May 6, 2022

How to lay the groundwork for digital transformation innovation in commercial underwriting

The following blog sheds light on the recent webinar that covers the topic of ‘Digital transformation in the field of commercial underwriting’ by Insurance Thought Leadership( ITL) and Intellect SEEC.

Insurance Thought Leadership (ITL) delivers engaging, informative content from their global network of thought leaders and decision-makers. ITL strives to empower content consumers with the insights needed to be knowledgeable about the drivers transforming the insurance industry.

Intellect SEEC is a ‘solution partner’ to commercial insurers that leverages artificial intelligence (AI), machine learning (ML), NLP and big data to deliver end-to-end commercial underwriting solutions.

The webinar featured eminent speakers including Paul Carroll, the Editor-In-Chief for ITL and Sandeep Tandon, CTO for Intellect SEEC.

Commercial Underwriting Decoded

“There has been a lot of talk about innovation in the insurance industry, but it is not a matter of waving a magic wand, there are preparatory things that one has to do with the core system so that they can actually function,”

– Paul Carroll 

Big data analysis is performed by businesses of all sizes today to guide their choices, particularly those involving financial risk.

Trends that contribute to digital underwriting

“There are a lot of new technologies out there that offer opportunities to innovate, get creative, take costs out and move the market faster.” – Jim McKenney

Initially, insurers’ priority for adopting technology was tactical and practical in the immediate aftermath of the pandemic’s outbreak. The top priorities were technical difficulties affecting the customer experience and staff productivity, followed by procedures and activities that historically depended on physical aspects (e.g., printing and mailing physical documents).

On a strategic level, planning for purpose-designed underwriting workbenches was advanced since they provide an efficient and intuitive underwriting experience by integrating and combining the data sources, tools, and procedures required for the task. 

By automating low-value activities, connecting third-party data sources, and applying underwriting rules to deliver actionable insights, underwriting workbenches and collaboration tools also provide a strong platform for improving long-term performance.

Insurers are looking at risk intake and triage as crucial tech-enabled skills, recognizing that giving data to underwriters in digital form, including third-party data, is critical to enhancing performance and producing returns on tech investments. 

Smarter processes based on document intelligence platforms that employ artificial intelligence (AI) to scan documents and extract important data will be an additional vital component of high-performing underwriting teams.

When underwriters have collaborative access to quality data, they do more complex analytics and gain high-value risk insights. Furthermore, by digitising intake operations, underwriters will be able to spend more time studying data insights rather than obtaining, validating, routing and modifying it.

As a result, digitalization and modernization lay the groundwork for insurers to increase automation, decision-making, data collecting, and analytics.

Benefits of automating commercial underwriting

  • Faster turnaround time
  • More engaged employees
  • More focus on new lines of business
  • Personal information is more easily accessible
  • Improved efficiency
  • Highly scalable

“To modernize it is integral that we identify horizontal technical services that can be decoupled to lay the groundwork” – Sandeep Tandon

“We need a framework to deliver complete APIs through API gateway to the customers in a scalable way”– Sandeep Tandon

“These frameworks definitely allow our clients to have very small hyper focused teams which are rapidly innovating on very defined units of business value and working together to deliver a complete larger application, we call this composable architecture.” – Sandeep Tandon

Manual Vs Digital Underwriting in the insurance industry


Manual Underwriting

  • Takes much longer to complete, and risks of human errors remain as it depends on a person to assess a client’s financial history.
  • Long-drawn manual form-fills, lengthy turnaround time, errors, higher premiums, lack of product personalization
  • Inefficient pricing, quality issues, and probable procedural errors
  • Takes weeks to receive a quote post-application making it one of the most time and resource-intensive processes in the insurance customer life cycle
  • Scaling up with manual Underwriting comes at high fixed costs in addition to increased operational overheads

Digital Underwriting

  • Works quickly with advanced algorithms and software to analyze a client’s background.
  • Better customer experience with personalized solutions. It automates low-complexity tasks and frees up underwriters for more complex interactions with the customer
  • Automation in Underwriting brings complete risk visibility and helps in suggesting the best possible quotes and coverage to the underwriters
  • Possible to achieve quotes in matter of seconds without investing manual efforts
  • Significant savings can be achieved by going down the digital underwriting road


Benefits of applying data science in commercial underwriting

Commercial underwriting is being transformed by data science, which is replacing human-powered aspects of the process with more objective data and computers. This shift is most noticeable in the following ways:

Getting rid of paperwork:

The irritating fact of typical underwriting work is that a large portion of it is data administration – shifting data from one form or source to another. When underwriters have access to data-science-powered underwriting workstations, their productivity increases.

Today’s products and services will accelerate underwriting by automating information capture from forms and reports, enabling access to data from thousands of sources, and combining it “intelligently” with the use of machine learning.

Smarter risk-management:

Data science may also “intelligently” compile data from hundreds of sources for underwriting analysis, allowing for improved risk analysis. Better risk analysis is the consequence of all that data being gathered by sophisticated algorithms. Increased data combined with a less human bias means fact-based risk analysis.

Boosting processing efficiency:

Naturally, underwriters can service more accounts if they spend less time on each account. Insurance companies are witnessing a 50% reduction in submission response times and a 40% rise in policy numbers.

“There are 3 modernization and transformation journeys that we can focus on, firstly it is about application architecture, secondly it is about Dev Ops automation to deliver high quality code to production and finally, there are various cloud platforms, so we should have a mechanism that this code base that we are developing can be wedded to one single cloud and can be deployed on any cloud infrastructure.”

Business is evolving, and the insurance business is adapting. Traditional underwriting lacks many of the elements that an insurer needs to accurately assess an applicant’s risk and provide them with the coverage they seek.

Furthermore, digital underwriting enables agencies and brokers to develop and scale in ways that conventional underwriting does not. Insurers may incorporate new systems, technologies, and tools by partnering with insurtech and analytics organisations rather than incurring the expense and risk of development.

Adopting digital underwriting propels the commercial insurance sector into the digital era by simplifying the underwriting  process and lowers  the cost and time investment in inefficient and repetitive tasks.

To learn more about digital transformation for commercial insurance companies – CLICK HERE

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