INETCO understands that your payment transaction environment is a “one of a kind.” Our professional services team is here to make sure all of your INETCO Insight product configuration and data extraction needs are met in a timely, successful fashion. Whether it is creating dynamic analytics dashboards, configuring real-time alerts and statistics, designing machine learning models or configuring case management workflows specific to your payments environment, INETCO has the payment data experience to help.
Guarantee INETCO Insight is configured to meet all your data acquisition, monitoring and analytics needs
Customizing analytics dashboards and on-demand reporting
The INETCO Professional Services Team is committed to helping you get the most value out of your payment transaction data. Our skilled team of data scientists specialize in extracting “ready to analyze” data from INETCO Insight in real-time, reducing the resource time and effort it takes to collect payment data across disparate data stores, card rails and payment channels. This transaction data forms the foundation of interactive dashboards, predictive forecasting and on-demand reports – built within any analytics application of choice – including Tableau, Microsoft Power BI and Jaspersoft.
Providing the data visualization you need to optimize your business
- Customer Usage – How, when, and why are customers engaging with my organization?
- Card Profitability – Which cards in my portfolio are the most profitable?
- Cash Forecasting – What cash points are running low on cash? Which have too much?
- Channel Performance – How are failures and outages impacting revenues and customer experience?
- Device Placement – How are my devices being used, where do we require new placement, removal or relocation?
INETCO analytics dashboard examples
Configuring INETCO Insight event monitoring, rules-based alerts and interval statistics
The INETCO Professional Services Team is here to guarantee every end-to-end transaction is screened from both a performance and fraud perspective in real-time. We help our customers decrease the white noise of overactive performance monitoring alerts. We work with you to configure the event monitoring, rules-based alerts and device interval statistics you need to speed up both the reactive investigation and proactive identification of transaction-level fraud attacks.
Real-time alert bundles are available for payment fraud detection, transaction performance, switch application performance management and channel systems management – across ATM, POS, digital, card or real-time payments environments.
Example alerts for transaction performance monitoring and payment fraud detection
A rise in transaction declines, unexpected EMV fallbacks, consecutive magnetic stripe transactions or reversal rates
For a certain BIN range, card type or group of self-service devices
Isolating terminals used in a coordinated ATM cash-out attack
Creating visibility into implausible transacting scenarios, such as multiple devices or countries where the same card is being used in a limited period
Distance-based card fraud
Knowing when the same card is being used for two consecutive device transactions that are not physically possible or likely
Missing back-end transactions for identifying “man-in-the-middle” attacks
Fake processing where a transaction enters the payment switch, but never reaches host for authorization due to switch malware or card compromise
Excessive transaction clearing or stand-in transactions by the switch
Over a set amount of time
Configuring real-time machine learning and risk scoring capabilities
The INETCO Professional Services Team knows how to match and configure machine learning models and predictive algorithms to the requirements outlined, such as cash forecasting, predicting card usage and fraud risk scoring. Our self-learning algorithms are built on newer methodologies such as Isolation Forest and XGBoost, incorporating seasonality, individual real-time transaction events and in-depth transaction data to increase precision. Both supervised and unsupervised machine learning algorithms are used in conjunction to assess the validity of a transaction.
SUPERVISED MACHINE LEARNING
Supervised machine learning models automatically learn from labeled fraud cases and are able to detect fraudulent behavior patterns based on previously confirmed fraud cases. In this way, these models reduce the amount of anomalies mistakenly detected.
UNSUPERVISED MACHINE LEARNING
Unsupervised machine learning models look at anomalies per customer based on past behavior. In this way, the unsupervised machine learning model is able to detect fraudulent patterns that have not previously been seen.
Configuring case management and workflows
INETCO Insight hosts case management features and logical workflows that can be configured by the INETCO Professional Services Team to help meet your triage checklist requirements, create an audit trail and speed up the investigation of flagged transactions. You will be only one click away from getting all the transaction details you need to see.