Other parts of this series:
Advances in AI can help underwriters manage their rising workloads and sharpen their decision-making.
There’s been plenty of discussion in all sorts of forums about how artificial intelligence (AI) could undermine jobs in many big industries. AI can certainly improve efficiency and productivity. The big benefit of this technology, however, is its ability to enhance the performance of workers.
AI has huge potential to assist workers in all facets of the insurance industry. Underwriting, especially, offers great opportunities for workers and intelligent machines to collaborate. As I mentioned in my previous blog post, underwriters are having to contend with a multitude of new risks. Many of them are highly complex and unfamiliar. What’s more, they must also manage an abundance of new data sources. These additional streams of data are certainly a boon for insurers. They can provide sophisticated insights, often in real-time, into a wide variety of risks. Managing this deluge of information, however, is becoming increasingly challenging.
Recent advances in AI can help underwriters manage their increasingly complex workloads as well as improve their decision-making. Our research shows that most insurers have been slow to apply AI to their underwriting processes. They still rely heavily on large teams of underwriting professionals. Unfortunately, many of these underwriters spend much of their time performing mundane tasks such as manually entering data into online applications. We found that most underwriters spend less than half their time processing core information. Furthermore, less than a quarter of their time is spent selling or engaging with brokers.
AI can help underwriters work far smarter. It can free them to focus on high-value activities and help them make faster, more accurate decisions.
Already around 33 percent of insurers are starting to systematically harness the data they receive from multiple sources. By using AI applications such as intelligent data solutions, these organizations could gather and organize structured and unstructured data from a wide range of internal and external sources. The data could then be aligned according to the requirements of the insurers’ underwriters so they could quickly assess its importance.
About a quarter of the insurers we surveyed are implementing intelligent processes in their organizations. By applying such AI processes to their underwriting, these insurers could improve substantially the performance of key workers. Such applications could include:
- Using cognitive robotics to sort and address basic service requests from agents.
- Deploying intelligent agents to respond to queries from agents and customers and provide them with basic information.
- Introducing self-adjusting win-probability calculators that help underwriters prioritize their tasks.
- Employing smart anomaly-detection systems that identify changes in renewal requests that might require an underwriter’s attention.
- Applying an intelligent demand-analysis system to identify potential new products.
These applications are all likely to enhance an insurer’s underwriting capability. As they constantly learn and improve with experience, their contribution will increase substantially.
In my next blog post, I’ll discuss how insurers should prepare their workforces for the introduction of AI. Until then, take some time to look at these links below.