By Geetesh Garg
Over the decades, the insurance industry has played a significant role in not only supporting financial expansions and infrastructure developments of a country but also securing its gross domestic product (GDP). The industry holds a vital objective, that is, to protect the country’s citizens, their businesses, and resources and hence, the insurance industry has always been closely connected to a country’s business operation.
While the insurance industry continues to be the guiding stick for a country, insurance underwriting has also played a critical role in the process of issuing insurance policies. A job that evaluates an organization’s risk in insuring numerous segments such as car, home, an individual’s health, etc. Underwriters examine the amount they are going to write in relation to the premium that is being paid for that risk and decide whether or not to write that risk followed by policy issuance for an individual or a business entity. Any wrong conclusion can actually affect the insurer’s solvency ratio further impacting the balance sheet as millions of dollars are at stake.
Although Forbes listed insurance underwriting as one of the “10 most endangered jobs in 2015,”, citing data from the Bureau of Labor Statistics (BLS), US that forecasts employment in this role is expected to fall by 6 percent between 2012 and 2022, from 106,300 insurance underwriters in 2012 to fewer than 99,800 in 2022. There are partnerships between several tech giants and insurers resulting in developments of the products available in market such as IBM’s Watson and the SymbioSys underwriting engine that are fueling the fact that underwriters might be replaced by off-the-shelf softwares.
Traditional vs automated approach
The traditional ways of dealing with linear processing to quote insurance policy has rapidly changed from month(s) to days and further to few clicks. Thanks to the emerging technologies like “Internet of Things”, “Artificial Intelligence,” and “Machine Learning” that are revamping the overall underwriting process with the help of the readily available customer data. The growth in the large amounts of data has initiated this predictive risk management approach.
Companies are moving to a more robust analysis of risk attributes and applying a dynamic approach to their evaluations by gaining insights from the data. This allows them to be aware of the changing aspects of risk ahead of the market and also ensure they are competitive and are aligned with the needs of their prospective customers. A trend that looks promising for the future is that tomorrow’s top performers in the industry will have underwriters who play considerably varied and diversified roles such as sales executive or decision scientist or customer advocate or an innovator further empowering business process innovation and also providing cross functional support.
According to the industry analyst firms, super computers’ cognitive capabilities is one of the most prominent reasons behind this cultural change. A lot of research and development is happening, and enterprises are making huge investments to take the first mover advantage. For instance, IBM has invested billions of dollars creating a Watson supercomputer. The main USP for Watson is that just like a human, it learns from whatever data is fed into it and is able to analyze and perform the deepest research and give suggestions, in a simple and understandable language.
Productivity Measurement
With the evolving technologies, traditional ways of measuring the productivity of underwriters on performance indicators like percentage of applications approved, turnaround time etc. would no longer be relevant. As the industry is showing signs of maturity for embracing the cultural shift, the performance indicators have to match the new age underwriting process. Few of the key performance indicators include fine-tuning the AI algorithms for analyzing the data, identifying upfront which risk class is favorable, preparing the better risk assessment models leading to lower expense ratio, etc.
Though it is just a thought based on the fact that industry is evolving and eventually over a period of time, these will get more refined and in line with the prevailing market theme.
To sum it up, on one hand where the future of insurance will be determined with the advent of powerful new technologies, there will be challenges for finding the right talent to capitalize on this data driven transformation. At the same time, due to practical and strategic reasons, underwriters have a clear and urgent opportunity to diversify their skills going ahead that can be in line with the changing landscape of the industry as a whole.
Also, we may say that although the underwriting role may be at the brink of closure, there will still be a need for them to spend a good portion of their time interacting with potential clients and brokers proving they are excellent “people persons” as well as they need to keep themselves updated with the latest market trends and technologies. With their experience and good judgement, they will further fine-tune those AI solutions rather than just defining the workflow or playing with BPM tools. This shift to prognostic risk measurements to highly data scientific roles will be one of the key factors that will break the status quo and will decide the future path for underwriters down the line.
(The author is Consultant – Business Solutions & Consulting Group, GlobalLogic)
