Can Automated Underwriting Impact Quality of Your Customer Base?
Evolving customer expectations is making the underwriting function a key area for greater digitization. With new innovative entrants, customer service is coming into the picture a lot sooner in the customer journey than it used to and customer journeys are being personalized from the very first touchpoint. This is a move away from the traditional route of seeing underwriters as the first line of protection for an insurance company and customer service was the responsibility of another department.
One study by McKinsey shows that customer satisfaction is the most important profit engine for insurers, beating out advertising and even lower premiums. Underwriters play a crucial role in one of the first customer touchpoints and can greatly influence customer retention and drop-off rates., while this is always known, it is being factored in now as the starting point of personalizing the customer journey.
Insurance carriers are moving away from considering ‘every claim as a failure in underwriting’ and instead are looking at underwriting to deliver smoother, more personalized experiences to customers.
Achieving underwriting excellence in today’s customer-centric world will mean reimagining risk selection, leveraging advanced applications of AI and ML, and redesigning customer onboarding.
Improved data quality is opening up new underwriting opportunities
The unprecedented access to customer dat that underwriters now have means that traditional forms of risk selection might no longer be valid. In health insurance, for example, serious pre-existing conditions like diabetes or obesity might require individuals to pay higher premiums as they pose a higher risk but assuming every diabetic has the same risk, is unfair. Today there is a wealth of data that can paint a more holistic, personalized picture of the individual for more accurate risk selection.
Underwriters can access a person’s day-to-day fitness levels through wearable devices, monitor their long-term control over their condition, and track health programs that they’ve participated in. These metrics take into account that most long-term conditions exist on a spectrum and that not all patients can be measured by the same yardstick.
This principle of data-driven risk selection can just as easily be used by auto insurers and P&C insurers.. In P&C insurance, underwriters need to account for various aspects of performance, including previous responses to catastrophes or losses. IoT devices are providing a data-driven insight into auto insurance underwriting that many insurance carriers are already implementing. Usage-based insurance where good drivers are rewarded with lower premiums will soon be a rule rather than an exception.
AI & ML can reduce processing times
New sources of information are churning out higher volumes of data. Raw data needs to be cleansed before it can provide insights. However, data quality assurance when dealing with this amount of data can only be accurately performed by advanced AI and ML applications. This is also crucial because applications can perform data extraction in a fraction of the time it would take for humans to perform the same task.
AI and ML applications can perform data extraction in a fraction of the time it would take for humans to perform the same task.
Today, when customers can get quotes from online insurance providers in a matter of seconds, maintaining fast processing times in underwriting can be a key differentiator.
Large commercial brokers also prefer to work with providers who consistently maintain high levels of underwriter productivity. However, bringing on more underwriters to achieve this is not sustainable for an insurance provider. SimpleINSPIRE, for instance, uses Machine Learning and AI to automate several manual processes such as data extraction from PDFs and printed documents and assessment of data quality. Automated underwriting reduces the time taken to process submissions and perform data quality assurance checks, helping underwriters focus on the more strategic aspects of their roles, such as managing broker relationships.
For customers, automated underwriting means shorter waiting times, higher satisfaction, and more accurate processing.
SimpleINSPIRE also uses an elastic search (ELK) based on the Lucene search engine. This feature can sync elastic data in real-time and support system-initiated searches. This enables intelligent underwriting in insurance and improves the quality of customer service.
Faster triaging of incoming requests
A significant portion of incoming submissions are straightforward and can be easily handled through automated workflows. However, in most cases, these submissions are still sent to underwriters who have to manually process them. Apart from the increased turnaround time, certain risk classes might need a differentiated process and elite underwriters specialized for this might be busy with routine tasks rather than high-value submissions. Such flexibility is absent from current underwriting workstreams.
A more efficient approach for underwriting in insurance would be to use intelligent rules to triage incoming requests based on their complexities, automate routine queries, and route only complex and high-value submissions to underwriters. A prioritized work queue will improve the premium yield per underwriter. Since submissions are processed faster, your customer satisfaction rates improve and your business can gain a loyal customer base.
Auto-assignment rules can also be applied according to industry categories. P&C insurers, for example, largely see SMEs as homogenous entities. Despite some variations in their risk profiles, coverage for small and medium enterprises are largely standardized. These applications can largely be automated to reduce processing times. Mid-market companies are more complex than SMEs but are not as varied as large companies, so some stages can still be automated. Large enterprises have the highest range of variability and therefore, underwriters can use the time saved through automation to spend more time on these requests.
Increase transparency through self-reporting
Improving the quality of your customer base also extends to building an onboarding process that is customer-centric. Most insurance carriers today have application processes that are designed to collect information that underwriters need rather than to provide customers with a hassle-free experience.
Customer-centric processes like quick questionnaires on the website can improve the customer journey and lead conversion rates. Carriers should keep in mind certain guidelines when framing the questionnaires to ensure that underwriters get accurate information to base their decisions around. In general, questions should be as concise and straightforward as possible. Long questions with technical jargon can confuse respondents and lead to inaccurate answers. Studies have also shown that customers tend to fill in questions more honestly if they are required to sign or check a declaration form before submitting the questionnaire.
As customers seek more transparency from insurance companies, self-service will become a crucial distinguishing factor in a company’s customer service. SimpleINSPIRE’s Policyholder Self-Service feature bridges the gap between customers and underwriters. Through the portal, customers can check their approved coverage, access their policy documents, and make payments online.
Transforming an organization is not an easy decision but using technology and digital as innovators has a value-promise that is hard to ignore. The first step is to transform the underwriting function. It is after all the gatekeeper to a brand promise that customers will experience with each interaction in their journey with the insurance brand they choose.
Topics: Intelligent Automation