The insurance industry today is overwhelmed with a large amount of data from a myriad of sources and devices. 90% of the world’s data has been created in the last two years alone. Underwriters are put under great duress to gather and aggregate the right mix of data to conduct risk assessment, curate personalized customer experiences and issue policies within the same day. While some insurance carriers have incorporated some form of digital transformation into their processes, many have yet to undergo a digital transformation and provide their underwriters with bespoke risk data that enables their underwriters to perform to the best of their abilities.
The reality is, an underwriting transformation is not a one-and-done affair. Continuous monitoring, assessment and testing is required to see substantial progress. Insurers can take the burden off their underwriters by utilizing and combining various emerging technologies and alternative data sources. The insurance industry is moving at such a rapid pace that insurers who do not make the jump sooner than later will trigger and descend into an unrecoverable tailspin. The unfavorable outcomes can be seen in adverse risk selection, difficulty in employee retention as well as distribution partner exits.
To ensure that your organization overcomes and conquers the digital disruption, let us chart a digital roadmap for you to multiply value creation by transforming your underwriting processes.
The Role of Technology in the Future of Underwriting
From data gathering to risk profiling and finalizing on the premiums, technology plays a crucial role in redefining the underwriting services,function and creating an efficient and flexible delivery system. By leveraging the data from various devices, sensors and IoT technology, it is possible for insurers to provide dynamic pricing and customized policy programs to their consumers. To break down and process large amounts of raw, unstructured data, the following technology can be used to convert data and provide better customer value.
- Blockchain
Blockchain is used to automate the payout functions based on predefined conditions and also the claims function by verifying coverage between reinsurers and companies. An analysis by Gartner estimates blockchain will generate $3.1 trillion in new business value by 2030.
- Predictive analytics
Insurers deal with an unfathomable amount of data on a daily basis. This data is gathered from various devices, customer and agent interactions, smart homes, social media, etc. Predictive models such as the ‘what-if’ model aid insurers in preparing for change accurately.
- Behavior-driven models
Devices play a huge role in framing outcome-based services for customers. Leveraging mass real-time data from customers enables insurers to make the underwriting process faster, cheaper and effective. However, consumers are becoming increasingly apprehensive over the security of their personal data due to various security breaches.
- Digital labor
Leveraging a digital workforce that can dynamically adapt to disruptions enables organizations to be immune to unforeseen events and recover quickly. By using cognitive virtual assistants, robotic process automation and various AI-based solutions, insurers can streamline their processes and strengthen their resilience.
Reimagining the Stages of the Underwriting Value Chain
The main issue that underwriters face is being burdened with compiling information manually and dealing with multiple systems. By automating the entire value chain, you allow your underwriters to free up valuable resources and master analytic skills instead of mechanical tasks. Having an AI-enabled and streamlined platform greatly boosts productivity and efficiency. Below is a reimagined underwriting value chain:
- Intake – Extracting data via Natural Language Processing, Text Analytics and Optical Character Recognition.
- Triage – Using recommendation engines and machine learning to prioritize submissions based on likelihood of policy purchase.
- Risk Assessment – Leveraging virtual assistants, third-party data, and intelligent rules engines to evaluate risk.
- Pricing – Price scenario modeling through the use of data visualization, decision support systems and machine learning.
- Processing – Utilizing virtual agents to wrap up the transaction closing process and digital workflow tools to improve customer engagement.
The Exponential Role of The Future Underwriter
According to a survey conducted by Deloitte involving 19 chief underwriting officers and business leaders, underwriters would have to take on newer and more critical decision-making roles as technology automates their manual tasks. The new roles and responsibilities have been aggregated under five personas:
- Data Pioneer:
With the emergence of predictive data analytics, underwriters should work closely with data scientists to streamline the digital workflow. By collaborating closely, underwriters can thoroughly understand the process and refine their platforms, automate rule sets and conduct exhaustive performance tests.
- Deal-maker:
Partnering with the sales team to break down the rationale behind their pricing and to help negotiate alternative T&C’s, underwriters can simplify sales closures and also assist account managers in identifying attractive risk segments and developing go-to-market strategies with producers.
- Technology Trailblazer:
“Underwriters are starting to own implementation of AI programs and are driving automation priorities by working on rule engines and their interfaces. This progression is likely to continue as real-time underwriting decisions become more important,” says Heather Milligan, senior vice president, life underwriting at Lincoln Financial Group.
- Risk detectives:
Freeing up valuable times has a direct effect on underwriters performing more risk assessment duties and identifying signals to foresee events that can be avoided. They can also spend more time to get involved with industry groups and implement innovative risk assessment models.
- Portfolio Optimizer:
Underwriters will have a more detailed understanding of data analytics and will naturally be equipped with the tools to optimize their portfolios. In order to maximize efficiency around budget allocation, the market intelligence can be used to further develop more sophisticated solutions to stay ahead of the competition.
Conclusion
To summarize, the role of the underwriter is going to shift from being a data sorter and aggregator to more of a collaborator, who harnesses the power of modern technology to accurately, efficiently, and cost-effectively create policies. The role of automation will go hand-in-hand with the underwriter to assist them in repetitive tasks. Through rigorous testing and experimentation, ideal systems can be built to keep the insurers at the forefront of the insurance industry.
