Finance datasets

Banking transactions, loan data, market analysis

  • 248 ready-made datasets
  • 8 formats, Excel to Parquet
  • First download free
What the 248 cover1 square = 1 dataset
  • Payments & messaging101
  • Credit & lending44
  • Banking & transactions36
  • Fraud & AML31
  • Markets & investing18
  • Expenses & invoicing13
  • Everything else5
Grouped by dataset title and tags.

248 datasets · page 8 of 11

Showing all 24 on this page

Payments & messaging

Microloan Repayment Performance Records

Payment timing, amounts, borrower demographics, and loan characteristics

This dataset provides granular microloan repayment histories, including payment timing, amounts, borrower demographics, and loan characteristics, across emerging markets and fintech platforms. It is ideal for developing and benchmarking credit scoring models, analyzing repayment patterns, and understanding risk factors in microfinance. The dataset supports advanced analytics for financial inclusion and responsible lending.

21 cols

  • repayment_amount
  • scheduled_repayment_amount
  • repayment_status
  • is_final_repayment
  • +17
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repayment_amount
520.75
scheduled_repayment_amount
520.75
repayment_status
on_time

Fraud & AML

Payment Fraud Detection Dataset

Payment transaction records, each labeled with ground-truth indicators of fraud

This dataset contains detailed synthetic payment transaction records, each labeled with ground-truth indicators of fraud. It includes transaction metadata, customer and merchant identifiers, payment methods, device and location context, and fraud reasons, making it ideal for developing and benchmarking machine learning models for payment fraud detection and risk mitigation.

19 cols

  • payment_method
  • fraud_label
  • fraud_reason
  • transaction_datetime
  • +15
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payment_method
credit_card
fraud_label
false
amount
249.99

Banking & transactionsTop 10 most opened

Bank Transaction Categorization Sample

Detailed transaction metadata, merchant information

This dataset contains labeled bank transaction records, including detailed transaction metadata, merchant information, and manually or automatically assigned expense categories. It is ideal for developing, training, and benchmarking automated expense categorization models for personal finance, budgeting, and regulatory compliance applications.

17 cols

  • merchant_category_code
  • transaction_type
  • category
  • transaction_date
  • +13
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merchant_category_code
5411
transaction_type
debit
category
groceries

Credit & lending

Loan Application Decision Records

Applicant demographics, financial information, loan terms

This dataset provides detailed, anonymized records of loan applications and their automated approval or rejection outcomes, including applicant demographics, financial information, loan terms, and decision rationale. It is ideal for credit risk modeling, regulatory compliance auditing, and fairness analysis of lending algorithms.

20 cols

  • decision_datetime
  • loan_amount
  • loan_term_months
  • loan_purpose
  • +16
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loan_amount
25000
loan_term_months
60
loan_purpose
auto

Fraud & AML

Finance AML Transaction Alerts

Banking transactions annotated with anti-money laundering (AML) alert flags

This dataset contains synthetic banking transactions annotated with anti-money laundering (AML) alert flags, detailed reason codes, and customer risk information. It is designed to support the development and evaluation of compliance models, enabling detection of suspicious activities and regulatory reporting. The dataset includes transaction details, alert triggers, and customer risk profiles for comprehensive AML analytics.

18 cols

  • transaction_datetime
  • transaction_amount
  • transaction_type
  • alert_flag
  • +14
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transaction_amount
0
transaction_type
deposit
alert_flag
false

Fraud & AML

Finance Customer Risk Profiles

Demographic information, financial activity metrics, risk scores

This dataset provides detailed synthetic customer risk profiles for financial institutions, including demographic information, financial activity metrics, risk scores, and compliance indicators. It is ideal for developing and testing lending analytics, risk modeling, and anti-money laundering (AML) compliance systems in banking environments.

28 cols

  • risk_score
  • risk_category
  • account_status
  • annual_income
  • +24
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risk_score
0.18
risk_category
low
account_status
active

Banking & transactions

Finance Transaction Time-of-Day Trends

Account, merchant, channel, and location information

This dataset contains detailed, timestamped financial transactions from retail banks and payment processors, including account, merchant, channel, and location information. Designed for in-depth analysis of temporal spending patterns, fraud detection, and channel usage trends, it supports a wide range of financial analytics and business intelligence applications.

15 cols

  • transaction_amount
  • transaction_type
  • transaction_status
  • currency_code
  • +11
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transaction_amount
-54.23
transaction_type
purchase
transaction_status
completed

Credit & lending

Credit Card Limit Optimization

Current and optimal credit limits, risk and utilization metrics

This dataset provides detailed records of credit card accounts, including current and optimal credit limits, risk and utilization metrics, payment history, and historical limit adjustments. Designed for credit risk modeling and customer optimization, it supports advanced analytics for limit management, customer segmentation, and predictive modeling in financial services.

