstructure research. The dataset's structure supports robust time-series analysis and cross-market comparisons.
Account, customer, merchant, and contextual data
This dataset provides detailed, labeled records of simulated financial transactions, including account, customer, merchant, and contextual data, with explicit fraud indicators and scenario types. It enables robust development, benchmarking, and evaluation of fraud detection models for banking and fintech applications, supporting both supervised and unsupervised analytics.
Aggregates real-time sentiment scores
This dataset aggregates real-time sentiment scores and metadata for financial news headlines, enabling rapid detection of market-moving events and trends. It includes headline text, publication details, sentiment analysis, relevance to financial markets, and links to affected stocks and sectors. Ideal for quantitative trading, risk monitoring, and financial news analytics.
Payment timing, amounts, and loan outcomes
This dataset provides detailed microloan repayment behavior sequences, including payment timing, amounts, and loan outcomes, linked to customer demographics and loan characteristics. It is designed to support credit risk modeling, repayment pattern analysis, and the development of responsible lending strategies for fintech providers. The flat structure enables easy integration with analytics platforms and machine learning workflows.
27 cols
Monetary transactions and non-monetary actions
This dataset provides detailed, event-level records of digital wallet user activities, including monetary transactions and non-monetary actions, with rich contextual information such as device, location, channel, and session sequence. It enables comprehensive analysis of user behavioral patterns, session flows, and transaction outcomes for engagement optimization and fraud detection. The dataset is ideal for building predictive models, anomaly detection systems, and user segmentation strategies in digital finance.
Time-ordered sequences of price
This dataset provides detailed, time-ordered sequences of price and volume movements for major cryptocurrencies across leading exchanges. Each record includes summary statistics, granular price/volume points, and contextual metadata, making it ideal for quantitative research, algorithmic trading, and anomaly detection in crypto markets.
Timestamps, device and location data, step statuses, and error information
This dataset provides detailed, step-level tracking of user journeys through online loan application funnels, including timestamps, device and location data, step statuses, and error information. It enables in-depth analysis of user behavior, identification of process bottlenecks, and optimization of digital lending conversion rates. Ideal for financial institutions seeking to improve their digital onboarding and loan origination processes.
Real-time records of suspicious financial transactions flagged for potential fraud in
This dataset provides comprehensive, real-time records of suspicious financial transactions flagged for potential fraud in digital banking platforms. It includes detailed transaction data, risk scores, fraud patterns, investigation outcomes, and contextual information such as device, channel, and location. Ideal for developing and benchmarking fraud detection models, auditing risk management processes, and supporting regulatory compliance.
Applicant demographics, financial profiles, application outcomes
This dataset contains detailed synthetic records of credit card applications, including applicant demographics, financial profiles, application outcomes, and risk assessments. It is ideal for validating credit scoring models, detecting bias, and supporting regulatory compliance or fairness analysis in financial services. The flat schema design enables seamless integration with analytics and machine learning workflows.
Applicant demographics, application status changes, review
This dataset provides detailed, step-by-step workflow traces for consumer lending applications, including applicant demographics, application status changes, review and underwriting timelines, and funding outcomes. It enables comprehensive analysis of lending process efficiency, bottlenecks, and applicant characteristics for process optimization and risk assessment.
27 cols
Detailed transactions, valuations, risk metrics, and attribution factors
This dataset provides a comprehensive time series record of synthetic investment portfolio holdings, including detailed transactions, valuations, risk metrics, and attribution factors. It is ideal for portfolio analytics, risk modeling, and performance attribution studies, enabling in-depth analysis of investment strategies and exposures over time.
Code systems found in the sample rows of all 251 finance datasets.
Generated
One sentence in. A dataset with that pattern out.
| channel | mcc | amount | is_fraud |
|---|---|---|---|
| Online | 5411 | 84.20 | 1 |
| Chip | 5812 | 23.50 | 0 |
| Online | 5999 | 412.00 | 1 |
| Online | 5999 | 412.00 | 1 |
A pattern you asked for Everything else