Electronic Payment Data: Best Electronic Payment Datasets & Databases

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Eugenio Caterino
Editor & Data Industry Expert

What is Electronic Payment Data?

Electronic payment data is information generated during electronic transactions, such as credit card purchases or online payments. It includes details like the transaction amount, date and time, merchant information, and customer data. This data is crucial for financial institutions, businesses, and individuals to track and reconcile payments, detect fraud, and analyze spending patterns. On this page, you’ll find the best data sources for digital payments dataset, online payments data.

Best Electronic Payment Databases & Datasets

Here is our curated selection of top Electronic Payment Data sources. We focus on key factors such as data reliability, accuracy, and flexibility to meet diverse use-case requirements. These datasets are provided by trusted providers known for delivering high-quality, up-to-date information.

Logo of Envestnet | Yodlee

Envestnet | Yodlee's De-Identified Electronic Payment Research Panel | USA Employee Payroll Data covering 4800+ employers | Cohort Analysis

by Envestnet | Yodlee
USA
Free sample preview
Pricing available upon request
Logo of Measurable AI

Paypal Email Receipt Data | Consumer Transaction Data | Payment Data | Asia, EMEA, LATAM, MENA, India | Granular & Aggregate Data available

by Measurable AI
USA
Japan
Brazil
+4
Free sample preview
API available
Pricing available upon request
Logo of Envestnet | Yodlee

Envestnet | Yodlee's De-Identified Electronic Payment Data | Row/Aggregate Level | USA Consumer Data covering 3600+ corporations | 90M+ Accounts

by Envestnet | Yodlee
USA
Free sample preview
Pricing available upon request
Logo of Measurable AI

SKU-Level Granular Email Receipt Data | Consumer Transaction Data for USA & Continental Europe | Ecommerce / Food Delivery / Ride Hailing / Payments

by Measurable AI
USA
United Kingdom
Germany
+6
Free sample preview
Pricing available upon request
Logo of Envestnet | Yodlee

Envestnet | Yodlee's De-Identified Electronrics Transaction Data | Row/Aggregate Level | USA Consumer Data covering 3600+ corporations | 90M+ Accounts

by Envestnet | Yodlee
USA
Free sample preview
Pricing available upon request
Logo of PG

PG | Consumer Transaction Data | 105M Transactions, $742M montly volume | Sales Transaction Data perfect for Consumer Trend Analysis

by PG
USA
Canada
Free sample preview
Pricing available upon request
Logo of Opah Labs

Opah Labs Bank Transaction Data | 800K Total Records w/ Weekly Updates |

by Opah Labs
Tanzania
Uganda
Free sample preview
Pricing available upon request
Logo of Envestnet | Yodlee

Envestnet | Yodlee's De-Identified Company Data Research Panel | USA Employee Payroll Data covering 4800+ employers | Cohort Analysis

by Envestnet | Yodlee
USA
Free sample preview
Pricing available upon request
Logo of IPQualityScore (IPQS)

IP Address Reputation & Intelligence

by IPQualityScore (IPQS)
5.0
USA
United Kingdom
Germany
+237
API available
Starts at
$499 / month
Logo of Envestnet | Yodlee

Envestnet | Yodlee's De-Identified Ecommerce Sales Data | Row/Aggregate Level | USA Consumer Data covering 3600+ corporations | 90M+ Accounts

by Envestnet | Yodlee
USA
Free sample preview
Pricing available upon request

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Electronic Payment Data is essential for a wide range of business applications, offering valuable insights and driving opportunities across industries. Below, we have highlighted the most significant use cases for Electronic Payment Data.

What Are Examples of Electronic Payment Data?

Examples of electronic payment data include transaction details, customer information, payment method used, and purchase history. Here is the complete list:

  • Transaction Amount: The total amount of the transaction.
  • Date and Time: When the transaction occurred.
  • Merchant Information: Details about the merchant receiving the payment.
  • Customer Information: Data about the customer making the payment.
  • Payment Method: Type of payment used, such as credit card, debit card, or electronic wallet.
  • Purchase History: Record of past transactions by the customer.

Electronic Payment Data Attributes

Imagine an online purchase made through a digital wallet. The electronic payment data for this transaction would include:

  • Transaction Amount: $120.00
  • Date and Time: July 1, 2024, at 3:45 PM
  • Merchant Information: ABC Electronics, merchant ID #4567
  • Customer Information: John Smith, customer ID #12345
  • Payment Method: Digital wallet
  • Purchase History: Previous purchases including a laptop and headphones

You can find this type of data in databases and datasets that fall under the category of transaction data, consumer transaction data and B2B transaction data.