18 cols

  • current_credit_limit
  • optimal_credit_limit
  • last_limit_adjustment_amount
  • limit_adjustment_reason
  • +14
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current_credit_limit
85000
optimal_credit_limit
90000
last_limit_adjustment_amount
5000

Banking & transactionsTop 10 most opened

Banking Transaction Categorization Dataset

Transaction amounts, merchant details, categories

This dataset provides detailed, labeled banking transaction records, including transaction amounts, merchant details, categories, and recurrence information. It is ideal for developing and benchmarking expense tracking, personal finance management, and automated categorization tools. The dataset enables granular financial analysis and supports machine learning applications for transaction classification.

18 cols

  • transaction_time
  • merchant_category_code
  • category
  • transaction_type
  • +14
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merchant_category_code
5411
category
Groceries
transaction_type
debit

Finance

Finance-Technology Support Interactions

Support ticket interactions for financial technology products

This dataset provides detailed logs of support ticket interactions for financial technology products, capturing issue types, escalation events, resolution times, agent assignments, and customer satisfaction ratings. It enables in-depth analysis of support efficiency, automation opportunities, and escalation trends, making it valuable for optimizing customer service operations and product support strategies.

21 cols

  • submitted_datetime
  • customer_name
  • product_name
  • issue_type
  • +17
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customer_name
Patricia Lee
product_name
FinFlow Mobile Banking
issue_type
login

Fraud & AML

Financial Transaction Fraud Scores

Bank transactions, each annotated with a synthetic fraud risk score

This dataset provides detailed, structured records of bank transactions, each annotated with a synthetic fraud risk score and binary fraud label. It includes transaction, account, merchant, and contextual information, making it ideal for training and evaluating fraud detection and risk assessment models. The dataset supports feature engineering for advanced analytics and machine learning applications in financial security.

19 cols

  • transaction_datetime
  • transaction_amount
  • transaction_type
  • fraud_score
  • +15
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transaction_amount
52.47
transaction_type
purchase
fraud_score
0.05

Credit & lending

Synthetic Microloan Performance Dataset

Origination, borrower demographics, repayment schedules, delinquency events

This dataset provides detailed, synthetic records of small business and personal microloans, including origination, borrower demographics, repayment schedules, delinquency events, and recovery outcomes. It is ideal for developing and benchmarking credit risk models, analyzing financial inclusion, and studying loan performance patterns across diverse borrower segments.

30 cols

  • loan_type
  • loan_amount
  • currency
  • interest_rate
  • +26
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loan_type
personal
loan_amount
800
currency
USD

Finance

Corporate ESG Compliance Disclosures

Company identifiers, reporting periods, ESG scores, emissions

This dataset provides detailed, standardized records of corporate ESG (Environmental, Social, and Governance) compliance disclosures, including company identifiers, reporting periods, ESG scores, emissions, diversity metrics, and policy indicators. It enables robust benchmarking, analytics, and transparency for investors, regulators, and sustainability analysts seeking to evaluate enterprise ESG performance and compliance trends.

29 cols

  • esg_framework
  • total_esg_score
  • esg_controversies_count
  • disclosure_url
  • +25
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esg_framework
GRI
total_esg_score
18.57
esg_controversies_count
18

Markets & investing

Financial Portfolio Stress Testing

Asset-level and portfolio-level impacts under various macroeconomic

This dataset provides detailed results of simulated financial portfolio stress tests, including asset-level and portfolio-level impacts under various macroeconomic and market shock scenarios. It supports regulatory compliance, risk analytics, and scenario-based portfolio management, making it ideal for financial institutions and risk professionals seeking robust stress testing automation.

22 cols

  • portfolio_name
  • portfolio_owner
  • total_portfolio_value
  • portfolio_value_post_scenario
  • +18
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portfolio_name
US Large Cap Equity Growth
portfolio_owner
Prime Asset Management
total_portfolio_value
50000000

Banking & transactions

Banking Transaction Graphs Dataset

Interconnected banking transaction records, capturing sender

This dataset provides detailed, interconnected banking transaction records, capturing sender and receiver relationships, transaction metadata, and anomaly flags. Designed for network analytics, it enables advanced anti-money laundering (AML) detection, fraud analysis, and financial behavior modeling by representing transactions as a directed graph. The flat structure ensures easy integration with machine learning and graph analytics tools.

16 cols

  • transaction_type
  • transaction_status
  • amount
  • currency
  • +12
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transaction_type
payment
transaction_status
completed
amount
56.23

Credit & lending

Automated Loan Application Assessment

Applicant demographics, financial profiles, loan details

This dataset contains detailed synthetic records of loan applications, including applicant demographics, financial profiles, loan details, automated risk assessments, and approval or denial outcomes. It is ideal for developing and evaluating AI models for credit decisioning, risk analysis, and fair lending compliance, with fields supporting bias detection and explainability. The data structure enables robust analytics for both operational and regulatory use cases.

30 cols

  • applicant_marital_status
  • applicant_employment_status
  • applicant_annual_income
  • applicant_credit_score
  • +26
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applicant_marital_status
married
applicant_employment_status
employed
applicant_annual_income
78500

Banking & transactions

ATM Usage and Failure Events

Detailed transaction records, failure diagnostics, and maintenance actions

This dataset provides a comprehensive log of ATM usage and failure events, including detailed transaction records, failure diagnostics, and maintenance actions. It enables financial institutions to analyze ATM performance, optimize service schedules, and implement predictive maintenance strategies for improved uptime and customer satisfaction.

