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What is CPA Fraud Detection Service?

Benford's law is an effective method for revealing patterns that may indicate fraudulent disbursements. It requires the analysis of audit trail reports from accounting software such as QuickBooks to identify suspicious actions like voids and deletions. Moreover, it also includes the detection of multiple payments made for the same amount on a single day. A comprehensive examination of payroll runs is performed to find any discrepancies, particularly payments that exceed designated salary or hourly rates. Payments made on days when businesses are closed are given extra attention. By employing statistical analyses, outliers that could point to fraud are uncovered, and duplicate payments are verified for accuracy. Furthermore, vendor files in accounts payable are scrutinized for names that may appear strikingly similar, leading to investigations into potential fictitious vendors. Comparisons of vendor addresses and payroll information are assessed through Z-Scores and relative size factor tests. Although data monitoring and unexpected audits have proven to significantly mitigate fraud losses, merely 37% of organizations have implemented these vital controls. For smaller businesses with fewer than 100 employees, the average estimated loss attributed to fraud stands at $200,000, underscoring the fact that these enterprises typically lack sufficient resources to effectively identify and respond to fraudulent activities. Therefore, it becomes crucial for small businesses to embrace more robust fraud detection strategies to protect their financial health and ensure long-term sustainability. By doing so, they can not only detect irregularities but also foster a culture of transparency and accountability within their operations.

What is Frogo?

Frogo is a robust AI-driven fraud detection solution built to safeguard revenue and reduce losses for organizations operating in high-risk industries such as iGaming, payments, e-commerce, forex, banking, dating platforms, and delivery services. The platform addresses a wide variety of fraud cases, from account takeovers and internal fraud to bonus abuse, affiliate fraud, SMS-based scams, and multi-accounting. It detects anomalies by analyzing login patterns, transaction flows, promotional activity, and affiliate behavior, ensuring that fraudulent activity is intercepted before it escalates. Frogo’s hybrid approach leverages static rules, dynamic scoring, and AI predictions, allowing companies to adapt rapidly to evolving fraud tactics. Businesses can create new policies or refine existing ones with customizable scoring engines while monitoring transactions with real-time updates and alerts. Investigators gain access to enhanced analytics and case management tools, helping them pinpoint vulnerabilities and strengthen compliance workflows. The system also integrates blacklist and whitelist management, enabling precise control over user activity. For companies with unique fraud challenges, Frogo can be tailored to specific use cases, providing bespoke protection strategies. With ISO27001 certification and Swiss Approval compliance, it ensures enterprise-grade security and trust. By combining predictive technology with operational flexibility, Frogo transforms fraud prevention into a competitive advantage.

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Media

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Integrations Supported

Additional information not provided

Integrations Supported

Additional information not provided

API Availability

API Availability

Pricing Information

$1,400 one-time payment

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

On-Site Training

Training Options

Not specified

Company Facts

Organization Name

MedCXO

Company Location

United States

Company Website

medcxo.com/fraud/

Company Facts

Organization Name

Frogo.ai

Date Founded

2025

Company Location

Cyprus

Company Website

frogo.ai/

Categories and Features

Fraud Detection

Not specified

Categories and Features

Fraud Detection

Not specified

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