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What is KROTON?

The H3M KROTON modules offer a seamless integration with conventional rule-based compliance frameworks, significantly elevating their effectiveness by leveraging Artificial Intelligence. This innovative approach not only supports businesses in meeting compliance requirements but also redefines the focus, making crime detection a valuable byproduct rather than the primary goal. In contrast to typical platforms, H3M is specifically designed to uncover hidden connections that aid in crime prevention, which in turn enhances compliance, cultivates better regulatory relationships, provides a competitive advantage, and elevates brand value as advantageous secondary outcomes. The KROTON suite features four AI-powered modules that adeptly combine compliance knowledge with data science principles. The H3M KROTON Suspect Miner addresses the considerable issues presented by legacy systems through its pioneering machine-learning approach that utilizes active learning methods. This advanced technology has the potential to cut false positives by two-thirds while consistently uncovering new money laundering strategies. By integrating the expertise of analysts with AI through active learning, H3M significantly boosts machine performance with proactive labeling, creating a more resilient compliance infrastructure. Consequently, organizations can anticipate not only enhanced compliance but also a profound transformation in their methodologies for risk detection and management, paving the way for future advancements in regulatory practices. This shift ultimately fosters a culture of continuous improvement and adaptability within the organization.

What is Clovis?

Clovis has been meticulously crafted to effectively integrate with existing data frameworks, enabling smooth interactions with legacy system information while enhancing the processing and reporting of alerts with an expanded range of features. Furthermore, our innovative AI-powered solution, ClovisQ, amalgamates diverse customer characteristics—such as demographic information, industry details, geographic insights, and transaction records—to furnish businesses with real-time data visibility as trends and patterns emerge. Our platform's flexibility allows for both On-Premises and Software as a Service (SaaS) deployment, giving organizations the freedom to select their preferred approach to managing resources, whether human or technological. This strategic framework is set to yield significant cost savings for businesses of varying scales, all while increasing their potential for revenue generation. By drawing upon the rich experiences of our founders, who hail from leading consumer banks, notable data organizations, and the U.S. Intelligence Community, we are at the forefront of developing a comprehensive AI-driven anti-money laundering (AML) solution that promises to revolutionize the industry. Ultimately, our goal is to equip businesses with the tools necessary to adeptly navigate complexities and adjust to the constantly shifting financial environment, ensuring they remain competitive and resilient.

Media

Media

Integrations Supported

Additional information not provided

Integrations Supported

Additional information not provided

API Availability

API Availability

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

SaaS
On-Prem

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub
Online Training
On-Site Training

Training Options

Documentation Hub
Online Training

Company Facts

Organization Name

H3M Analytics

Company Location

United States

Company Website

h3m.io/kroton-suspect-miner

Company Facts

Organization Name

Clovis Technologies

Date Founded

2018

Company Location

United States

Company Website

www.clovistechnologies.com

Categories and Features

AML

Not specified

Identity Verification

Not specified

Categories and Features

AML

Not specified

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