INETCO Solutions for Retail POS and E-Commerce

INETCO Solutions for Retail POS and E-Commerce

Drive payment revenue and deliver a seamless omni-channel experience across POS, self-service check-out and e-commerce with data analysis

Helping retailers, merchant acquirers and payment service providers perform POS and e-commerce data analysis to guarantee the completion of every transaction

Delivering a seamless customer experience across between online and bricks & mortar store fronts is the key to growing revenue and customer loyalty. But expanding payment options and increasingly complex retail network infrastructures have resulted in a growing number of  incomplete and lost transactions.

INETCO solutions are designed to help retailers, merchant acquirers and payment processors account for every card-present and card-not-present interaction in real-time, and deliver more valuable payment services across POS and e-commerce environments.

  • Make sure every omni-channel payment completes as the consumer expects – without risk of failures, fraudulent activity or unexpected declines.
  • Analyze and forecast shifts in consumer buying behavior across POS, self-service check-out, in-store pickup and e-commerce applications using POS and e-commerce data analysis 
  • Detect suspicious card-present and card-not-present payment fraud activity in real-time thanks to POS and e-commerce data analysis.

INETCO Insight use cases for the POS and E-commerce channel

Analysis and forecasting of revenues and consumer usage

Analyze consumer spending behavior and shifts in POS, Mobile and Online channel usage. Retail payment data can be broken down by dollar amounts, device or geographic location, merchant, card types, POS terminal or register types (ie: self check-outs, online carts, kiosks, lanes). Run predictive algorithms and machine learning models against this data, and predict swings in buying habits. Also analyze incident rates by location and lost revenue by device failure or timeouts.

Card-present and card-not-present payment fraud detection

Set real-time triggers to minimize card fraud, reversals, stand-in modes and EMV fallbacks. Immediately detect high-risk activity patterns such as large purchases, repeat card declines, unusual rapid activity on a specific POS terminal, card or customer ID, and high gift card redemptions. Identify missing transaction links indicative of “man-in-the-middle” switch malware attacks.

Real-time event monitoring across POS, self-service and digital payment channels

Quickly isolate transaction performance issues, failures and bottlenecks by card type, payment application, payment rail, POS device or store location. Make sure digital wallet interactions that are getting more complex — such as contactless, card-not-present, just-in-time promotions and cross channel transactions — complete as expected.

Transaction profiling and research into payment slowdowns and failures

Diagnose mysteries around transactions that are “lost” — monitor transactions across multiple transition points and isolate POS, third party payment application, network, payment switch and authorization host issues in real-time. Speed up troubleshooting by ~85% by seeing both the application payload and network communications details – all in one view.

Real-time card risk scoring and reducing false declines

Improve the precision of card risk scoring by configuring rules-based alerts and machine learning models to update individual models each time a transaction occurs. Flag, rank and investigate behavioral patterns that signal potential fraud.


Set up automated scripts to block high scoring card transactions at the firewall port or network layer. Speed up the analysis of flagged card payments by ~75%.

payment switch performance monitoring

Identify longer than average processing times, round trip times and queue times. See events that are internal to the switch and combine OS statistics, performance counters, application process statistics and application process log file data with the state of your transactions. Add additional security for the payments switch against malware attacks.

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.

Payment intelligence acquisition, data streaming and forwarding

Create a centralized source of transaction data across all retail channels – continuously updated in real-time. Improve the delivery speed and availability of payment data – to any teams or analytics applications that need it.