Every credit union has data. But having data is not the same as knowing what to do with it. For many institutions, turning transaction data into meaningful insights requires technology, specialized talent, and ongoing investment that can be difficult to build and maintain.

MAP and AiVantage took a different approach. By combining MAP’s payments expertise and credit union network with AiVantage’s data, analytics, automation, and AI capabilities, the two CUSOs created a shared analytics environment designed to make complex transaction data easier to understand and act on.

From hourly data refreshes and executive dashboards to peer benchmarking and fraud intelligence, the solution demonstrates how existing data can become a powerful business asset. The result: faster access to intelligence, expanded analytical capabilities, and a model that can deliver advanced analytics without requiring every credit union to build the infrastructure alone.

This case study explores:

• How MAP transformed its transaction data into a shared intelligence platform
• How AiVantage built the technology and analytics foundation behind MAP Data
• How peer benchmarking provides a broader view of credit union performance
• How shared infrastructure can expand capabilities while reducing technology costs

Explore the full case study to see how two CUSOs turned an existing data asset into a new source of intelligence and value.