Fraud Detection Machine Learning Case Study: Exploring INETCO’s Case Management Engine to Speed up Payment Fraud Investigations and Reduce False Positives

INETCO thrives on helping financial institutions deliver an amazing customer experience through optimized transaction performance, faster detection of transaction-level fraud and maximized business value from payment intelligence. Our core competency lies in our ability to decode a wide variety of payment protocols on-the-fly, making comprehensive transaction data ready for real-time analysis. FIs can continuously feed this data to rules-based alerts, configurable risk scoring and machine learning algorithms, analytics dashboards and now…drumroll please…the INETCO Insight case management and workflows engine.

fraud prevention team member using machine learning to detect and prevent payment fraud
Read the whitepaper titled, “INETCO Insight – Machine Learning and Risk Scoring for Real-time Payment Fraud Detection and Prevention.”

INETCO Insight features case management and workflows that help our customers promote real-time collaboration, establish a simplified triage system and speed up the investigation (and blocking) of suspicious transactions.

Seamlessly combined with the real-time data collection, rules-based alerting, risk scoring and machine learning capabilities also contained within INETCO Insight, this module provides a systematic and repeatable process for tracking, evaluating and prioritizing flagged transactions. Logical workflow rules help streamline fraud investigations, with risk scores, alert specifics and suspicious transaction details linked directly to each task.

a screenshot of inetco insight's fraud case management dashboard
Screenshot 1: Here’s an example of what happens when an alert triggers a task in INETCO Insight’s case management and workflow system. At this point, notification is automatically sent to the fraud analyst team, and an analyst can claim this task and start working through their triage checklist. You can see that this task was triggered because the card risk score is high, mainly due to the withdrawal amount, and the distances between the usage points of this card, or velocity, being higher than normal. The task window can also show KYC and other account details from your banking system. 
a screenshot of the inetco insight platform performing real-time rules-based alerting & machine learning
Screenshot 2: Within one click, get to all the transaction details you need to see….
screenshot of the inetco insight platform detecting potential payment fraud attacks in a customized workflow.
Screenshot 3: Work through your triage task checklist, and gain a visual as to where you are in the workflow steps. Create and customize new checklists, workflows and workflow steps that align to your triage processes.

With real-time payment data acquisition and the right combination of rules-based alerts, configurable machine learning, case management and workflow capabilities, FIs can implement more precise risk scoring, transaction blocking and investigation tactics to speed up investigation and reduce the amount of false positives associated with traditional payment fraud detection. For more information on how INETCO professional services can get you started with our case management customization package, contact .