UK Row-level Transaction Data - Sample

PII-Cleansed row level data highlighting both credit and debit transactions, income, and demographic details for a growing panel of opted-in consumers. This includes enhanced merchant tagging for over 1700 merchants and over 380 publicly listed companies.

What makes Exact.One unique?<br/>ClearScore provides consumer debit and credit card data at a transaction level and the data is updated daily:

- The data is made available directly from open banking connections that users have through ClearScore.
- A large active panel of 650K users contributing to over 20 billion in spend. Over 2.5 million users overall.
- Historic view of data spanning 7 years.
- Mapped to 380+ publicly listed companies.

What is the panel size?<br/>More than 650k users are actively sharing their Open Banking data and this is growing monthly as we acquire more users.

How do I receive the data?

1. Snowflake DataShare

What’s the structure of the data?

- Raw transactions.
- Custom or aggregated datasets upon request

What is the quality of the panel?

- The users who we have acquired have a re-auth rate of ~70%.
- 1700 merchants tagged, mapping to 380 tickers, 200 of which are UK publicly listed

Exact.One is built on an industry-leading transaction categorisation service

- Our categorisation service is a rules based deterministic model which favours accuracy over coverage
- We focus on accurately categorising spend at merchants, as well as spend pertaining to credit risk (e.g. income, gambling, benefits, financial institutions, cash withdrawals, and debt management services)<br/>

Sample Table:<br/>TRANSACTIONS - Row level transaction data

Sample Fields:<br/>AGE_BAND<br/>SALARY_BAND<br/>POSTCODE<br/>TRANSACTION_DATE<br/>ACCOUNT_TYPE<br/>MERCHANT_NAME<br/>AMOUNT

For information regarding the complete dataset please contact [e-mail]

Check out our website here -> https://www.exactone.io/

搜集汇总

背景与挑战

背景概述

该数据集为英国行级交易数据样本，包含去除了个人身份信息的借记卡和信用卡交易记录，同时涵盖收入与人口统计信息。数据来源于开放银行连接，拥有超过65万活跃用户，历史数据跨度7年，覆盖1700多家商户和380多家上市公司，并通过基于规则的分类模型确保准确性。