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csideEffectively tracking third-party scripts removes ambiguity, guaranteeing that you remain informed about what is sent to your users' browsers. The uncontrolled existence of these scripts within users' browsers can lead to major complications when issues arise, resulting in negative publicity, possible legal repercussions, and claims for damages due to security violations. Organizations that manage cardholder information must adhere to PCI DSS 4.0 requirements, specifically sections 6.4.3 and 11.6.1, which mandate the implementation of tamper-detection mechanisms by March 31, 2025, to avert attacks by alerting relevant parties of unauthorized changes to HTTP headers and payment details. c/side is distinguished as the only fully autonomous detection system focused on assessing third-party scripts, moving past a mere reliance on threat intelligence feeds or easily circumvented detection methods. Utilizing historical data and advanced artificial intelligence, c/side thoroughly evaluates the payloads and behaviors of scripts, taking a proactive approach to counter new threats. Our ongoing surveillance of numerous websites enables us to remain ahead of emerging attack methods, as we analyze all scripts to improve and strengthen our detection systems continually. This all-encompassing strategy not only protects your digital landscape but also cultivates increased assurance in the security of third-party integrations, fostering a safer online experience for users. Ultimately, embracing such robust monitoring practices can significantly enhance both the performance and security of web applications.
What is Tookitaki?
Tookitaki's Anti-Money-Laundering Solutions enhance your Compliance Lens by significantly minimizing false positives, achieving at least a 50% reduction in transaction monitoring programs and over 60% in screening programs. Additionally, it improves risk management by boosting the identification of genuine suspicious cases (SAR/STR) by 5%. Alerts are efficiently prioritized, allowing for quicker responses. With ongoing automatic learning, the system maintains high detection rates even amid increasing data volumes and evolving regulations. The complex machine learning models are presented clearly for user comprehension. Furthermore, the integration process with current and prospective up/downstream systems within the financial institution is streamlined through pre-built connectors. Our Transaction Monitoring feature includes secondary scoring, employing a proprietary semi-supervised approach that leverages multi-dimensional unsupervised methods, network analysis, and supervised learning techniques to enhance the overall effectiveness of the monitoring process. This comprehensive methodology ensures that compliance teams can effectively tackle the challenges posed by sophisticated financial crimes.
What is SAS Financial Crimes Analytics?
SAS Financial Crimes Analytics serves as a cloud-driven platform aimed at bolstering Anti-Money Laundering (AML) efforts by utilizing artificial intelligence and machine learning to streamline compliance operations. This groundbreaking solution enables financial organizations to more efficiently detect and prevent financial crimes while reducing the occurrence of false positives, automating investigations, and improving overall detection efficacy. Users benefit from features that facilitate data exploration and visualization, allowing for easy importing, transforming, and integrating of data through a user-friendly drag-and-drop interface. Moreover, it accelerates the deployment of analytical models via automated processes, making it suitable for both batch processing and real-time applications. The system integrates effortlessly with existing transaction monitoring frameworks, eliminating the need for major revisions to current AML systems. In addition, it harnesses sophisticated analytical tools, including network and text analytics, to deliver a thorough understanding of risk factors, enabling institutions to stay responsive to the changing dynamics of financial crime threats. This comprehensive strategy not only enhances compliance measures but also fortifies the institution’s overarching risk management framework, ensuring better protection against emerging risks. Ultimately, SAS Financial Crimes Analytics represents a pivotal advancement in the fight against financial crime, equipping institutions with the necessary tools to navigate an increasingly complex environment.
Integrations Supported
SAS Anti-Money Laundering
API Availability
Has API
API Availability
Has API
Pricing Information
Pricing not provided
Free Version
Free Trial Offered?
Pricing Information
Pricing not provided
Free Version
Free Trial Offered?
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
Tookitaki
Date Founded
2014
Company Location
Singapore
Company Website
www.tookitaki.com
Company Facts
Organization Name
SAS
Date Founded
1976
Company Location
United States
Company Website
www.sas.com/en_us/software/financial-crimes-analytics.html
Categories and Features
Categories and Features
AML
Behavioral Analytics
Case Management
Compliance Reporting
Identity Verification
Investigation Management
PEP Screening
Risk Assessment
SARs
Transaction Monitoring
Watch List
Financial Risk Management
Compliance Management
Credit Risk Management
For Hedge Funds
Liquidity Analysis
Loan Portfolio Management
Market Risk Management
Operational Risk Management
Portfolio Management
Portfolio Modeling
Risk Analytics Benchmarks
Stress Tests
Value At Risk Calculation