Future Undercurrents for Insurance Underwriting

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Insight categories: AI and MLPerspectiveFinancial Services

Introduction

Insurance underwriting is a process of analyzing and evaluating the risks involved in insuring people and assets. However, with a surge in technology, almost every aspect of life has become technology-oriented. The advent of software has put individual underwriters and their jobs at great risk. We are observing a diametric shift from risk management to scientific data analysis. In an era of the machine versus the mind, will insurance underwriters be able to sustain themselves?

What’s Coming Your Way

According to Forbes, insurance underwriting was listed as one of the “10 most endangered jobs in 2015.” Citing data from the Bureau of Labor Statistics (BLS), U.S., it forecasts that employment in this role is expected to fall by 6 percent — from 106,300 insurance underwriters in 2012 to fewer than 99,800 in 2022. The partnerships between several tech giants and insurers have resulted in the development of products such as IBM’s Watson and the SymbioSys underwriting engine, which are fueling the fact that underwriters might be replaced by off-the-shelf software.

This article is not just limited to the role of underwriters and the possibilities in technological advancements. It will also touch upon various technologies that affect the insurance industry and whether it will be apt to believe that humans will be replaced by the computer algorithms.

What Does an Underwriter Do?

Underwriting is a job that has existed for as long as there has been a need for insurance. It’s one of the critical steps involved in the process of issuing insurance policies. Underwriters examine the amount they are going to write in relation to the premium that is being paid for that risk. They 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.

Traditional vs Automated Approach

To quote insurance policy, the traditional ways of dealing with linear processing has rapidly changed from month(s) to days, and further, to a few clicks. Emerging technologies like the Internet of Things, Artificial Intelligence, and Machine Learning are revamping the overall underwriting process with the help of readily available customer data. The growth in these large amounts of data has initiated this predictive risk management approach.

Companies are moving to a more robust analysis of risk attributes and are 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. It also ensures that they are competitive and 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 diverse roles, such as sales executive or decision scientist, customer advocate or innovator. This will further empower business process innovation and also provide cross-functional support.

According to the industry analyst firms, supercomputers’ cognitive capability 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 of Watson is just like that of a human: it learns from whatever data is fed into it. It is then able to analyze, do research, and give suggestions in a simple and understandable language.

Productivity Measurement

With the evolving technologies, traditional ways of measuring underwriters' productivity 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. Some 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, over a period of time, these will get more refined and in-tune with the prevailing market theme.

A Note Before We Part

On one hand, the future of insurance will be determined by the advent of powerful new technologies. There will be challenges to find the right talent to capitalize on this data-driven transformation. On the other hand, due to practical and strategic reasons, underwriters have a clear and urgent opportunity to diversify their skills moving forward, which 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 these individuals to spend a good portion of their time interacting with potential clients and brokers, proving they are excellent “people persons.” They also need to keep themselves updated with the latest market trends and technologies.

With their experience and good judgement, underwriters can further fine-tune these emerging AI solutions rather than just define the workflow or play with BPM tools. This shift from 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.