Leveraging technology to design timely and efficient underwriting processes.
Life insurance companies undergo a rigorous underwriting process to evaluate the risk and exposure of an individual policy. While the exact process will vary by company, coverage amount and customer demographics, it is widely considered to be a critical component of the sales process, feeding into multiple policy level decisions, including:
Whether to accept or decline coverage The maximum level of acceptable coverage Whether exclusions should be applied to decrease exposure The appropriate premium levels for the given risk profile and coverage level However, in a world that continues to demand a customer first approach, the underwriting process is becoming quite problematic as it is a lengthy and manual process riddled with customer pain points. The process typically takes 4-6 weeks to complete and involves numerous customer interactions and intrusive medical exams.
Insurance companies are generally aware of this problem and some have even developed solutions in response. While some of the recent underwriting process modifications have been successful in reducing time and pain points, they are for the most part only applicable to a small subset of the population and to policies with less than $100,000 in coverage. Insurance companies are starting to tackle this problem, however many continue to believe that modified underwriting processes create significantly more policy level risk than the traditional approach that they’ve relied upon for decades.
In the age of advanced analytics and machine learning technology, there must be a way to design an instantaneous underwriting process that alleviates the current pain points without increasing risk.
In this two-day sprint at Cookhouse Lab (Toronto), we will run through a series of design thinking exercises to identify the key components of a simplified underwriting process that would solve this industry wide problem.
Using new technology to industrialize routine underwriting
Requiring eSubmissions to prevent manual reworking and to minimize application errors
Pre-filling manual assessments with 3rd party data
Reinventing the “risk score” by identifying the 5-10 most important risk measures and identifying alternative available data sources to get to the same answer
This is a taster session at the Cookhouse Lab – there is no cost associated with this project. Organizations may send one participant each. Space is limited so make sure to RSVP soon to secure your place!
This project is now full and is no longer accepting applications.
However, we've got some other great things cooking in our kitchen! Visit ourProjects Listing pageto learn more.
What is on the menu
This innovation project will begin with a Lean Startup exercise, followed by the phases of Design Thinking as supported by a variety tools. The ultimate goal is to develop a high-level set of business processes and use cases.