Fraud Analytics Case Study: How E-Global Speeds Up Fraud Analysis and Improves IT Operational Performance

E-Global is the largest electronic payments processor in Mexico, processing more than 8 million credit and debit card financial transactions each day. Owned by BBVA Bancomer and CITI Banamex, the Company services acquiring banks, merchant retailers and issuers operating in Mexico, Brazil and Central America. They currently provide transaction switching services for a large majority of the acquiring business in Mexico, and nearly two-thirds of the Country’s 350,000 point-of-sale devices.

Case Study Challenges

Facing an average growth in electronic transaction volumes of 20 percent year over year, the ability to have analytics that can monitor the performance of credit and debit card transactions across a growing number of connections out to financial institutions, banks, and retail merchants was a major requirement for E-Global. The IT operations team needed to quickly isolate operational performance issues, while the fraud detection team needed to ensure transaction messages and data flows had not been altered or tampered with. This required real-time monitoring and data streaming analytics that would provide a correlated, end-to-end view into the four segments of every transaction:

  1. From the acquirer to the E-Global switch
  2. From the E-Global switch to the issuer
  3. The response from the issuer back to the E-Global switch
  4. From the E-Global switch to the merchant

Easy access to security-related transaction message fields and metadata for fraud analysis was also important to E-Global’s fraud detection team. This included data such as:

  • Message types
  • Card numbers
  • Amounts
  • Transaction dates and times
  • Fraud response codes
  • Terminal ID’s
  • ISO 8583 messages

Case Study Solution

E-Global worked closely with system delivery and service provider Moneta Technologies (Stratus Technologies Mexico) to find a transaction-level monitoring solution that could provide the end-to-end data capture, real-time alerting and open data streaming they needed to share this data between both IT operations and fraud teams. They chose INETCO Insight® as their fraud analytics to improve IT operational performance and fraud analysis.

Case Study Results

The IT operations and fraud detection teams now have access to accurate and consistent real-time transaction data for fraud analysis with machine learning capabilities. They can select the real-time transaction data most relevant to them and either use INETCO Insight to view this data or forward it to their preferred fraud management environment. Benefits of the fraud detection solution include:

The delivery of a more secure, undisrupted customer experience

  • Reduced risk of service disruption by spotting and resolving potential fraud attacks and operational performance issues faster
  • Improved protection against chargebacks, service level agreement penalties, security breaches and other legal situations and liability shifts
  • More flexibility when it comes to implementing real-time alerting and applied business analytics

An improved ROI by extending the use of transaction data across IT operations and fraud detection teams

  • Access to a trusted, reliable source of quality transaction data that can be leveraged and repackaged for multiple business use cases thanks to machine learning capabilities
  • Creation of a centralized data repository that can be used across IT operations performance, interchange compliance rules and fraud detection
  • An easy way to verify the speed and reliability of transaction switches and customer-facing applications

Faster average mean-time-to-repair

  • Shortened customer fraudulent transactions complaint process from 90 days to a few hours
  • Reduced resource cycles traditionally associated with capturing, preparing and analyzing this data
  • Faster response times to issues such as too many transaction rejections from one of the banks, or unusually slow transaction response times