Continuous Underwriting: Real-Time Insurance Backed by AI & Data

Traditionally, underwriting is performed during policy issuance or renewal. Based on a customer’s risk profile and historical data, the policy is priced accordingly. However, continuous underwriting transforms these procedures into a real-time or near real-time process.

This approach allows insurance carriers and MGAs to dynamically adjust terms, pricing, and risk exposure throughout the policy period.

With advancements in AI-powered underwriting, carriers now have access to real-time data, predictive analytics, and automation. With the continuous underwriting process, risks can be assessed continuously, and pricing can be revised during the policy term instead of waiting until renewal.

Often paired with usage-based insurance (UBI), this model rewards ideal policyholder behaviors. It enables coverage for protection gaps that might emerge after the policy is issued.

Instead of relying on a one-time risk snapshot, insurers can:

• Monitor risk continuously

• Adjust premiums based on real-time data

• Take corrective action instantly

Lines of Business Where Continuous Underwriting Can Deliver Impactful Results

1) Auto Insurance

Pay-as-you-drive is a prime example of usage-based insurance. Currently, premiums are based on the vehicle’s make and model, and now UBI strategies, such as telematics-based auto insurance, reward safe driving behaviors with reduced premiums.

With telematics and GPS data,

• Insurers can monitor the behavior of drivers and adjust the premium on real-time driving habits.

• The premium for drivers who do not follow the traffic rules and get tickets will be increased from next month.

This provides more accurate pricing for insurers and rewards safer drivers with lower premiums.

2) Homeowners’ Insurance

IoT applications have become common to Healthcare, Manufacturing, Retail, Agriculture, Transportation, and the insurance industry is no exception. Devices like smart smoke sensors and leak sensors help:

• Detect potential losses early

• Allow premium adjustments based on risk measures

• Enable risk re-evaluation during the policy period

Insurers gain continuous insight into home safety, enabling smarter pricing models.

3) Commercial Insurance

The monitoring of accumulation data indicates the concentration of risks in a particular zone or location to avoid losses in any catastrophic event. The real-time monitoring of fire safety systems like sprinklers, building security, and fire drills helps the insurers adjust coverage or premiums based on risk mitigation measures.

4) Health Insurance

Continuous underwriting in health insurance benefits both insurers and policyholders. Health-tracking apps can monitor:

• Physical activity

• Heart rate

• Calorie intake

This data enables AI-powered underwriting to:

• Suggest preventive health checkups

• Alert users of potential risks early

• Reward healthy behavior with lower premiums

This continuous underwriting process enables insurers to incentivize individuals with healthier behavior and vice versa.

5) Cyber Insurance

Under cyber insurance, continuous monitoring of network security helps insurers:

• Adjust terms

• Send alerts for immediate action when vulnerabilities are detected

• Reward clients adopting strong cybersecurity practices

This makes continuous underwriting a game-changer for the digital world.

6) Marine and Cargo Insurance

Another area where continuous underwriting is useful in marine insurance is tracking shipments and geographical conditions. The monitoring of temperature, humidity, transit route, weather conditions, and other geopolitical risks helps the insurers either suspend or modify the coverage involving high-risk areas and periods.

Advantages of Continuous Underwriting

Automation significantly reduces the likelihood of manual errors, resulting in more accurate and efficient operations. The integration of policy issuance, claims processing, and risk monitoring enhances overall workflow efficiency, enabling a more proactive approach to risk management.

For Insurers:

• Access to real-time data for more accurate risk selection and pricing.

• Early detection of emerging risks enables preemptive action.

• Proactive risk management helps mitigate potential losses.

• Improved decision-making enhances overall portfolio performance.

For Policyholders:

• Receive real-time feedback on their behavior.

• Incentives and rewards are available immediately, without waiting for policy renewal.

• Dynamic pricing ensures premiums reflect actual risk profiles and behavior.

• Real-time adjustments promote a sense of fairness and transparency.

Challenges and Risks of Continuous Underwriting

The primary challenge associated with continuous underwriting lies in data privacy and the potential for data breaches when sensitive policyholder information is collected and processed continuously. A breach of such data could expose confidential customer information, leading to reputational damage and potential legal liabilities.

Furthermore, real-time monitoring and premium adjustments may face regulatory hurdles, as existing frameworks may not support dynamic pricing models within the policy period. From a customer perspective, many policyholders, particularly businesses, prefer the certainty of a fixed insurance cost to facilitate accurate budgeting and financial planning. Frequent fluctuations in premium rates could create uncertainty and dissatisfaction among customers.

The substantial initial investment required to implement the necessary infrastructure, including IoT, AI, and machine learning systems, may also deter insurers. Integrating real-time data streams with existing legacy systems presents additional technical complexities, which could increase operational costs and implementation timelines.

Moreover, frequent changes in premiums and policy terms could undermine customer confidence, leading to customer dissatisfaction. In such cases, competitors offering more stable and predictable pricing structures may gain a competitive advantage, potentially resulting in customer attrition.

Final Thoughts

Continuous underwriting driven by AI-powered underwriting and usage-based insurance models represents a bold step toward data-driven, personalized insurance. While it brings undeniable benefits in risk management and dynamic pricing, it also demands robust tech infrastructure, regulatory adaptation, and transparent communication.

Author: CA Chandrasekaran Ramakrishnan, Senior Technical Advisor, INSILLION

Disclaimer: The opinions expressed within this article are the personal opinions of the author. The facts and opinions appearing in the article do not reflect the views of IIA and IIA does not assume any responsibility or liability for the same