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What is FICO Identity Resolution Engine?

The FICO® Identity Resolution Engine thoroughly investigates various and separate data sources to uncover links between individuals, locations, and events that could indicate fraudulent behavior and money laundering. Utilizing sophisticated fuzzy matching algorithms significantly enhances its ability to detect anomalies, while graph analytics offer real-time visual representations of connections between accounts, applicable both during and after transaction recording. By integrating multiple data points within a single application, it effectively connects them with other applications and accounts, even if the relationships are indirect. The system automates ongoing analysis of accounts based on their risk profiles, enabling it to uncover connections that may only surface after transactions take place. Additionally, it proactively identifies and prioritizes organized fraud and criminal activities through predictive analytics focused on relationships. With capabilities to perform federated searches across raw data and implement intricate link analysis, it utilizes advanced querying tools alongside visual link charts to deepen the understanding of the data ecosystem. Consequently, the FICO® Identity Resolution Engine plays a critical role not only in detecting fraudulent activities but also in facilitating the continuous investigation of such behaviors, ensuring a robust approach to financial security.

What is AWS Entity Resolution?

Implement entity resolution workflows in mere minutes, drastically reducing the time typically required for such processes from months to just a few short spans. Customize advanced matching techniques that boost data accuracy based on your unique business needs. Protect your data while minimizing unnecessary transfers by retrieving records directly from their original sources. AWS Entity Resolution streamlines the task of matching and connecting related records, removing the need for custom-built solutions entirely. Leverage flexible, configurable machine learning (ML) techniques in tandem with rule-based methods to fine-tune record matching according to your organizational objectives. By removing duplicate entries, you can uncover richer insights from your data, effectively preparing it for artificial intelligence (AI) model training and ultimately driving better business outcomes. Cultivate more impactful experiences by utilizing integrated insights across multiple areas, including advertising, marketing campaigns, customer support services, loyalty initiatives, and e-commerce activities. Achieve seamless integration of SKUs, UPCs, or distinct product identifiers into a unified product record, which enhances tracking across retail outlets and supply chains and leads to greater operational efficiency. Furthermore, this streamlined approach not only boosts productivity but also fosters a data-driven culture that can adapt to future challenges and opportunities.

Media

Media

Integrations Supported

Amazon Web Services (AWS)

Integrations Supported

Amazon Web Services (AWS)

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

FICO

Date Founded

1956

Company Location

United States

Company Website

www.fico.com/en/products/fico-identity-resolution-engine

Company Facts

Organization Name

Amazon

Company Location

United States

Company Website

aws.amazon.com/es/entity-resolution/

Categories and Features

Categories and Features

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