How is Electronic Payment Data Collected?

Electronic payment data is collected through various methods, depending on the payment system used:

How is Electronic Payment Data Used?

Electronic payment data is used for various purposes such as:

  • Fraud Prevention: Identifying unusual transaction patterns that may indicate fraud.
  • Sales Analysis: Understanding revenue trends and financial performance.
  • Customer Behavior Analysis: Gaining insights into customer purchasing habits.
  • Payment Process Improvement: Streamlining and enhancing payment processes.

What Are the Models of E-Payment?

Several models of electronic payment systems cater to different needs:

  • Single Payment Systems: Traditional one-time payment methods.
  • Recurring Payment Systems: Models for subscriptions and recurring services.
  • Micropayment Systems: Handling small transactions often used in digital content purchases.
  • Mobile Payment Systems: Specialized models for transactions via mobile devices.

Digital Payment vs. Electronic Payment

While often used interchangeably, digital payments and electronic payments have distinct differences:

  • Digital Payment: Encompasses all forms of payments made electronically, including cryptocurrencies and digital wallets.
  • Electronic Payment: Typically refers to payments made using traditional electronic methods like credit cards and bank transfers.

Electronic Data Interchange (EDI) in Payments

EDI is a method used to transfer payment information between businesses in a standardized format:

  • Automated Transactions: Streamlines the exchange of payment data between organizations.
  • Standard Formats: Uses specific formats to ensure consistency and accuracy.
  • Cost-Effective: Reduces the need for manual processing and minimizes errors.

Frequently Asked Questions

How Frequently is Electronic Payment Data Updated?

Electronic payment data can be updated on a daily, weekly, monthly, quarterly, or yearly basis. The update frequency depends on the provider and the specific needs of the business.

What Formats are Available for Electronic Payment Data?

Electronic payment data is commonly available in formats such as .sql, .txt, .json, .xml, and .csv. These formats facilitate easy integration with various data analysis and business intelligence systems.

What Geographic Areas Does Electronic Payment Data Cover?

Electronic payment data typically covers specific regions or countries. For example, some data cover the USA, while others might include regions like Asia, EMEA, LATAM, MENA, and India.

How Much Historical Data is Available for Electronic Payment Data?

The amount of historical data available varies by provider. Some datasets offer up to 10 years of historical data, enabling detailed trend analysis and long-term market research.

What is the Volume of Electronic Payment Data Available?

The volume of electronic payment data can be extensive, covering millions of transactions from thousands of merchants. For instance, some providers offer data from over 3,000 merchants and millions of users, with high precision tagging for detailed analysis.

How Accurate is Electronic Payment Data?

The accuracy of electronic payment data is typically high, with some providers reporting up to 100% match rates and 99% precision tagging. This ensures reliable and precise insights for business decision-making.

How Can Electronic Payment Data Be Delivered?

Electronic payment data can be delivered via methods such as S3 Bucket, REST API, and file formats including .sql, .txt, .json, .xml, and .csv. These delivery methods provide secure and efficient access to large volumes of data.

How is Electronic Payment Data Sourced?

Electronic payment data is sourced from de-identified consumer credit, debit, and ACH transactions. The data is aggregated from financial technology platforms and includes detailed information such as transaction history, account details, and merchant information.

What Privacy and Compliance Measures are Taken for Electronic Payment Data?

Electronic payment data is de-identified and aggregated to ensure privacy and compliance with industry standards. Providers apply rigorous data science practices and adhere to federal and state regulations to maintain data quality and privacy.

What is the Cost Structure for Electronic Payment Data?

The cost of electronic payment data varies depending on the provider and the specific requirements of the business. Pricing models are typically customized based on data volume, delivery frequency, and the level of detail required.

How Can Businesses Integrate Electronic Payment Data?

Businesses can integrate electronic payment data into their existing systems using the provided formats (.sql, .txt, .json, .xml, .csv) and delivery methods (S3 Bucket, REST API). This integration enables seamless data analysis and supports various business intelligence applications.

What Similar Data Types Complement Electronic Payment Data?

Electronic payment data can be complemented by other data types such as Point-of-Sale (POS) Data, Sales Transaction Data, B2B Transaction Data and SKU-Level transaction data.

Eugenio Caterino

Eugenio Caterino

Editor & Data Industry Expert @ Datarade

Eugenio is an editor and data industry expert with over a decade of experience specializing in B2B data marketplaces and e-commerce platforms. He has a strong background in data analytics, data science, and data management. Eugenio is passionate about helping companies leverage data and technology to drive innovation and business growth, ensuring they can easily and efficiently access the solutions they need.

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