How Brokers Can Use AI While Maintaining Data Security 

As AI reshapes the insurance industry, brokers are increasingly adopting AI tools to reduce manual work and better help clients. However, particularly when working with sensitive client data, security and privacy is a top priority. We’re going to explore three approaches to ensuring data security when implementing AI solutions in your brokerage: on-premise deployments, VPC deployments and secure multi-tenant applications.

Consider this a kind of "cheat sheet" of security options the next time you're considering buying software for your agency or brokerage.

On-Premise Deployments

On-premise solutions offer the highest level of control and security over your data. With an on-premise solution, the whole tech stack runs entirely on your hardware (either physically or in your cloud). Here are some pros and cons to consider: 

Pros:

1. Most Control: You have complete oversight of your data and AI systems.
2. Customization: Tailor the infrastructure to your specific needs and security protocols.
3. Compliance: Easier to meet strict regulatory or carrier requirements.
4. Data Isolation: Minimize exposure to external threats by keeping everything in-house.

Cons:

1. Expensive: Significant investment in hardware, software, and infrastructure, especially when running AI models due to the cost of GPUs.
2. Ongoing Maintenance: Requires dedicated engineering staff and continuous updates, or for the vendor to remain engaged in maintaining the solution for you.
3. Scalability Challenges: Handling workload spikes, especially ones requiring additional computing resources, can be tricky.
4. Not Widely Offered: Building and maintaining a completely on-prem solution, especially one that involves one or more large AI models, is hard. Not every vendor has this capability.

For larger brokerages dealing with extremely sensitive data or operating under stringent regulations/carrier restrictions, the on-premise approach might be worth the investment. However, for many small to medium-sized agencies, this option is probably overkill; most companies lack either the resources or the expertise to deploy their own on-premise AI software, which is why they turn to cloud-based third-party solutions.

VPC Deployments

Virtual Private Clouds (VPCs) offer an additional layer of security, without many of the downsides of a full on-prem deployment, by utilizing virtualization to separate physical servers into distinct virtual machines. Essentially, it's a happy medium between a full on-prem deployment and a public cloud setup. VPC deployments, although often incurring additional costs, provide an added level of security not always present in the default configurations of cloud platforms.

Pros:

1. Enhanced Security: VPCs provide an added layer of security by isolating your resources from the vendor’s other customers, ensuring that your data remains private and protected.
2. Customizable Network Configurations: Organizations can customize network settings, including IP address ranges, subnets, route tables, and network gateways to suit specific security and operational needs.
3. Dedicated Resources: VPCs often have dedicated resources which can result in better performance and reliability compared to shared resources.
4. Compliance: Easier to meet strict regulatory compliance requirements due to the higher level of control and security measures available.

Cons:

1. Higher Costs: VPC deployments generally incur higher costs than multi-tenant systems due to the need for additional infrastructure and more complex management.
2. Not offered by every vendor: Requires more expertise to set up and manage, which means not all AI vendors offer it.
3. Scalability Limitations: While scalable, it may not offer the same ease of scalability as multi-tenant cloud solutions, particularly in terms of rapid deployment and elasticity.

A VPC setup allows organizations to benefit from the cloud’s flexibility while ensuring that their data is segregated and protected. This is particularly beneficial for companies handling sensitive information or those with stringent security requirements. Data centers managed by leading providers like Amazon, Microsoft, and Google apply robust security measures to both standard and VPC environments, ensuring high levels of data protection.

For brokerages, implementing a VPC with their AI vendor, or any vendor for that matter, can be a strategic move to enhance data security. It’s essential to weigh the additional costs against the benefits of increased security, especially when dealing with confidential client information.

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Multi-Tenant Shared Cloud Solutions

Cloud-based AI solutions built on reputable cloud services like AWS Bedrock, Azure OpenAI, or similar offer significant security advantages without the added cost of the above two options. These multi-tenant shared cloud solutions leverage the expertise and resources of major tech companies to ensure robust data protection.

Key Security Features to Look For:

1. SOC 2 Compliance
   • SOC 2 certification is a strong indicator that the service provider follows strict information security policies and procedures. This compliance assures that the platform prioritizes data protection.
2. Granular Access Controls
   • Effective access controls are crucial, allowing organizations to manage who can view and manipulate data. This feature helps maintain data integrity and prevents unauthorized access within the organization.
3. Regular Security Audits
   • Frequent security assessments and penetration testing are vital for identifying and addressing vulnerabilities. Opt for providers that conduct regular security audits to ensure ongoing protection against emerging threats.

Multi-tenant shared cloud solutions offer several benefits, including lower upfront costs, easier scalability, and advanced security measures that might be challenging to implement in-house. For many insurance brokerages, especially those aiming to adopt AI swiftly without a significant IT overhaul, these platforms provide a robust balance of security and accessibility.

Pros:

1. Lower Costs: Shared infrastructure typically results in lower upfront and operational costs, making it more affordable for many organizations.
2. Ease of Use and Management: Managed by the service provider, these solutions require less in-house expertise, making them easier to deploy and manage.
3. Scalability: Highly scalable with the ability to quickly adjust resources according to demand, offering greater flexibility for growth.
4. Regular Updates and Security Enhancements: Continuous updates and security enhancements provided by the cloud service provider help protect against emerging threats.

Cons:

1. Shared Resources: Resources are shared among multiple tenants, which can potentially lead to performance issues if not properly managed.
2. Less Control: Reduced control over the underlying infrastructure and network configurations compared to VPCs.
3. Potential Security Risks: While generally secure, the shared nature of the environment might pose risks, particularly if there are vulnerabilities in multi-tenant isolation mechanisms.‍
4. Compliance Challenges: Meeting specific regulatory compliance requirements can be more challenging in a shared environment, depending on the provider's controls and certifications.

Solution-Agnostic Considerations

Regardless of whether an organization uses an on-premise solution or a cloud-based solution, implementing encryption and Data Loss Prevention (DLP) is a good idea.

• Encryption
  • Often mandated by regulations like PCI DSS and HIPAA, encryption should be implemented based on specific threat models rather than as a mere compliance checkbox. For instance, encrypting mobile devices is critical to prevent data loss in case of theft, while the necessity for encrypting data center servers may vary.
• Data Loss Prevention (DLP)
  • While not explicitly required by compliance standards, DLP is frequently used as an implied control for various regulations. Its implementation should be tailored to address specific threats, whether it’s preventing accidental leaks, deterring malicious insiders, or maintaining privacy in cloud environments.

Encryption and DLP are typical parts of the security apparatus of any enterprise software vendor. An astute buyer of broker tech should consider these, and several others, as they evaluate AI vendors.

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Choosing the Right Approach

Ultimately, the decision between on-premise and cloud-based AI solutions depends on your specific needs, resources, and risk tolerance. Consider factors like the sensitivity of your data, your IT capabilities, budget constraints, and growth projections. If going with a cloud-based solution, make sure to ask questions about data handling, encryption, and access controls when evaluating AI solutions to ensure that your clients’ most sensitive information is only being used by tools you trust.

If you're interested in secure, private AI automations for your agency or brokerage (we offer all of the above options), please book a call here to learn more and get started!