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Average Ratings 0 Ratings
Description
KYCsphere is an innovative compliance platform utilizing AI to streamline the KYC and AML processes throughout the entire compliance lifecycle, from the initial onboarding of customers to necessary regulatory reporting, all hosted within a cloud-based SaaS framework on Microsoft Azure. This comprehensive solution amalgamates various functions such as customer onboarding, identity verification, sanctions and PEP screening, transaction monitoring, risk evaluation, alert management, investigative case handling, and regulatory reporting, including SAR and CTR filings, into a singular system. By leveraging machine learning, the platform enhances risk scoring, utilizes fuzzy-matching techniques for name screening, and implements real-time anomaly detection to significantly minimize false positives. Compliance teams can effortlessly set up workflows and customize risk parameters using no-code tools, eliminating the need for IT support. The solution adheres to the regulatory standards set by FinCEN, OFAC, FATF, and EU AML Directives, ensuring compliance across all jurisdictions. There is no requirement for hardware investment, allowing for rapid deployment within days, automatic scaling, and comprehensive audit trails throughout every region. By integrating these diverse functionalities, KYCsphere not only simplifies compliance but also improves operational efficiency for organizations.
Description
NetOwl NameMatcher, recognized for its excellence in the MITRE Multicultural Name Matching Challenge, delivers unparalleled accuracy, speed, and scalability in name matching solutions. By employing an innovative machine learning framework, NetOwl effectively tackles the intricate challenges of fuzzy name matching. Conventional methods like Soundex, edit distance, and rule-based systems often face significant issues with precision, leading to false positives, and recall, resulting in false negatives, when confronting the diverse fuzzy name matching scenarios outlined previously. In contrast, NetOwl leverages a data-driven, machine learning-based probabilistic strategy to address these name matching difficulties. It automatically generates sophisticated, probabilistic name matching rules from extensive, real-world multi-ethnic name variant datasets. Furthermore, NetOwl employs distinct matching models tailored to various entity types, such as individuals, organizations, and locations. To add to its capabilities, NetOwl also integrates automatic detection of name ethnicity, enhancing its adaptability to the complexities of multicultural name matching. This comprehensive approach ensures a higher level of accuracy and reliability in diverse applications.
API Access
Has API
No
API Access
Has API
No
Screenshots View All
No images available
Integrations
ArcGIS
No
Elasticsearch
No
Google Maps
No
IBM Cloud
No
Kibana
No
MarkLogic
No
Palantir Apollo
No
SolrCommerce
No
Tableau
No
Integrations
ArcGIS
Yes
Elasticsearch
Yes
Google Maps
Yes
IBM Cloud
Yes
Kibana
Yes
MarkLogic
Yes
Palantir Apollo
Yes
SolrCommerce
Yes
Tableau
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
Yes
Vendor Details
Company Name
Divas Software
Founded
2000
Country
India
Website
www.divassoftware.com
Vendor Details
Company Name
NetOwl
Founded
1996
Country
United States
Website
www.netowl.com/name-matching-software
Product Features
Product Features
Data Quality
Address Validation
No
Data Deduplication
No
Data Discovery
No
Data Profililng
No
Master Data Management
No
Match & Merge
No
Metadata Management
No