8 MINUTE READ
In the rapidly evolving landscape of insurance claims management, incorporating artificial intelligence (AI) in insurers’ day-to-day work is no longer a futuristic concept—it’s here, and it’s an absolute requirement, as AI tools are becoming indispensable in claims operations.
According to Insurance Journal, approximately 67% of global insurers are now using AI technologies, particularly in customer service, while 45% report that they have incorporated AI into their claims processing.
As AI technologies continue to integrate into our daily lives, it’s crucial to make informed decisions about the tools we choose for work. This is especially true when it comes to public AI models. Particularly Large Language Models (LLMs), which offer amazing benefits, but also present significant risks to insurers if not properly licensed or managed.
LLMs, such as chatGPT, Claude and Gemini, are artificial intelligence systems that were trained on vast amounts of text data to understand, generate, and process human language. They are particularly adept at interpreting context, generating human-like responses, and analyzing complex documents.
In insurance claims management, LLMs are the most frequently used type of AI, often employed to assist in tasks such as customer service, extracting information from documents, and summarizing communications with policyholders.
Understanding the Privacy and Compliance Risks of Public LLMs
LLMs, while powerful and effective, often lack the necessary guardrails to ensure data privacy.
- Data Leaks: By default, public LLMs take user prompts and conversations as new data to train on, and leverage this data in newer versions of these models. That’s the way machine learning (ML) works, and it’s spelled out in their terms of service. As a result, confidential or personal data that an uniformed adjuster puts into the AI chat might find its way to answers that AI model gives to other users, who should not be privy to such information.
- Compliance Issues: Public LLMs often do not adhere to strict data protection laws, which can lead to various compliance breaches. For instance, regulations such as the General Data Protection Regulation (GDPR) in the European Union require companies to protect personal data, ensure its confidentiality, and limit its retention. Public LLMs may struggle with ensuring the permanent deletion of data (“Right to be Forgotten”), as well as controlling access to sensitive information, managing data transfers across borders, and maintaining proper documentation for audits. Additionally, they may expose companies to risks related to data breaches, unauthorized access, and failure to uphold consent mechanisms, all of which can result in severe legal penalties and damaged reputations.
The scenario where a claims adjuster uses a public LLM to draft sensitive communications involving private policyholder information, which then remains stored within the LLM’s database, is far from a mere hypothetical risk. Incidents of data retention and unintended data exposure have been reported across various industries, highlighting the severe implications of such breaches.
Ignoring or Preventing LLMs Usage is Not Sustainable
Given the risks associated with public LLMs, one might consider simply banning their use within the organization. However, this approach is neither sustainable nor practical in the long run.
The Inevitability of AI
The integration of AI tools in everyday tasks will only increase, making it impossible to avoid their usage entirely. AI has proven its value in improving efficiency across various industries, including insurance. Employees will continue to seek out these tools to help them perform their tasks better and faster.
Consequences of Inaction
If organizations choose to ignore or outright ban the use of LLMs without providing a suitable alternative, they risk driving their employees to use these tools in an unregulated and unsupervised manner. This could lead to a rise in shadow IT practices, where employees use unauthorized tools without the knowledge of their IT departments. Such practices increase the risk of data breaches and make it difficult to ensure compliance with security and privacy policies.
A Balanced Approach
Rather than ignoring or banning LLMs, organizations should focus on channeling their use through controlled and secure platforms. This approach allows employees to benefit from the efficiencies that AI offers while ensuring that the tools they use are compliant with data protection regulations and company policies.
How to Choose the Right AI Tools for Your Claims Management Operation
This brings us to a critical question: How do we choose the right AI tools that improve our day-to-day while protecting our companies’ data, our customers’ personal information, and complying with stringent regulations?
When selecting AI tools for your claims management operation, maximizing efficiency must go hand-in-hand with uncompromised adherence to compliance. Look for AI solutions that are tailored to the insurance industry, offering features like built-in data protection safeguards and compliance with relevant regulations, such as GDPR or HIPAA. The AI tool should also provide transparency, explainability and traceability enabling users to track and audit its processes.
Most importantly, don’t choose “open source” solutions. Rather, choose AI solutions that leverage secure, enterprise-grade infrastructure, such as Google Cloud Platform or Amazon Web Services, ensuring stringent data governance, encryption, and residency controls to protect your sensitive information.
Introducing Clive™: The Secure and Compliant AI Choice for Insurance Claims
Clive is the insurance industry’s first AI Claims Adjuster, developed by Five Sigma – an insurtech software developer that also develops and offers an AI-Native Claims Management Platform (CMS) to insurers, MGAs and TPAs.
Clive operates as an adjuster’s best friend on top of any CMS, leveraging advanced AI technology to assist adjusters in streamlining every step of the claims process from FNOL to resolution. Clive analyzes vast amounts of claims data, offers recommendations for next steps, and automates the execution of many tasks, ensuring faster, more accurate claims handling.
Built with a deep understanding of the Insurance claims environment, Clive offers a seamless AI experience, integrating effortlessly into existing workflows while safeguarding sensitive data.
Clive runs on Google Cloud Platform (GCP), leveraging GCP’s enterprise-grade infrastructure and services to ensure data is stored and processed securely.
The Benefits of Clive
Clive’s value extends far beyond public LLMs. It’s a secured multimodal AI product, able to analyze, understand and create multiple formats of content, such as texts, images, voice and video.
Clive is a powerful business enabler that enhances the efficiency and effectiveness of the entire claims operations.
Clive automates routine tasks like document processing, data entry at FNOL, and communication management, freeing up adjusters to focus on value-added tasks like decision making and customer care.
Clive provides actionable insights and recommendations based on data, helping adjusters make quicker and more accurate decisions, and accelerating claim resolution.
Data Security
Clive provides a controlled and secure AI usage with built-in data privacy protections. It ensures that sensitive information is handled with the utmost care and is never exposed to unauthorized parties. Clive’s architecture is designed to prevent data leaks, ensuring that all interactions within the platform are secure and compliant with data protection regulations.
By utilizing GCP’s Vertex AI technology, Clive operates with the assurance that customer data is fully encrypted at rest and in transit. Vertex also does not train its models on GCP’s customer data.
Unlike public LLMs, Clive offers a secure and governed platform that mitigates the risks associated with AI usage while enhancing the efficiency of claims operations.
Compliance
Clive is built for compliance with data protection regulations like GDPR, including the “Right to be Forgotten.” It allows companies to maintain control over their data, ensuring that information can be erased upon request and that all actions within the platform are logged and traceable. In this capacity, Clive functions as a safeguard and an assistant for maintaining regulatory compliance.
Governance and Traceability
Clive offers complete governance and traceability of AI interactions within the claims department. Every interaction within Clive is logged, allowing for full visibility and accountability.
Clive can also reason its recommendations and decisions, providing clarity into the data analysis and implementation of best practices and insurers’ SOP. Each Five Sigma customer can select the boundaries of Clive’s actions and automation, to comply with local laws and provide human oversight to Clive’s AI operations.
Embrace the Future with Confidence
The future of insurance lies in the integration of AI, but the key is to adopt it wisely. Rather than resisting or fearing new technologies like AI, it’s crucial to learn how to harness their capabilities while maintaining security and compliance.
AI, when developed and governed properly, can be a powerful tool that elevates your claims operations while mitigating applicable risks.
