Reassessing Our Underwriting & Risk Data Ecosystems

As innovation accelerates, distribution and BGAs seek ‘friction free’ experiences

by Nanditha Nandy

In the race to achieve higher straight through processing (STP) rates and improve the speed of underwriting decisions, we cannot leave distribution behind. The industry has made great strides in automation and acceleration of underwriting, but successful implementation and adoption of newer innovations requires careful consideration of the end-to-end ecosystem. BGAs are closely connected to, and trusted by, the end customer. Their buy-in is essential.

With the introduction of clinical health data in the underwriting process, there’s an even greater opportunity to collaborate with distributors and collect this information earlier in the process. With easy access to longitudinal health data and deeper insights into their customer’s medical events, distributors would be more equipped to find the right product, provide a more accurate quote, and enable a smoother underwriting process.

Underwriting: Newer Processes, Newer Automation

Clinical health data is one of the most valuable assets for the insurance industry. The underwriting process relies on making sense of significant volumes of relevant data. Traditionally, insurance underwriters used paper-based forms to collect information about client’s health history, lifestyle and other factors. However, today the advancements in digital technology and the ubiquity of digital health data are paving the way for a streamlined underwriting process.

The global pandemic was a change agent for the underwriting community to use medical data, but how much data is too much data? Could underwriting assessments be offered faster and reduce the friction to the customer?

In parallel, tech has enabled digitization of the underwriting process, and the need for legacy systems to be upgraded and connected has become apparent. The lower data storage costs with cloud migrations led to the increase of Health Information Exchange (HIE), electronic health records/electronic medical records (EHR/EMR) and healthcare systems offering connectivity. We started observing improved hit rates with clinical health data. The pandemic also promoted the rapid rise of telemedicine and remote care.

The changes present insurers with an opportunity to leverage digital health data to improve the underwriting processes. The use of digital health data still mitigates risk and keeps premiums affordable in the face of disruptive events like pandemics. The use of digital health data offers insurers significant competitive advantages. By streamlining the underwriting process, insurers can offer underwriting assessments and policies quickly, improving their ability to attract and retain clients. Additionally, the use of digital health data enables insurers to identify potential health risks and offer personalized health and wellness programs to their clients.

Making efficient use of the alternative data requirements came with challenges, not just faced by carriers and reinsurers, but also distributors. The digital data was not in a legible format for underwriters. Many distributors continue to rely on traditional sources such as APS (Attending Physician Statements) reports. To derive meaningful insights from digital health data, insurers must have the right tools and expertise to analyze data effectively. Insurers that lack sophisticated data analysis capabilities may struggle to take full advantage of the opportunities offered by digital health data.

To address the challenge of delivering the key information found in the data into the hands of underwriters and to bypass the reading of long text narration, Swiss Re designed a software as a service (SaaS) platform called Underwriting Ease. Underwriting Ease visualizes and renders the impairment level insights in an actionable manner. The benefits of integrating digital health data into a visualizing SaaS platform include: improved efficiency (our studies estimate cutting down the time taken to assess the case up to half), consistent decision making (training tool to address the talent gap), reduced costs due to minimizing over ordering (builds into the smart ordering framework), enhanced customer experience by increased transparency and trust (consistent information flow through agents, customer, underwriting and claims).

Currently, clinical health data (CHD) is used post automation and post issue. The desire is to use CHD within the insurance value chain and convert into a CHDi intelligence to leverage a longitudinal view of the applicant risk profile. Today, the process of compiling and analyzing data can be time-consuming and cumbersome, requiring significant human effort. The integration of digital health data into a visualizing SaaS platform provides distribution, BGAs, carriers and reinsurers with an aligned view of the risk profile and the missing link to drive innovation across the ecosystem.

Quicker Risk Assessment Solutions

Over the last several years, as a global reinsurer, we have partnered with leading insurers and digital data source aggregators to perform various protective value studies and mortality studies to analyze the effects of replacing traditional invasive evidence with a newer data source.

In certain cohorts of risk profile, we are more confident of the protective value gained from the non-disclosures uncovered from the supplementary sources, and in some other cohorts, we can define rules sets to triage the skipping of invasive labs or APS and use digital clinical labs instead.

In one study, we found that EHRs can help accelerate the decision pipeline, and 50% of the time the underwriters arrived at the same underwriting decision using this newer data source compared to traditional paths.

EHRs are used at the point of care to generate a detailed profile of an individual’s health history. Underwriters’ exposure to EHRs has accelerated since the COVID-19 pandemic but has often resulted in lower automation efficiency and higher manual underwriting time and effort to assess long, detailed and repetitive EHRs. The challenges with efficiency and time are premised on both the inherent challenges of raw clinical data and the challenges associated with industry understanding, workflows and change management.  Since the data has both machine readable and unstructured elements, data semantic normalization can be combined with natural language processing technologies to drive integration into an underwriting rules engine to generate a faster, more consistent, more cost-effective, and more accurate traditional underwriting assessment.

However, integration poses a challenge, and the development and deployment of robust data analysis and visualization tools, which bring everything together in one customer risk view, is needed to move this solution forward

Change Management Needed At All Levels

When individual carriers begin to evolve in newer products or processes to offer coverage with the help of new tools and data, the explainability and training of agents needed to keep the distribution process up to date grows more complex. Rolling out a newer process without engaging and co-developing with the rest of the value chain can cause roadblocks to successful adoption.

In our industry trust and relationships are invaluable. The back-office support BGAs provide to insurance agents has consistently been backed by data and technology. Active agent awareness and upskilling tools are needed to create transparency around the data and processes. This contributes to an increase of take-up rates. When agents can track application processes and provide better estimates around turnaround times, it helps them improve trust with customers and drive cross sell opportunities.

Underwriting teams are also undergoing a change management and training exercise as alternative data is used for assessment of risk in underwriting and the level of experience of underwriters varies across the industry. The clinical data also presents some unique aspects to learn, trust and build upon compared to the traditional narrative of a case, upon which underwriters have notoriously relied.

As efficiencies in the utilization of underwriting time improves, the use of newer data sources also provides innovation towards new distribution opportunities to reach more uninsured and underserved pools of risk.

Launchpad For Success And Differentiation

We are in a decade where the life insurance industry is adopting new data and technology at a fast pace. The modern consumer is surrounded by digital channels to access products, conversational AI, fitness apps and wearables, which all have had a hand in shaping the consumer mindset to be more willing to share data if there is a value proposition to improve their overall experience.

Successful innovations are embedded and connected within the insurance ethos bringing higher transparency into the applicant journey for the agents, seamless experience for the end customer and more efficient underwriting. What we build today, we need to be able to sustain and upgrade for the next 30 years. An impactful innovation team is integrated and cross functional. IMOs can improve customer targeting with the help of enhanced digital data and improve BGA relationships by delivering the right product fit for the right customer.