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What is eFraud Investigator?
eFraud Investigator converts a variety of financial documents, including bank statements, credit card statements, and PDFs, into transaction data that meets legal standards, serving the requirements of forensic accountants, fraud investigators, lawyers, and governmental organizations. This innovative tool functions without templates, adeptly processing both scanned and digital documents from any financial institution while guaranteeing data accuracy. Each transaction undergoes thorough validation against the printed balances from the bank, incorporating running balances for each line and daily balance tables when relevant, which helps to illuminate any discrepancies that may occur. If reconciliation does not succeed, the software pinpoint specific transactions involved in the inconsistency. Users benefit from the ability to see the original PDF page next to the extracted data, enabling them to correct inaccuracies or add missed transactions, all modifications are recorded in a tamper-evident audit trail. The tool identifies different versions of counterparty names without automatically merging them, thus leaving it to the reviewer to decide on grouping, which maintains accountability and reversibility in the process. Furthermore, it monitors the movement of funds, uncovers patterns of structuring and round-dollar amounts, and has the capability to export verified data in Excel, PDF, and CSV formats. The service is offered at a rate of $0.75 per page, with a promotional deal allowing access to the first 50 pages free of charge and without requiring a credit card. In addition, the tool significantly boosts the efficiency and precision of financial investigations, rendering it an essential asset for professionals in this domain, ultimately contributing to more thorough and reliable analyses.
What is RiskNet?
The aiRiskNet® platform operates as a self-service rules engine for real-time and near real-time detection and prevention of payment fraud and suspicious activities, catering to card issuers, acquirers, payment service providers (PSPs), and merchants around the world. This adaptable solution can be implemented as either licensed software on-premises or through a cloud-based service on Azure. Engineered to protect the entire payment ecosystem, aiRiskNet® features a modular design with three main configurations that can operate independently or be seamlessly integrated into a broader enterprise solution. Notably, aiRiskNet® Acquirer is dedicated to managing risks associated with merchants and identifying fraud across various payment channels, such as point-of-sale (POS) and ATM transactions. On the other hand, aiRiskNet® Issuer specializes in fraud detection for financial entities and card issuers, covering all types of card payments, including credit, debit, pre-paid, private label, and e-wallets, while also addressing other payment mechanisms like cheques, ACH, and wire transfers. This flexibility allows users to combat fraud effectively, aligning the solution with their individual operational requirements. Additionally, the platform provides ongoing updates and enhancements to adapt to the ever-evolving landscape of payment fraud.
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Integrations Supported
API Availability
API Availability
Pricing Information
$0.75 per page
Free Trial Offered?
Pricing Information
Pricing not provided
Free Trial Offered?
Supported Platforms
SaaS
Supported Platforms
SaaS
On-Prem
Customer Service / Support
Standard Support
Customer Service / Support
Standard Support
Web-Based Support
Training Options
Documentation Hub
Webinars
Online Training
Training Options
Documentation Hub
Webinars
On-Site Training
Company Facts
Organization Name
eFraud Services
Date Founded
2020
Company Location
United States
Company Website
efraudservices.com
Company Facts
Organization Name
The ai Corporation
Date Founded
1998
Company Location
United Kingdom
Company Website
www.aicorporation.com/products-services/risknet/
Categories and Features
Fraud Detection
Not specified
Categories and Features
eCommerce Fraud Protection
Not specified
Fraud Detection
Not specified