Card Operations Teams

Card Operations Teams

Stay on top of payment card profitability while delivering best-in-class service performance

Helping card operations teams increase the value, safety and stability of every card transaction

The payment card business is currently under a lot of strain, as card operations teams face the difficult job of balancing amazing customer service with revenue concerns. Keeping a customer engagement strategy successful and profitable requires constant analysis of shifting consumer buying behaviors. Delivering stable card rails and adopting a payment security strategy that keeps you ahead of the fraudsters exploiting the surge in digital transactions will have a positive impact, as well.

This is where INETCO Insight helps.

How card operations teams benefit from INETCO Insight

  • Gain real-time insights into customer buying trends to find credit-worthy customers, maximize engagement and deepen wallet share across self-service and digital channels.  
  • Increase successful payment transactions by making sure they are not abandoned due to performance issues on the end-to-end transaction path.
  • Roll out card-present, card-not-present and mobile wallet programs in a safe and reliable way.
  • Analyze interchange fees, card program charges and loyalty fees to make more impactful decisions around payment revenue and card profitability. 
  • Understand customer spend by card, merchant category and mobile wallet usage to align habits with the right cards and rewards programs.
  • Detect payment card fraud and cybersecurity attacks in milliseconds – configure real-time risk scoring models to keep false positives to a minimum.

Use cases for card operations teams

Card usage analysis and behavioral forecasting

Deepen knowledge of credit, debit, prepaid card and mobile wallet usage. Analyze usage by card type, activation status, renewal status, location, PAN entry mode and channel type. View transactions by merchants, purchase amounts and volumes. Improve customer segmentation, reduce the risk of card program cannibalization and improve engagement through better rewards alignment. Use predictive models to identify credit-worthy bank customers.

Real-time performance monitoring of end-to-end card rails, digital wallet and host authorization connections

Monitor card present and card-not-present transactions in real-time. Quickly isolate and remediate performance issues or failed transition points affecting debit, gift card or credit card transaction completion. With a comprehensive view of every end-to-end transaction journey you can identify activities that would fly under the radar of individual security components.

Rules-based payment fraud alerts for card-not-present transactions

Instantly detect suspicious transaction patterns and missing transaction links in milliseconds. Identify account take-over attacks, BOT and DDoS attacks, phishing attacks, device fingerprint and IP geolocation changes, high purchase velocity, high ticket purchases, and repeat customer ID usage by mobile/online application, distance or store.

Payment fraud alerts for card-present transactions

Combine multi-point transaction monitoring, rules-based alerts and machine learning models to detect suspicious transaction patterns and missing links in milliseconds. Match card usage to negative countries and blacklists. Be alerted to “man-in-the-middle” malware attacks, EMV fallbacks, stand-in modes, reversals, rapid cash-out attacks, repeat card usage by device, distance or store, and high ticket purchases. Identify when there is suspected compromise of cryptographic Key security or Cardholder PINs.

Real-time card risk scoring and machine learning

For card operations teams to truly detect payment fraud in real-time, their fraud solutions do not have the luxury of time to rebuild the customer risk model as an end of day process. Reduce customer friction and false positives by customizing machine learning and rules-based alerts for your unique payment environment. Rebuild card models every time an event occurs, and immediately flag behavioral patterns that deviate from past card transactions for investigation

Card portfolio profitability and forecasting

Understand how all your card programs are contributing to revenue. Analyze the breakdown of interchange fees, card program fees and interest margins per transaction. See how many payment cards are being successfully activated within digital wallets. Understand if reward programs are consuming too large a portion of your revenues.

Isolating root cause of performance issues causing transaction delays, unexpected declines or failures

Automatically construct a full profile for each end-to-end transaction. Extract and assemble application payload messages, metadata, response/request timing and network communications information – across correlated transaction links – to speed up mean-time-to-detect and remediation efforts. These are the features upon which the rules-based alerts engine and different machine learning models will assess the validity of a transaction.

Regulatory compliance and transaction audits

Independently log every transaction in real-time – while remaining out-of-band and not adding latency to the payments switch. Conduct a true, real-time audit into every link along an end-to-end payment transaction journey. Capture mandatory audit and security fields such as message types, card numbers, amounts, transaction dates and times, response codes, terminal ID’s and ISO 8583 messages. Be instantly aware of suspect fraud activity, hacking attempts and security incident events related to invalid MAC values, invalid PIN blocks, MAC failures, MAC Key synchronization errors, HSM failure errors and server timeouts.

Blocking card transactions at the firewall

Set up automated scripts to block high scoring card transactions at the firewall port. Take action to reduce false positives.

Data forwarding for fraud, channel management and analytics applications

Acquire, decode, correlate and forward rich real-time transaction data to any team or application of choice. Blend this data within other fraud, channel management and analytics platforms that require it. This includes message fields such as transaction type, amount, response codes, terminal IDs, card types, dates, transaction status and message types.

BIN Trolling Attacks

View authorization volumes that are approved and declined in the same dashboard. Identify when decline rates spike, indicating the possibility of a BIN troll attack. Spot high volume usage patterns on virtual merchant terminals that indicate a merchant has been phished and their credentials are being used by fraudsters.