Over the last decade we saw a major shift in how our industry embraced the cloud for many of its application services. Now, it is not uncommon when speaking to IT teams about their technology strategies that they are “Cloud First” where every new solution bought will be SaaS unless determined otherwise. We are now at the doorstep of the “Automation First” strategy influenced by the rapid evolution of artificial intelligence (AI). You may have not heard the term used yet, but it’s coming. The rapid advances in AI will significantly influence all processing aspects of insurance in the years ahead. Intelligent automation is the new game changer. We are only at the beginning of the digital evolution, and it has the makings for a long and wild ride. Intelligent automation is the propellent that will power the next transformational decade in insurance.
As of today, the insurance industry has only begun to test the water with AI. But it is now top of mind in many of the conversations I have with clients and core system and solution providers in the industry. The road to joining the AI evolution goes from the first adopters to those that would rather wait and see. Even what has been the basic foray into process automation, Robotic Process Automation (RPA) is getting significantly smarter with the integration of intelligence into RPA platforms. This will increase the value proposition for RPA as over 80 percent of the insurers that participated in one of our surveys noted they have RPA inhouse.
For an industry that has been notoriously slow to adopt to change, it doesn’t seem to be the case now. This is likely due, in part to the rapid digital acceleration forced by the pandemic and the subsequent void in skilled labor that hasn’t come back to work.
AI is only going to continue to get more advanced and more refined.
NLP has made significant strides in programming machines that can understand and have a general understanding of human language: “Hey Siri lookup … “. But the next step is to not only to understand what you say but also what you mean. A lot of future focus will be on natural-language semantics.
Machine learning and deep learning algorithms will self-improve over time without programming, providing even more accurate and complex insights. ML will continue to decrease costs and increase its impact on areas such as underwriting, lead generation, claims, and fraud.
For OCR, continued investment in handwriting analysis, will lead to improvements in the accuracy of reading documents of all kinds. This will also directly improve the capability to convert unstructured data to structured data, enabling insurers to identify new trends, emerging risks, and future forecasting and develop new products in response.
What does this all mean? It means that the mostly standard tasks in the claims and underwriting process will be handled by machine learning algorithms making the process more accurate and streamlined. Human interaction will transition to the more complex processes and as machine learning improves as more data is assessed, the associated algorithms will improve as well for increasingly complex scenarios. We expect to see a lot of the human touch that currently in the process go down considerably over the next decade as AI continues to evolve.
Insurers, platform providers, and service integrators will be acutely focused on turning automation into speed and efficiency for both cost savings and a competitive advantage. The forward thinkers in our industry are already realizing significant impact from automation. But no matter where you are within your automation journey, you must continue to reimagine technology platforms and operating models through automation to stay competitive.