Disaster and insurance have always shared a symbiotic relationship – one begets the other.
In 2022, insurers shouldered historic underwriting losses. Worsening results continued in Q1 of 2023 for the US property and casualty (P&C) industry, posting its first and largest net underwriting loss in the first quarter in 12 years. As a result, carriers are exiting major markets like California and Florida, or halting new business altogether, citing reasons such as “catastrophic exposure.”
To assert that insurance cannot be offered because of “catastrophic exposure” represents a complete failure of an organization to demonstrate its value and, hence, reason for existing.
In a recent interview with SAS, Robert L. Pick, EVP and CIO of Tokio Marine North America, explains the immense potential of using AI in a "data-rich industry such as insurance." He sees AI deployed ethically into all disciplines across the insurance enterprise, acting as a trusted advisor or "copilot" and complementing the skills and experience of existing staff for underwriting decisions, claims handling or pricing.
Considering this discussion, a new benchmarking study reveals that SAS Viya is, on average, 30 times faster than commercial and open source alternatives and scales better with larger and more complex data. For insurers, SAS doesn't just offer an analytics platform. It offers cloud-native solutions and support for every stage of the insurance equation.
And for insurers suffering from increased frequency, severity and expenses, here are three ways they can realize operational and business benefits through sophisticated cloud computation.
1. Ability to revolutionize insurance premiums with data-driven pricing
Data fuels the rate-making function. In order to introduce competitive premiums into the marketplace, insurers need an end-to-end pricing solution that yields results fast. While testing Viya against competitors on 300 million unique data points, Viya delivered results in under 12 minutes, while two competitors hit a brick wall: They ran for hours before failing to yield any results.
Insurers cannot afford to invest time into building models only to have them fail – or waste hours and hours waiting for results to come back.
2. Customers get the personalized experience they crave
Today's customers demand personalized experiences. They want to feel recognized and understood, regardless of how they do business. While insurers have established multichannel distribution, creating a rich and immersive omnichannel journey for customers requires the integration of disparate data sets. In short, when data integration lags and practitioners cannot make real-time decisions, insurers risk losing customers.
These losses are especially devastating to the bottom line because insurers aren't just forfeiting the future value of customers; they're yielding sunk costs from acquiring them in the first place.
3. Enhanced claims management with the cloud
Insurers have a duty to act in good faith and conduct proper claim investigations. Investigators consume mass quantities of data while fulfilling this promise to their customers. Cloud computing and artificial intelligence can help analyze this data and its connectedness and help investigators quickly determine coverage or identify fraud.
Without the necessary computing power, insurers will experience increased claim volume, leading to poor investigations and subjecting insurers to bad faith accusations, all while missing fraudulent behavior. Associated loss results will feed back into increasing rates and erosion of competitive position.
The future of insurance and AI
All countermeasures insurers deploy to improve results will create ripples in the business. Introducing more sophisticated and competitive rates into the marketplace adds pressure to capital requirements, regulatory compliance and expenses. Incorporating new risks into the portfolio increases claim volume and additional need to fight fraud.
Yes, powerful computational speed adds value, allowing insurers to run complex business processes autonomously and in real time. However, the return on investment will be short-lived if the AI creates additional risk.
SAS offers AI solutions that incorporate trustworthy AI capabilities across the entire AI and analytics life cycle: robust data management, model interpretability, bias mitigation, model risk management, model management and more. SAS also supports customers with a range of cloud deployment options, consulting services and comprehensive training on the responsible use of our technology.
The Futurum study illuminates a path for insurers to realize significant business value. "SAS Viya helps users lower computing costs and consider more data to drive intelligent decisions faster," says Russ Fellows, Senior Partner and Analyst at The Futurum Group.
Not all AI is created equal, and a decision to deploy AI can make or break the future of any organization - so make it a good one.
