Augmented Automated Underwriting
Life insurance’s new generation of digital underwriting
Declan O’Neill, Executive Vice president, Product & Data, Munich Re Automation Solutions
The financial services industry is continually digitising, and the life insurance market is no different. For too long, the sector has been saddled with outdated systems and processes. As a result, underwriting has been prone to human error and inefficiency, inconveniencing the insurer and consumer alike.
However, technology is currently playing a key role in the industry’s progression. Today’s customer is increasingly willing to share data in return for a personalised experience, with 60% saying that they are comfortable sharing personal details with their insurer in exchange for lower premiums. So, the onus is on life insurance firms to implement technology that allows them to anticipate customer needs and provide a streamlined experience throughout the life insurance customer journey.
Consequently, augmented automated underwriting (AAU) has come to the fore, as the industry embraces the next generation of underwriting technology. And as underwriting technology continues to evolve from strength to strength, it’s worth looking at its evolution, and where technology will take the industry next.
Black-box systems initiated the industry’s transition to automated augmented technology. These systems introduced clear casing for pre-existing back office models that were used before modern digital underwriting engines.
Such capabilities were developed by underwriters and sought to introduce automation to the process. The black-box systems ensured that life insurance customer application forms with no disclosers were quicky processed, accelerating the onboarding process efficiently.
Still, there was plenty of progress to be made. These systems offered little insight into the philosophy of how to improve underwriting in a wider sense, with their code-based nature significantly limiting their ability to adjust to boundaries.
The next stage of the industry’s technological advancement is the implementation of electronic underwriting. The crucial differentiator between this and the previous phase is the ability to enhance the underlying philosophy of underwriting, which black-box systems weren’t able to do.
Essentially, electronic underwriting introduced the concept of behavioural economics and data to the life insurance space. At this point, insurers were considering psychological insights from customer information into their decision making, paving the way for predictive capabilities further down the line.
That said, these electronic underwriting abilities have significant constraints. Instead of being fully digitised, they still require IT and human programming expertise. And following initial underwriting interviews, potential change requests must still be sent to reinsurers for manual input, creating lengthy queues and significantly hindering efficiency.
The next stage in the evolution of underwriting technology adds flexibility and greater empowerment to individual underwriters.
Here, descriptive analytics enables underwriters to implement statistical techniques to summarise data. Insurers can take insights from dashboards, reports and graphical user interfaces (GUIs) and analyse them effectively to offer customers the best premiums.
In essence, descriptive analytics allowed underwriters to manage new business process with ease, without depending on IT and programming expertise when looking to change rules, significantly improving efficiency.
Currently, most life insurance businesses still implement second or third-generation systems, despite the evolution continuing. The next stage of innovation unlocks deeper insights from customer data, creating opportunities to increase sales and maximise customer satisfaction.
However, most insurers are yet to take the step.
The fourth generation introduces advanced analytics – a huge stride forward in the underwriting process.
Identifying patterns and using data points to make all-important connections is at the crux of risk-based decision making in a process such as underwriting. And while identifying such patterns is often beyond human capabilities, advanced analytics can do so accurately and almost instantaneously.
Crucially, this stage introduces artificial intelligence (AI) and machine learning techniques to life insurance underwriting. Conveniently, this technology allows insurers to quickly determine which data points are irrelevant or simply redundant. Furthermore, artificial intelligence in underwriting enables insurers to assess risk profiles with appropriate risk management and limit the number of questions asked to the consumer, with no impact on risk assumed by the insurer.
Typically, customers are faced with numerous, intrusive questions throughout their underwriting interview process. The answers are often straight-forward yet the questions are repeated, and this often deters consumers from following through with purchasing life insurance.
AI and machine learning significantly improve the customer experience. They enable insurers to gain a deeper understanding of customer data and make better-informed decisions. Through removing friction, this approach improves the overall experience for the end customer and gives insurers optimal results, with maximum efficiency.
It’s one thing to embark on advanced analytics initiatives, but it’s another to effectively deploy them in the long term. In doing so, fifth generation systems can integrate predictive models into existing automated processes, thereby augmenting previous automated underwriting capabilities or AAU.
Now, insurers must ensure this is the norm in order to reap numerous benefits. For instance, AAU has the capabilities to attract more customers to the life insurance application process and increase the chance they will complete the application process, benefitting both customer and insurer.
Leveraging artificial intelligence in insurance underwriting lets companies accurately calculate an applicant’s risk in advance and therefore reduces onboarding barriers. And throughout the process, this technology streamlines the underwriting process significantly and improves turn-around times, all while insurers can reduce manual and underwriting and medical evidence costs for the insurer.
Fundamentally, AAU offers life insurance companies an opportunity to transform the customer experiences they provide. Models deployed allow life insurers to reduce the number of questions asked during underwriting interviews and be more considerate of their customer’s time.
Finding an underwriting approach which encompasses technology, analytics and industry expertise is a complex journey. Providing value to consumers while remaining efficient is challenging. However, as firms are forced to adapt to changes being forced on the industry, AAU combines with existing systems and enables insurers to adapt accordingly, while reinventing the end customer’s experience.