25 cols

  • atm_location_name
  • event_type
  • event_datetime
  • failure_type
  • +21
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atm_location_name
Downtown Branch
event_type
transaction
atm_status_post_event
operational

Fraud & AML

Online Merchant Fraud Indicators

Transaction volumes, chargeback rates, fraud losses

This dataset provides merchant-level fraud signals and outcomes, including transaction volumes, chargeback rates, fraud losses, and calculated risk scores. Designed for supervised learning and analytics, it enables robust fraud detection, risk profiling, and compliance monitoring for online payment platforms. The comprehensive structure supports both operational and predictive use cases in fraud prevention.

21 cols

  • merchant_name
  • merchant_category
  • fraud_flag_last_30d
  • fraud_type_last_30d
  • +17
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merchant_name
Vivid Electronics Ltd
merchant_category
electronics
fraud_flag_last_30d
false

Banking & transactionsTop 10 most opened

Transaction Categorization Dataset

Raw descriptions, merchant information, categorized labels

This dataset provides a comprehensive, labeled collection of real-world bank transactions, including raw descriptions, merchant information, categorized labels, and enrichment fields for AI training. It enables robust development of transaction categorization, statement enrichment, and personal finance analytics models, supporting both supervised and semi-supervised learning scenarios.

20 cols

  • merchant_category_code
  • category
  • transaction_type
  • balance_after_transaction
  • +16
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merchant_category_code
5942
category
Shopping
transaction_type
debit

Payments & messaging

Customer Loan Repayment Histories

Payment amounts, statuses, timing, and outstanding balances

This dataset provides granular, event-level records of customer loan repayments, including payment amounts, statuses, timing, and outstanding balances. It enables robust risk modeling, customer segmentation, and repayment behavior analysis for lenders and financial institutions. The inclusion of customer and loan attributes supports advanced analytics and credit scoring applications.

20 cols

  • loan_amount
  • loan_status
  • loan_start_date
  • loan_end_date
  • +16
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loan_amount
10000
loan_status
active
payment_amount
322.5

Banking & transactions

Bank Call Center Interaction Logs

Timing, outcomes, speech analytics, sentiment, and satisfaction scores

This dataset provides granular logs of bank call center interactions, capturing detailed information about each customer-agent conversation, including timing, outcomes, speech analytics, sentiment, and satisfaction scores. It enables comprehensive analysis of customer experience, agent performance, and operational trends, supporting both quality assurance and advanced speech analytics use cases.

18 cols

  • interaction_datetime
  • interaction_duration_seconds
  • call_direction
  • call_channel
  • +14
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interaction_duration_seconds
415
call_direction
inbound
call_channel
phone

Expenses & invoicing

Enterprise Procurement Transaction Logs

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.

27 cols

  • department
  • item_category
  • quantity
  • unit_price
  • +23
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department
IT
item_category
IT Equipment
quantity
12

Markets & investing

High-Frequency Stock Order Book

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.

13 cols

  • order_book_level
  • symbol
  • event_type
  • side
  • +9
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order_book_level
1
symbol
AAPL
event_type
new_order

Expenses & invoicing

Corporate Expense Reimbursement Logs

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.

22 cols

  • expense_category
  • expense_amount
  • expense_date
  • employee_name
  • +18
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expense_category
Travel
expense_amount
487.5
employee_name
Samuel L. Miller

Real codes. Never real customers.

Code systems found in the sample rows of all 248 finance datasets.

Code systemDatasets using it, of 248
  1. ISO 4217currencies161USD · GBP · EUR
  2. ISO 3166countries144US · USA · FR
  3. SWIFT BICbank identifiers45DEUTDEFFXXX · BOFAUS3N · NWBKGB2L
  4. MCCmerchant categories115814 · 5411 · 5812
  5. IBANaccount numbers7DE89370400440532013000 · IT60X0542811101000000123456 · DE23100100101234567893
  6. SWIFT MTmessage types6MT103 · MT900 · MT202
  7. ISINsecurities4GB00B03MLX29 · DE000BASF111 · FR0000123456
  8. ISO 20022payment messages3ACCP · pacs.008
A person from the Identity Theft Cases datasetGenerated
victim_first_name
Jessica
victim_last_name
Mendoza
victim_date_of_birth
1988-03-25
victim_gender
female

Generated

Most common columnsDatasets, of 248
  1. currency99
  2. transaction_id62
  3. customer_id53
  4. transaction_type49
  5. transaction_amount41

Not quite what you need? Describe it.

One sentence in. A dataset with that pattern out.

  • Online fraud 4×
  • Real merchant category codes
  • Duplicate rows
Preview 20 rows freeNo signup. No card.
Fraud rate by channel
0%2.5%5%1%Chip1%Contactless4%Online11%Phone
Sample rows for: Card payments from 5,000 customers, where online payments are 4× more likely to be fraud, with real merchant category codes and a few duplicate rows.
channelmccamountis_fraud
Online541184.201
Chip581223.500
Online5999412.001
Online5999412.001

A pattern you asked for Everything else

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