Insurance underwriting is a complex, data-intensive process. Assessing risk and making accurate policy decisions requires evaluating immense amounts of information. Artificial intelligence promises to transform underwriting by extracting deeper insights from data at scale.

Intellect Risk Analyst is one pioneering AI solution aiming to improve underwriting outcomes. This platform ingests structured and unstructured data, conducts risk analysis, and generates insights for human underwriters. Early adopters like Liberty Mutual are already seeing major efficiency gains.

Below we explore how Intellect Risk Analyst works, its key capabilities, and the benefits it offers insurance providers.

Overview of Intellect Risk Analyst

Intellect Risk Analyst is an AI-powered data analytics platform designed for insurance underwriting. Developed by insurtech firm IntellectAI, it aims to accelerate underwriting through data-driven insights.

The platform integrates data from disparate sources, applies machine learning to analyze risk, and synthesizes insights for underwriters. This augments human decision-making with an amplified view of risk factors.

Key features of Intellect Risk Analyst include:

• Data aggregation - Integrates structured data like forms and unstructured data including images, emails and documents.

• Data normalization - Cleans and standardizes inconsistent data from different sources.

• Risk scoring - Analyzes data and calculates customized risk scores using AI models.

• Insights engine - Summarizes data into key insights for underwriters.

• API integration - Allows real-time data access from underwriting systems.

• Scalability - Handles high data volumes across different insurance lines.

• Auditability - Maintains transparency into data and models.

By leveraging these capabilities, insurers can significantly accelerate underwriting decisions powered by data.

Step-By-Step Use of Intellect Risk Analyst

Below we walk through the typical workflow of using Intellect Risk Analyst for insurance underwriting:

1. Data Ingestion

First, raw data from both internal systems and external sources is inputted into Intellect's platform. This includes structured data like forms and tables as well as unstructured data such as claims documents, emails, and scanned applications.

2. Data Processing

Intellect's AI algorithms then normalize, cleanse, extract insights, and transform the aggregated data into a consistent, standardized format. This curated data corpus is made available for downstream analytics.

3. Risk Analysis

Proprietary machine learning models developed by Intellect analyze the processed data to detect signals, patterns and insights relevant to risk assessment for a given policy application. Key risk indicators are flagged.

4. Insights Generation

An AI insights engine summarizes the data, risk analysis, and other underwriting factors into easily digestible insights for human underwriters. These are surfaced through interactive dashboards.

5. Decision Making

The underwriter reviews the dashboards, risk scores and insights surfaced by the platform to swiftly make an informed decision on whether to approve, decline or revise the policy application.

6. Real-time Updates

As new data comes in, Intellect's platform continually keeps risk analysis and insights updated in real time via API integrations into core underwriting systems.

By automating much of the heavy lifting of data processing and analysis, Risk Analyst allows underwriters to evaluate policies faster and make more judicious data-backed decisions.

The Benefits of Leveraging Intellect Risk Analyst

Adopting Intellect's AI underwriting solution offers insurers the following key benefits:

• Accelerated underwriting - Quickly extract insights from vast amounts of structured and unstructured data.

• Improved risk assessment - Generate more accurate and customized risk scores for applicants.

• Higher approval rates - Make better decisions by holistically assessing risk factors.

• Increased underwriter productivity - Automate repetitive manual tasks to focus on judgment.

• Reduced reliance on manual processes - Shift away from error-prone and inefficient legacy workflows.

• Auditability - Maintain transparency into the AI's underlying data and models.

• Real-time data access - Leverage dynamic insights powered by continually updated data.

Case Study: Liberty Mutual Sees Major Gains

Liberty Mutual deployed Intellect Risk Analyst in 2020 to enhance its auto and home underwriting. The insurer saw significant benefits:

• Reduced underwriting time from days to minutes - Automated many repetitive manual processes.

• 30% improvement in loss ratio - More precision in risk assessment and pricing.

• 60% increase in straight-through processing - Higher auto-approvals with the AI's support.

• 10-15% further efficiency gains forecasted - Continued optimization of underwriting with the platform.

The Future of AI-Augmented Insurance Underwriting

Intellect Risk Analyst demonstrates the enormous potential of AI in insurance underwriting. By automatically aggregating and analyzing huge amounts of data to uncover insights, AI can help underwriters overcome information overload.

As capabilities continue improving, insurtech solutions like Intellect's will help insurers unlock even deeper insights from data. This will enable hyper-personalized risk assessment powered by end-to-end AI automation.

Leading insurers like Liberty Mutual are already pioneering AI underwriting today. Over time adoption will accelerate across the industry as these technologies transition from early emerging innovations to mission-critical workflow systems of the future.