23%

Improvement in Merchant Compliance Rate

57%

Capture of Average Transaction Value

47%

Reduction in Fraud Detection Rate

26%

Increase in Chip Card Adoption Rate

This credit card analytics dashboard centralizes performance, security, and usage trends for chip enabled payment cards. Financial institutions, payment processors, and businesses use it to track transaction volumes, fraud rates, and customer adoption, and to decide where to tighten payment security. Infocepts built it on Power BI.

What problem did this dashboard by Infocepts solve for the financial institution?

Institutions need to watch how chip enabled cards perform, how secure they are, and how customers use them. Infocepts brought transaction, fraud, and adoption data into one interactive view through data engineering and integration. Teams no longer have to depend on periodic batch reports to see what is happening.

What does the credit card analytics dashboard track?

It tracks transaction volumes, fraud rates, and customer adoption of chip enabled cards. Segments follow however an institution reports, by region, product, or channel. The dashboard also lists merchant compliance rate and average transaction value. The visualizations are interactive, so users can work from one view rather than several reports.

Who uses credit card analytics dashboards in Financial Services companies and how?

Fraud teams use them to watch unusual transaction patterns and start investigations sooner. Payment processors monitor volumes and processing efficiency. Card leaders track chip card adoption by region, product, or channel. Businesses that issue or process credit cards use them to monitor security and usage at scale.

What business impact did the financial institution see after rollout?

Reported results include a 23% improvement in merchant compliance rate and a 26% increase in chip card adoption rate. It also lists a 47% reduction in fraud detection rate and 57% capture of average transaction value.

Key metrics: transaction volumes, fraud rates, chip card adoption, merchant compliance rate, and average transaction value.

Explore more examples in the Financial Services section, see the transaction analytics for banks dashboard, or review the financial analytics for banking dashboard.

Want a credit card analytics dashboard for your institution? Talk to our team about what to track and how to build it.

Frequently asked questions

Credit card analytics is the analysis of card transactions, fraud, and customer usage to understand performance and risk. A dashboard puts those measures in one view. Issuers and processors use it to see volume trends, spot unusual activity, and track how customers adopt chip enabled cards.

Show fraud rates over time, split by region, product, or channel, and place them next to transaction volumes so the rates have context. Add average transaction value to see whether suspicious activity differs from normal spending. Trends matter more than a single day, so keep a clear time axis.

Banks usually compare chip enabled cards in use with the cards issued, then break the result down by region, product, or channel. A trend line shows whether adoption is rising. Read it next to fraud rates to see whether adoption and payment security are moving together.

That depends on how data reaches the dashboard. Batch feeds show yesterday’s activity. A streaming feed can show unusual transaction patterns in near real time, which gives fraud teams a head start on investigation. The faster the feed, the sooner an analyst can look at a suspicious pattern.

Start with the questions fraud, payments, and card teams ask each day, then connect the transaction and fraud systems that answer them. Design the views around those users and test with real analysts. Infocepts handles this work through data product design, so the dashboard fits how financial teams work.

The dashboard reports what is happening with cards: volumes, fraud, and adoption. The Real Time Data Streamer is an Infocepts accelerator that moves data between transactional and analytical systems. It turns a once a day batch into an all day stream, so it can feed the dashboard fresher data.