Vendors
日本語

Fraud & abuse detection system

Create a vendor selection project
Click to express your interest in this report
Indication of coverage against your requirements
A subscription is required to activate this feature. Contact us for more info.
Celent have reviewed this profile and believe it to be accurate.
We are waiting for the vendor to publish their solution profile. Contact us or request the RFX.
Projects allow you to export Registered Vendor details and survey responses for analysis outside of Marsh CND. Please refer to the Marsh CND User Guide for detailed instructions.
Download Registered Vendor Survey responses as PDF
Contact vendor directly with specific questions (ie. pricing, capacity, etc)

Overview

NovoAI’s Fraud Detection System is a powerful AI-driven solution designed to identify and mitigate fraudulent activities in insurance claims. The system uses advanced machine learning algorithms and pattern recognition to analyze vast amounts of data in real time, detecting suspicious behaviors and anomalies across multiple data sources. By automating fraud detection, NovoAI helps insurers minimize financial losses, protect their bottom line, and maintain compliance with regulatory standards.

The solution goes beyond traditional rule-based systems by incorporating dynamic behavioral models, making it highly effective against both known and emerging fraud schemes. It integrates seamlessly with existing claims management platforms, providing insurers with actionable insights and automated alerts for faster decision-making. Currently trusted by leading insurers, NovoAI’s Fraud Detection System has proven to significantly reduce false positives while ensuring genuine claims are processed quickly.

Key Features

1. Advanced Pattern Recognition and Anomaly Detection:
- Uses machine learning models to detect unusual claim patterns, inconsistencies, and outliers.
- Identifies common fraud tactics such as inflated claims, duplicate submissions, and staged accidents.

2. Dynamic Behavioral Modeling:
- Continuously updates risk profiles based on claimant behavior, historical data, and external factors.
- Learns and adapts to new fraud schemes, providing proactive protection.

3. Multi-Source Data Integration:
- Analyzes structured and unstructured data from multiple sources including policy information, medical records, and external databases.
- Cross-references data points to spot discrepancies and hidden connections.

4. Real-Time Alerts and Case Flagging:
- Generates real-time alerts for suspicious claims, enabling quick investigation.
- Prioritizes high-risk cases and provides actionable insights for fraud investigators.

5. Risk Scoring and Predictive Analysis:
- Assigns a risk score to each claim based on various parameters and predictive models.
- Helps prioritize and categorize claims for efficient handling and resource allocation.

6. Intuitive Dashboard and Reporting:
- Offers a centralized dashboard for monitoring fraud cases and viewing detailed reports.
- Provides a complete audit trail of detected fraud patterns, investigations, and outcomes.

7. Seamless API Integration:
- Easily integrates with existing claims management systems through an API, ensuring quick deployment without disrupting ongoing operations.

Key Benefits

Reduced Fraud-Related Losses:
Detects fraudulent claims early, minimizing financial impact and protecting profitability.

Increased Accuracy and Reduced False Positives:
Lowers the rate of false positives through sophisticated machine learning models, allowing genuine claims to be processed without delays.

Faster, Proactive Fraud Detection:
Real-time monitoring and automated alerts enable insurers to stay ahead of emerging fraud schemes, reducing investigation time and enhancing compliance.

Media

White Papers
Videos

Product/Service details