Monitor Plus DBFD™ 

Digital Banking Fraud Detector

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Fraud Prevention in

Mobile and Web Banking

Monitor Plus DBFD™ (Digital Banking Fraud Detector) is a comprehensive solution that prevents external and internal fraud in digital banking (mobile and web). This system helps reduce loss, improves customer experience and loyalty with its low-friction interaction.

 

Continuous monitoring and prevention in different moments and irregular situations:

Before Session

  • Onboarding fraud prevention.

  • Detection of user credentials affected by data breaches.

  • Suspicious alterations to customer contact info or balances, limits, etc.

During Session

  • Comprehensive analysis of customer and session elements (session behavioral biometrics and advanced behavioral biometrics through deep learning neural networks, device properties, data access routes, geolocation analysis, statistical profiling of origin and destination accounts, regions, origin and destination banks, consultations and internal administrative operations).

  • Detection of Man-In-The-Middle, malware and trojans, Phishing and its variants, fake apps, and hacker environments (emulation techniques, and device rooting and hacking).

  • Generation of second authentication factors. 

  • Detection of internal fraud patterns.

After Session 

  • Control over unusual withdrawals in accounts that have recently received funds.

 

 

Monitor Plus DBFD™ (Digital Banking Fraud Detector) interacts with the institution’s authorized in real time. It can deny high-risk transactions and/or executive alternate validation processes (Strong Customer Authentication – SCA). The system includes a wide array of validation methods (challenge library) so that the customer may confirm their identity. The model also includes an automatic defense system that can block accounts, channels, regions, decrease limits, etc. in situations that merit such actions (ex. Massive fraud attacks).

Multi-layer protection

The detection model protects the five layers of the suggested Gartner® model to treat fraud risks in digital banking:

 

Entity Link Analysis

Detection of common points of fraud and correlation with administrative operations through neural networks and LightGBM decision trees.

Customer Cross-Channel/Product Analysis

Comprehensive transactional correlation (when combined with other Monitor Plus® products).

Channel Monitoring

Digital channel behavior-based account monitoring and fraud detection.

Behavioral Analysis During Session

  • Detection of navigational habits to confirm identity.

  • Detection of data alterations by malware, spoofing, emulation techniques, rooting and hooking.

End Point

  • Advanced behavioral biometrics.

  • Detection of device, network and TOR environments, IPs, suspicious proxies, and alterations to data in transit.

  • Detection of Man-In-The-Middle (MITM) and Man-In-The-Browser (MITB).

Exploit Your Data

The Monitor Plus Analytics™ submodule may be acquired additionally. This is an information management system that provides customized consultations and managerial reports. This tool enables a quick and effective visual data analysis to optimize decision-making on accurate data.

This system can be used as a basis to analyze system or team performance through various consultations (as per requirement). For example:

Alert Viewer

Digital Onboarding or WEB/APP Transfers

  • Number of cases in Alert Viewer.

  • Cases grouped by different criteria.

  • Pending alerts per investigator.

  • Alert summary.

Investigation Cases

Digital Onboarding or Web/APP Transfers

  • Customer profile by investigation case.

  • Number of cases by result and period.

  • Productivity by analyst.

  • Range of amounts and cases by list of criteria.

  • Cases by different grouping criteria.

  • Device GPS location.

  • Cases by country - OP.

  • Top N IP's

  • Grouped investigation cases.

  • Case evolution by browser.

  • Crossed dimensions.

This tool is accessible through smart devices and allows the user to define a friendly presentation format for data, easily grouping different criteria to combine multiple data sources in a single view.