Nightfall AI
The 3 I’s of DLP in Action: How Nightfall Secures Sensitive Data for Financial Services
Summary
This case study describes how a financial services firm addressed long-standing data loss prevention (DLP) challenges using Nightfall's AI-powered DLP platform, resulting in improved detection accurac...
Value Drivers
Challenges
- Lack of visibility across endpoints, SaaS, and AI apps, making it difficult to monitor sensitive data movement.
- Lack of real-time visibility into operations
- Difficulty in scaling current infrastructure
- High operational costs due to legacy systems
3 more challenges available
Solutions
- Deployment of Nightfall's seamless, API-based DLP platform with lightweight agents and browser plugins across endpoints, SaaS, and GenAI applications.
- Deployed real-time monitoring and analytics platform
- Migrated to cloud-based scalable infrastructure
2 more solutions available
Outcomes
- Achieved comprehensive monitoring of file uploads, cloud storage sync, and clipboard activity with negligible system resource usage and no user impact.
- Achieved 24/7 real-time visibility and monitoring
- Successfully scaled operations to support 3x growth
- Decreased operational costs by 40% annually
- Improved data accuracy and accessibility by 85%
4 more outcomes available
Products
Software
Nightfall DLP Platform
An all-in-one, AI-powered data loss prevention platform providing coverage across SaaS, GenAI apps, and endpoints.
Target Organization
unknown
Description: A financial services firm that experienced compliance violations due to unauthorized analysis of customer financial data in unapproved cloud applications.
Industry:Financial Services