CFS Analytics Data Connector

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.

Common Use Cases

Some of the common use cases for this solution include:

  • Implementing targeting programs that offer products and services to members who are likely in the market for products.
  • Daily / Monthly automated measurement of organizational Key Performance Indicators
  • Competitive analysis with other financial institutions vying for member’s share of wallet.
  • Member fee analysis in response to regulatory, compliance or member relationship purposes.
  • Member engagement, retention and cross sell initiatives
  • Data integration to CRM and user journey / workflows being implemented by the credit union.

Common Questions

All transactions that exist on the core that make a material change to an account balance are included

CFS has reduced the number of columns to include only those of the highest analytical value.

Yes, while CFS will make many of the updates independently, the Credit Union is able to review the classifications and make sure that they fit their specific needs.

Yes, CFS offers several native integration (PSCU, TMG, FIS) where the transactions can be pulled from the source system and integrated in to the primary transaction table.

CFS does not try to classify every transaction perfectly as many transactions are not required to be classified (i.e. transfer from checking to savings). Most of the high value transactions are automatically classified without intervention.

The MCC descriptions and classifications are a mixture of sources including the IRS, Visa, and CFS expertise around grouping the MCCs together.

Technical Details

Following summarizes the technical details of the Analytics Data Connector:

  • Native transactional support exists for  Episys/ARCU, PSCU, FIS and Co-Op/TMG.
  • Example Dashboards available in Power BI and TIBCO Spotfire.
  • The Data Connector can be deployed on a Microsoft SQL Server 2014 or higher database.
  • A configurable dictionary is maintained to allow for changes in merchant information over time.

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- CFS Data & Analytic Products

The CFS Insight way to unlocking your credit union data

Data connectors and CFS analytical models are just tools. To succeed, your data initiative needs the right process to handle the preparation, detailed integration, and well planned training and support. The CFS process will help guide your project to successful implementation and adoption.

CFS Insight Process

Step 1

Discovery Call & Demo

Start with a quick discovery call followed by a customized demo. CFS will seek to answer specific questions and show how the CFS process will apply to your data needs.

Step 2

Review Agreement

Work with the CFS Insight team to define goals and project requirements. Develop a scope of work and review with any other key stakeholders and make adjustments.

Step 3

Onboard & Prerequisites

As your team works on required prerequisites defined in the agreement, CFS will onboard to your technology environment and begin preparing for implementation.

Step 4

Implement, Train, Support

CFS will Implement the data connectors and analytic models, provide your team with training, help push your new solution to production, and provide you with dedicated ongoing support and consultation

Predictive analytics in banking for credit unions - CFS Insight

- How CFS Insight can guide you

Ready to make better data driven decisions?

CFS Inight’s process will guide you and your team into a better understanding of your data. Once your systems are connected, CFS will help you create productive ways to access, analyize, and model your data. So the question is — how can we help?
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- About CFS Insight

Why CFS Cares About Credit Unions

Credit unions want to serve their communities well. Their community may be a region, organization, or identity. But, not matter what their community looks like, credit unions want to see the their people thrive.

That’s why for more than a decade CFS Inisght has helped credit unions like your’s not only survive, but thrive!