Genai Adoption In Insurance Has Remained Painful And Slow, Why?

By Author: Blue pond
Total Articles: 3
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Despite slow progress in various GenAI-enabled solutions, the gap between the need and potential of GenAI and its actual deployment remains wide. Why?

A different app for each process: Over the years, point solutions have emerged to tackle specific tasks or processes but implementing each takes time and cost.

No cross-learning: Each application is narrowly trained for its task, making it difficult to extract learnings or data from one to enrich another.

Stuck at 80% accuracy: Despite seemingly high accuracy, the lack of reliability often demands extensive manual intervention, diminishing the expected improvements in turnaround time and cost efficiency. Even slight inconsistencies can undermine trust and hinder the widespread adoption of AI solutions.

No reuse of common building blocks: Enterprise services, external data sources, prompt libraries, or model libraries.

The complexity of managing multiple point solutions: Multiplies exponentially with each app requiring separate updates and management, spiraling down the rabbit hole of interconnections and interdependencies.

Multiplying ...
... cybersecurity, vendor dependency and regulatory concerns: Each application, served by a different vendor on a different platform, brings its risks.

Lack of IP ownership and data confidentiality concerns: Many GenAI vendors are unfortunately not transparent about how their models were trained. How many give you ownership of the IP built on your data? How can you be sure that your data isn't enriching your competitors?

Consultants and SI firms’ love for ‘reinventing the wheel’: Yes, each insurer has unique business rules, underwriting guidelines and processes, but the industry follows a common set of data structures, document types and processes.

In a nutshell, this is causing our industry to suffer from the ‘death by a thousand cuts’ syndrome.

Why are ‘bare metal LLMs’ not enough?

Hyperscaler-managed LLMs are indeed the underlying foundation of most GenAI infrastructure. However, building multiple applications on bare metal LLMs from scratch isn’t cost-effective, fast, or scalable. These off-the-shelf solutions require insurers to invest heavily in building everything from workflows to models and analytics, leading to inefficiencies and delayed ROI.

LLMs are now very well trained in the English language, but we are missing the layer of ‘insurance language training’ - a basic understanding of our industry’s typical terms, forms, documents, processes and rules.

Further, while hyperscalers provide the necessary infrastructure layer elements, there is a gap in a foundational ‘software chassis’ to rapidly build applications leveraging shared enterprise components.

P&C-ready GenAI as a Service: A new platform approach to enterprise GenAI deployment

BluePond.AI’s P&C Copilot was conceived with these industry challenges, friction points and gaps in mind. We aim to create a P&C-ready GenAI as a Service platform – a unifying platform that can be hosted on an insurer’s cloud environment, enabling powerful applications across the P&C value chain. For us to overcome the current challenges, it must enable applications to reuse a common set of language understanding, model libraries, enterprise services and share learnings across use cases. Finally, it must allow data and documents to remain within the insurer’s cloud environment when required.

Key features of the P&C CoPilot

Out-of-the-box P&C ready: Human-like GenAI understanding

Pre-trained for P&C insurance: State-of-the-art GenAI that is equipped with P&C insurance language understanding.

Document intelligence: Identifies and processes documents automatically.

Standard process rules: Extracts data from documents, compares and analyzes it and prompts human intervention when necessary.

Language analytics: Ability to compare insurance language (e.g. coverage conditions in one policy vs. another) at scale and draw insights and trends.

P&C-specific analytics: Unlocks actionable insights tailored to insurers’ needs.

Pre-built workflows: Ready-to-use solutions for claims triaging, renewals and more.

2. One Platform - Multiple applications, by design

Implementation: Deploys across underwriting, claims, analytics and more.

Easy integration: Shared enterprise integrations like security, core systems, mailboxes, enterprise utilities, data lake/warehouse, etc.

Accelerate processes: Reuses prompt libraries and workflows across functions.

External data connectors: Expands functionality through seamless integrations.

End-to-end DevOps support: Scales operations without friction.

3. Enterprise-grade

Pre-built, common integration frameworks: Seamlessly connects with tools like CRMs and ERPs.

Configurable pipelines: Customizable to suit unique enterprise workflows.

VPC hosting: Ensures data sovereignty and security.

Scalable by design: Supports the demands of large enterprises with ease.

Compliance standards: SOC 2 certified for trust and reliability.

4. Fully managed GenAI

Continuous domain updates: Ensures relevance with ongoing training and refinements.

Model drift management: Proactively mitigates performance degradation.

Cost-performance optimization: Maximizing ROI through smart resource allocation.

SLA-backed performance guarantee: Ensuring accuracy, uptime and quick response times you can count on.

5. Multi-LLM architecture: Optimize and de-risk your GenAI

Flexibility: Easily switches workloads between LLMs.

Dynamic routing: Automatically selects the best LLM for each task.

Out-of-the-box compatibility: Works seamlessly with multiple LLMs for diverse use cases.

P&C GenAI as a Service: A game-changing paradigm

The GenAI revolution is here to stay. The world is moving to a new paradigm where one large, nearly AGI-level model performs most tasks in one instance. Insurers now have the opportunity to switch to this P&C GenAI as a Service platform path, delivering their initiatives with speed, certainty and scalability. Staying on the current path of nurturing a growing array of point solution applications will bring significant management headaches, enterprise risks and the possibility of missing out on the seismic shift already underway in the GenAI world.

To read full blog - P&C GenAI as a Service: Hyperscaling GenAI in insurance