Most credit unions recognize the value they have in member transactional records but very few are able to produce the insights they desire. The problem is multi-fold with the complexity of the transactions being spread across multiple tables, records, and days. Text values for payee and merchant information is text-based with varying patterns to represent the same entity along with credit card transactions separated into other non-core platforms.
The CFS Transaction Analytics connector solves several critical issues. First, it restructures the transactions into one transaction equals one record. This makes the transactions significantly better for analytics. The connector also cleans and classifies the transactions so that they have more value. Transactions from credit card platforms are also consolidated into the model providing a holistic view of both debit and credit card activity.
Credit unions are able to monitor and assess member spend with specific merchants and categories of merchants across debit and credit platforms. In addition, executives and analysts can evaluate the member relationship with other financial institutions to improve their share of wallet and assess the impact of future marketing investments using a data driven approach. The transactions are also foundational for understanding member retention, spend, loan analytics, charge off prediction, and fee analysis.