Inflation, climate change, supply chain disruption, and an unending pandemic is a list of concerns that most businesses would agree are top of mind for 2022. But for the property and casualty insurance industry, these concerns are particularly acute as all four of them can drive up rates and increase the number of claims. As one industry executive put it recently: "they are exogenous factors, externals over which the industry has little control. The industry is not suffering from poor management of issues about which it does have control, like the use of capital, reserving, or pricing."
These outside issues add to a need for smarter data, efficient operations, and a digital approach. So it’s no wonder that AI is finding traction within the insurance industry. With an expected ceiling of almost $700 billion in claims in 2021, McKinsey has called it “ripe for disruption.” Over the years, it has lost ground to other types of insurance such as auto coverage and intellectual property protection from cyberattacks. One of the defenses against that disruption recommended by McKinsey and others is AI, as it provides the data to mitigate risks and even spawn new product offerings.
According to Gartner, by 2024, investment in AI will rise by 40 percent as insurers shift from automation to human support initiatives. Those investments so far have found the sweet spot in customer experience (65percent, according to a 2021 PwC study). Aside from the human element, the sheer volume of data in the P&C business makes AI the ultimate management tool. Consider that when it was in test phases back in 2018, driverless cars generated 30 terabytes of data a day. There are many areas in which AI can improve the P&C business, all of which can streamline its processes and generate more revenue. We’ve picked five that have the most potential:
1. Better Risk/Reward Calculations
It is the bedrock of the business. Evaluating a property, calculating the potential risk to that value, and then adjusting the rates used to be a manual and decidedly analog process. As early as 2015, re-insurance companies (reinsurers take on risks that are too large for insurance companies to handle) were seen as more profitable and growth-oriented than insurance. The risk and reward were already known for the re-insurers like Berkshire Hathaway and Swiss Re, and profits followed. For example, a retail center being built near a flood zone is a much higher risk than one constructed inland.
The calculations for that risk, rate, and reward were, and sometimes still are, done through human visits and comparable property valuations. Because it is so effective at finding patterns in past behaviors and data, AI is completely changing the way underwriters make these calculations, and they're more accurate as a result. AI allows underwriters to access richer data sets that incorporate rates, risks, and outcomes for thousands of retail centers like the one mentioned in the previous example, and inform a fact-based risk and rate decision. “Back of the envelope” figuring can be relegated to the dust bin.
2. Improved customer experience
AI enables insurers to decrease the claim processing time and make the entire underwriting process more efficient. It can automate analyzing documents and checking them for authenticity and potential fraud. As a result, the customer experience is improved. It is first improved via the lower prices the firm can charge because it doesn’t need to spend as much money on claims personnel. Some estimates put the time required for processing at a week or at least several days. AI could reduce that to hours or even minutes. It would also P&C companies to customize contracts based on unique circumstances rather than “look-alike” estimates.
3. Advanced fraud detection
Building on the customer experience, the same AI algorithm that's built for claims processing can identify fraud patterns. Fraudsters are becoming more sophisticated by the minute, making their work harder to detect and often invisible to manual processes. AI finds patterns that red flag suspicious activity and catches fraud before it's too late. According to global insurance fraud specialist FRISS, 18 percent of all insurance claims carry some fraud attempt or outright crime attached. A typical example is contractor fraud, which reaches crisis levels after a catastrophic event like the recent tornado cluster in Kentucky. Many states have legislation and regulations designed to prohibit contractor fraud, but AI gives insurers the chance to bring data to an in-house effort. Many P&C insurance carriers used data and AI early in the pandemic and throughout the crisis tore-evaluate properties that weren’t being used due to lockdowns, or by adjusting for less vehicle usage and higher residential usage. Because so many claims during the pandemic were filed digitally, online fraud became a pandemic problem. AI became an essential tool to adjust to this digitization.
4. Increased agent productivity
The first three factors all add up to a better experience for the agent. They're able to serve customers more personally, calculate risks, lower losses, and make more commissions. Much of this new experience is driven by chatbots, a direct usage application for AI. Chatbots are used by 80 percent of today’s insurance companies. They’re not unique to the business, but insurance agents can move toward more revenue-driving and customer-retaining activities like customization if a chatbot can handle website queries, appointment bookings, or answering simpler questions. In the future, expect chatbots to handle more complex actions, even providing quotes and collecting payments.
5. Building new models necessitated by climate change
Losses from floods and wildfires don't fit into the standard data models that are built for hurricanes and more minor wind storms. Losses from floods and wildfires have doubled over the past ten years, and Swiss Re forecasts a 63 percent spike in climate-related losses by 2040. Swiss Re also estimates the world stands to lose 10 percent of its economic value from climate change by mid-century. AI is already in motion in this area, with Japan using it to analyze satellite images to predict future disasters. At the same time, NASA reported that it tracked the path of Hurricane Harvey in the United States six times more accurately than traditional monitoring, helping authorities to prepare in advance.
AI has the potential to completely transform the P&C business from one that has been associated with manual processes, decades-old risk calculations, long claims times, and overworked agents to one in which data-driven decisions are the norm. And while data is necessary, the effect AI can have on the human side of the equation is substantial. Agents can be more productive. Customers can be more satisfied. And that list of problems mentioned at the beginning of this piece can prove to be more manageable.
How No-Code AI is Transforming Property and Casualty Insurance
No-code AI is just beginning to proliferate in the insurance business, and it is an excellent step toward the digital transformation necessary for P&C companies to compete and grow. By using a no-code approach, a company’s existing data expertise can easily embrace new data sources, build a new structure for them, and import them into existing databases. The agent considering the risks, rates, and potential reward from that retail center doesn’t have to wait for a new team of data scientists to crunch the numbers, build a new algorithm and generate fact-based results. No-code AI will be an important trend to watch as 2022 plays out. For more information on no-code AI in the insurance industry, request a demo today.
