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Description
Utilizing graph analytics throughout the customer lifecycle can help uncover hidden risks and unveil unexpected opportunities. Conventional Master Data Management (MDM) solutions struggle to accommodate the vast amounts of distributed and diverse data generated from various applications and external sources. The traditional methods of probabilistic matching in MDM are ineffective when dealing with siloed data sources, leading to missed connections and a lack of context, ultimately resulting in poor decision-making and uncapitalized business value. An inadequate MDM solution can have widespread repercussions, negatively impacting both the customer experience and operational efficiency. When there's no immediate access to comprehensive payment patterns, trends, and risks, your team’s ability to make informed decisions swiftly is compromised, compliance expenses increase, and expanding coverage becomes a challenge. If your data remains unintegrated, it creates fragmented customer experiences across different channels, business sectors, and regions. Efforts to engage customers on a personal level often fail, as they rely on incomplete and frequently outdated information, highlighting the urgent need for a more cohesive approach to data management. This lack of a unified data strategy not only hampers customer satisfaction but also stifles business growth opportunities.
Description
For more than ten years, Quantifind’s data analytics platform has empowered governments and Fortune 50 companies to extract valuable insights from a wide variety of public data sources. The platform’s effectiveness lies in its integration of scientific principles with design aesthetics, marrying machine learning advancements with user-friendly, comprehensive web applications and APIs. Currently, Graphyte is instrumental in addressing financial crime risks, boasting accuracy and features that enhance the efficiency of Anti-Money Laundering (AML) investigations by 40% or more. It incorporates diverse data points, including corporate information, law enforcement records, regulatory details, registrations, leaks, Politically Exposed Persons (PEPs), sanctions, enforcement actions, restricted lists, and social media. The technology developed by Quantifind is utilized throughout the investigative workflow, optimizing each phase of the process for better efficiency. Additionally, a robust web application designed with a consumer-grade user experience allows investigators to quickly locate the information they need, significantly streamlining the investigative efforts. This innovative approach not only saves time but also enhances the overall quality of investigations.
API Access
Has API
API Access
Has API
Integrations
Amazon Web Services (AWS)
Apache Spark
Azure Marketplace
Google Cloud Anti Money Laundering AI
Google Cloud Platform
Hadoop
Microsoft Azure
Salesforce
Integrations
Amazon Web Services (AWS)
Apache Spark
Azure Marketplace
Google Cloud Anti Money Laundering AI
Google Cloud Platform
Hadoop
Microsoft Azure
Salesforce
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Quantexa
Founded
2016
Country
United Kingdom
Website
www.quantexa.com
Vendor Details
Company Name
Quantifind
Founded
2009
Country
United States
Website
www.quantifind.com
Product Features
AML
Behavioral Analytics
Case Management
Compliance Reporting
Identity Verification
Investigation Management
PEP Screening
Risk Assessment
SARs
Transaction Monitoring
Watch List
Fraud Detection
Access Security Management
Check Fraud Monitoring
Custom Fraud Parameters
For Banking
For Crypto
For Insurance Industry
For eCommerce
Internal Fraud Monitoring
Investigator Notes
Pattern Recognition
Transaction Approval
Master Data Management
Data Governance
Data Masking
Data Source Integrations
Hierarchy Management
Match & Merge
Metadata Management
Multi-Domain
Process Management
Relationship Mapping
Visualization
Product Features
Data Analysis
Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics
Investigation Management
Contact Management
Data Management
Incident Management
Reporting & Statistics
Subject Profiles