Lockstock enhances cybersecurity and develops an AI framework for a Reinsurance Company
A well-established reinsurance company seeking to leverage artificial intelligence (AI) in its business processes while ensuring robust cybersecurity and compliance with industry standards.
Lockstock was able to create a secure framework for AI application development while also enhancing its security of cloud assets, which resulted in reduced vulnerability and risks. Lockstock was also able to assist in the decision for the most appropriate security vendors and products, which increased the overall security posture of the company.
Challenges Faced
AI Integration in Sensitive Environments: The company needed to develop and implement AI applications in a highly secure and compliant manner.
Cloud Asset and Vulnerability Management: With a significant presence in cloud environments, the firm required a comprehensive approach to manage cloud assets and vulnerabilities.
Third-Party Security Vendor Selection: The need to choose the right security vendors and products to meet specific business requirements and mitigate risks.
Solutions Provided
AI Policy and Procedure Creation
In-Network AI Policy Development: Developed policies and procedures for the use and development of AI applications, addressing cybersecurity and compliance risks.
AI Compliance with NIST Guidance: Ensured that AI policies align with NIST guidelines and industry best practices.
Cloud Asset Inventory Management Program
Inventory Management: Implemented a cloud asset inventory management program to track and manage all cloud assets efficiently.
Cloud Vulnerability Management Platform Integration: Integrated a platform for ongoing monitoring and management of vulnerabilities in the cloud environment.
Cybersecurity Vulnerability Management
Ticketing System Integration: Established a ticketing system to effectively address and resolve cybersecurity vulnerabilities.
Cloud Network Diagram Creation: Created a comprehensive cloud network diagram detailing assets, monitoring services, testing services, and more.
Third-Party Vendor and Product Selection
Risk, Cost, and Use Case Analysis: Advised on selecting third-party security vendors and products based on risk assessments, cost-effectiveness, and suitability for specific use cases.
Results Achieved
Robust AI Governance Framework: Successfully established a secure and compliant framework for AI application development and use.
Enhanced Cloud Asset and Vulnerability Management: Improved the management and security of cloud assets, reducing vulnerabilities and risks.
Effective Third-Party Vendor Integration: Chose the most appropriate security vendors and products, enhancing the overall security posture.
Conclusion
This case study demonstrates how the company advanced its cybersecurity framework and AI governance by aligning with NIST guidance. The introduction of a comprehensive AI policy, cloud asset, and vulnerability management program, and a strategic approach to third-party vendor selection significantly bolstered the company’s security infrastructure. The reinsurance company not only achieved a high level of security and compliance but also positioned itself to harness the benefits of AI in its business processes effectively and safely.
