Insurance AI Dictionary
A–Z Glossary
Explore executive reference definitions for Property & Casualty insurance AI. Select a letter to jump to matching terms, then open any entry to read the full guide.
A
9 termsThe Executive Guide to Autonomous AI Systems in Property and Casualty Insurance
Agentic AI refers to artificial intelligence systems that can autonomously pursue goals, plan multi-step activities, make decisions within …
Autonomous and Assistive AI for Governed Insurance Workflows
An AI agent is a software system that can interpret a goal, plan and execute permitted actions with tools and data, evaluate progress, and …
How Autonomous and Human-Governed AI Agents Can Transform Claims, Underwriting, Fraud Detection, and Insurance Operations
AI agents represent a shift from isolated prediction or content generation toward governed systems that can pursue a defined goal, use …
A Practical Guide for Property & Casualty Insurance
AI bias is a systematic tendency in data, models, or workflows that can produce distorted, inconsistent, or unjustified outcomes. In P&C …
Strategy • Accountability • Risk-Tiered Controls • Lifecycle Oversight • Evidence
AI governance is the enterprise system of policies, decision rights, roles, controls, evidence, and oversight used to ensure that …
A Practical Guide for Property & Casualty Insurance
AI guardrails are the policies, technical controls, workflow constraints, monitoring mechanisms, and human oversight practices that keep …
A Practical Guide for Property & Casualty Insurance
An AI hallucination is an output that sounds plausible but is unsupported, fabricated, inconsistent with available evidence, or materially …
A Practical Guide for Property & Casualty Insurance
AI model drift is a material change in the relationship between an AI system, its inputs, its operating environment, and the outcomes it …
A Practical Guide for Property & Casualty Insurance
Artificial intelligence is not a single product or model. It is a family of technologies that helps computers analyze information, …
B
1 termA Practical Guide for Property & Casualty Insurance
AI bias is a systematic tendency in data, models, or workflows that can produce distorted, inconsistent, or unjustified outcomes. In P&C …
C
2 termsTurning Insurance Images and Video into Actionable Evidence
Property & Casualty insurance is inherently visual. Damage photographs, vehicle images, property inspections, medical images, aerial …
How Language-Based AI Understands and Supports Insurance Work
A large language model is an AI model trained on very large collections of text so it can interpret language, generate responses, …
D
2 termsA Practical Guide for Property & Casualty Insurance
Data quality is the fitness of data for a defined business purpose. It is measured against explicit expectations for accuracy, …
Advanced Neural Networks for Complex Insurance Intelligence
Deep learning is a specialized form of machine learning that uses multi-layer neural networks to learn complex patterns from large volumes …
E
2 termsA Practical Guide for Property & Casualty Insurance
Embeddings are numerical representations that place words, passages, documents, images, or other insurance objects into a multidimensional …
A Practical Guide for Property & Casualty Insurance
Explainable AI (XAI) is the discipline of making AI outputs sufficiently understandable for the people who must evaluate, challenge, …
F
2 termsA Practical Guide for Property & Casualty Insurance
Feature engineering is the disciplined process of converting raw insurance data into meaningful, model-ready variables that represent …
A Practical Guide for Property & Casualty Insurance
Fine-tuning is the controlled process of further training a pre-trained model on curated examples so that its behavior becomes more …
G
1 termCreating New Content While Transforming Insurance Workflows
Generative AI is a class of artificial intelligence that creates new content - including summaries, explanations, draft communications, …
I
1 termFrom Documents to Structured, Evidence-Linked Insurance Workflows
Intelligent Document Processing is an end-to-end capability that receives documents, determines what they are, reads their contents, …
K
1 termA Practical Guide for Property & Casualty Insurance
Knowledge graphs provide a structured way to represent real-world entities, their attributes, and the relationships among them. In …
L
1 termHow Language-Based AI Understands and Supports Insurance Work
A large language model is an AI model trained on very large collections of text so it can interpret language, generate responses, …
M
2 termsThe Predictive Engine Powering Modern Insurance AI
Machine learning enables insurers to learn patterns from historical data and apply those patterns to new claims, submissions, policies, …
Connecting Governed AI Assistants and Agents to Insurance Systems
Model Context Protocol (MCP) is an open protocol that standardizes how AI applications connect to external tools, data resources, and …
N
2 termsTurning Insurance Language Into Actionable Intelligence
Natural language processing converts human language into structured, searchable, and evidence-linked information that supports insurance …
How Layered Learning Models Recognize Patterns and Support Insurance Decisions
A neural network is a machine learning model composed of interconnected computational units arranged in layers that learn complex patterns …
O
1 termTurning Scanned Insurance Documents into Machine-Readable Text
Optical Character Recognition is the technology used to detect and convert visible characters in an image into machine-readable text. In …
P
2 termsTurning Insurance Data into Earlier, Explainable Business Insight
Predictive AI uses historical and current information to estimate likely future outcomes so professionals can prioritize attention, …
A Practical Guide for Property & Casualty Insurance
Can an insurer convert general-purpose AI capability into repeatable, controlled assistance for claims, underwriting, operations, and …
R
3 termsLearning Sequential Decisions Through Feedback, Rewards, and Constraints
Reinforcement learning is a method for improving sequential decisions by learning from feedback. The system observes a situation, chooses …
A Practical Guide for Property & Casualty Insurance
Responsible AI is the disciplined design, deployment, and oversight of artificial intelligence so that it supports legitimate business …
Grounding Generative AI in Trusted Insurance Knowledge
Retrieval-Augmented Generation is an architecture that retrieves relevant information from approved sources and supplies it to a …
S
3 termsA Practical Guide for Property & Casualty Insurance
Semantic search retrieves information based on meaning, context, and conceptual similarity—not only exact keyword matches. In P&C …
Learning from Known Outcomes to Improve Insurance Decisions
Supervised learning is a machine learning approach in which a model learns from historical examples that already include the correct …
A Practical Guide for Property & Casualty Insurance
Synthetic data is artificially generated information designed to reflect the statistical patterns, relationships, and business behaviors …
U
1 termDiscovering Hidden Patterns, Segments, and Anomalies in Insurance Data
Unsupervised learning analyzes data without predefined outcome labels to reveal natural groupings, unusual cases, hidden structures, and …
V
1 termA Practical Guide for Property & Casualty Insurance
A vector database is a specialized data platform designed to store high-dimensional embeddings and quickly retrieve the most semantically …
Currently viewing letter A with 9 terms.