The insurance industry, which has historically operated on razor-thin profit margins, now faces mounting pressure from both new competitors and shifting customer expectations. Insurtech disruptors leverage cutting-edge technologies to provide faster service at lower cost, resonating with modern policyholders – 85% of whom demand quicker insurance purchases.
To survive in this challenging environment, incumbent insurers must transform their underwriting operations. Specifically, they need solutions to more accurately price a greater volume of policies in less time. In this post, we‘ll explain why updating underwriting is an imperative and introduce seven technologies enabling insurers to effectively meet today‘s demands.
The Need for Effective Underwriting
Effective underwriting balances three elements:
- Accurate risk pricing – Assess expected losses to optimize profits
- Diversification – Spread risk across geography, policy type, etc.
- Speed – Issue policies rapidly enough to satisfy customers
Underwriting involves estimating the likelihood and costs of a loss event affecting people, properties, or businesses. Insurers then offer a policy covering specified losses in exchange for premium payments that reflect the risk profile. Policyholders mitigate their exposure by transferring some uncertainty to the insurer.
But underwriting is more than just risk scoring. A diversified book of business and responsiveness are equally vital.
Why Improving Underwriting Matters Now
Enhancing underwriting capabilities is among the best ways for insurers to boost profitability.
The return on surplus (ROS) ratio indicates profitability relative to reserves. It divides net income by policyholder surplus (assets minus liabilities). A higher ROS signals a stronger financial position.
From 2007-2017, the average P&C insurer ROS was 11.6%. However, 80% of firms scored at or below 11.3% – far from the mean due to a few high performers skewing the average. This indicates most insurers earn lackluster returns.
A McKinsey study showed that top quintile P&C insurers generated superior results by adopting advanced underwriting capabilities before competitors.
With profitability already constrained, insurers must upgrade underwriting to remain viable.
1. Advanced Analytics
Sophisticated predictive analytics enable insurers to price risks precisely and rapidly while optimizing their book.
The most accurate method of estimating future claims is analyzing policyholders‘ background data. Relevant variables for pricing health insurance policies could include:
- Age
- Tobacco use
- Alcohol consumption
- Diet
- Medical history
- Exercise frequency
- Occupational hazards
- Family medical history
Advanced AI and machine learning models can process thousands of datapoints in seconds to quantify correlation and causation between variables and expected losses based on historical actuarial data.
Modern portfolio theory relies on mean-variance analysis to construct optimized portfolios. Insurers now use analytics approaches similar to robo-advisors to diversify their underwriting book and manage concentrations.
Behavioral analytics assess website activity to estimate fraud potential. This allows insurers to reward low-risk policyholders rather than penalizing all customers for fraud risks.
2. Natural Language Processing
Like advanced analytics, natural language processing (NLP) improves risk scoring accuracy. But while analytics utilize structured data, NLP leverages unstructured text and speech.
Insurance depends heavily on document evaluation, including questionnaires, claims forms, and doctor’s reports brimming with textual data. NLP techniques help make sense of these materials by extracting insights and detecting patterns.
For example, an NLP model could pinpoint correlations between certain answers on an application and eventual loss activity that underwriters may miss but indicate higher inherent risk.
3. Optical Character Recognition and Handwriting Recognition
OCR and HWR technology allow insurers to digitize scanned paper documents, opening new troves of data to feed analytics and NLP systems.
Insurers still depend on paper documents to understand customers and markets. Two reader technologies bridge the divide between analog documents and digital systems:
- Optical character recognition (OCR) interprets printed text
- Handwritten character recognition (HWR) reads handwritten documents
OCR and HWR alleviate tedious and inefficient manual data entry. Underwriters spend over 50% of their time transcribing documents into systems. Automating this process gives insurers more manhours to dedicate to high-value tasks.
4. Digital Twins
Digital twins are virtual clones of real assets like buildings or cars used to run simulations analyzing thousands of risk scenarios. Insurers leverage twins for two key reasons:
- Test portfolio resiliency to ensure diversification safeguards longevity
- Model losses for rare events with sparse historical data
For example, major volcanic eruptions near Naples, Italy are infrequent but could produce catastrophic insured losses. Simulating thousands of eruption scenarios with a digital twin of the region allows insurers to more accurately price the risk.
5. Internet of Things
By connecting billions of sensors embedded in common objects, the Internet of Things (IoT) massively expands insurers’ data universe. Consider what new datapoints IoT enables across key lines:
| Line | Pre-IoT Data | Post-IoT Data Added |
|---|---|---|
| Health | Age, Questionnaires, Doctor Reports | Exercise, Sleep, Heart Rate |
| Auto | Make/Model, Accidents, Age | Braking, Mileage, Location |
| Commercial | Questionnaires, Industry | Equipment Usage Data |
Data from smartwatches, autos, factories will help transform underwriting.
Pay-as-you-drive auto insurance also incentivizes safer driving. However, more smart devices mean elevated cyber risks, underscoring the need for cyber insurance.
6. Application Programming Interfaces
While IoT expands available data and analytics interpret it, APIs enable seamlessly piping external data into underwriting systems.
APIs help efficiently extract information from outside databases. For cloud-based underwriting, they optimize costs.
Per Deloitte, open insurance APIs could reduce policy issuance costs by 70%.
APIs also facilitate valuable open insurance business models. As one example, Lemonade shares its claims API with auto insurers so linked claims can be settled simultaneously, amazing customers.
For more API insurance use cases, see Top 6 API Examples in Insurance.
7. Blockchain
Certain useful underwriting data like medical records contain sensitive personal information. Regulations like GDPR restrict sharing such data with third parties.
Blockchain provides a encrypted, decentralized way for insurers to leverage these datasets without directly accessing confidential data. Policyholders benefit if smart contract conditions based on their data are met.
For instance, insurers could deploy smart contracts gathering encrypted health data from wearables to pay for gym memberships and other "living benefits" that reduce eventual claims.
The Technologies in Action
We‘ve examined 7 advanced technologies modernizing insurance underwriting. Let‘s see how they work together to help insurers succeed:
- Data Expansion – IoT and document digitization feed exponentially more data points into underwriting systems
- Analytics Power – Advanced analytics and NLP models derive insights from massively expanded data
- Simulation – Digital twins allow complex risk scenario testing unavailable before
- Efficiency – APIs seamlessly pipe external data into underwriting systems
- Trust – Blockchain overcomes data privacy obstacles that could limit underwriting
Together, these innovations enable insurers to accurately underwrite more business faster. This unlocks greater profit potential while satisfying today‘s on-demand customers.
Legacy insurers must now follow the lead of high-performing peers and insurtechs by adopting modern underwriting capabilities. Those who digitally transform underwriting will sustain a durable competitive advantage.
Underwriting excellence hinges on balancing advanced analytics for precision pricing with speed and diversification. New technologies now allow insurers to effectively strike this balance. Companies that leverage AI, IoT, blockchain and other innovations will be best positioned to thrive in the years ahead.
