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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 Efforts to engage customers on a personal level often fail, as they rely on incomplete and frequently outdated information, highlighting the urgent need for a more cohesive approach to data management.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
Companies that leverage data effectively utilize the Tilores API to establish a cohesive customer profile across all their various source systems. They develop real-time solutions that help mitigate risk, detect fraud, and provide tailored digital experiences, all while avoiding engineering complications. The challenges posed by inconsistent, incomplete, and outdated customer information hinder businesses in their efforts to align, strategize, and report accurately. For organizations to harness their customer data effectively, they must first standardize their schemas and integrate both new and historical data seamlessly. However, even after creating a centralized system with unified customer data, it often necessitates dedicated development efforts to enhance its utility. To streamline this process, it's essential for unified customer data to be synchronized back to the individual source systems of each department, turning every system into a distributed source of truth. This approach empowers businesses to manage risk more efficiently, detect fraud proactively, and enhance customer service. By transforming fragmented and isolated customer data into a comprehensive Customer 360 view, organizations can unlock new insights and drive better decision-making. Ultimately, this unification fosters a deeper understanding of customer behavior, enabling continuous improvement and innovation.
API Access
Has API
API Access
Has API
Integrations
Salesforce
Amazon Web Services (AWS)
Apache Spark
Azure Marketplace
Google Cloud Anti Money Laundering AI
Google Cloud Platform
GraphQL
Hadoop
HubSpot CRM
HubSpot Customer Platform
Integrations
Salesforce
Amazon Web Services (AWS)
Apache Spark
Azure Marketplace
Google Cloud Anti Money Laundering AI
Google Cloud Platform
GraphQL
Hadoop
HubSpot CRM
HubSpot Customer Platform
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
$2000/month
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
Tilores
Founded
2021
Country
Germany
Website
tilores.io
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