Adoption of Automated Sales & Underwriting Strategies can Transform Insurance
The insurance industry—which, in the US alone, stands at $1.2 trillion, is seeing the volume of insurance transactions growing every year. The unprecedented circumstances surrounding pandemic have increased awareness around insurable risks across different financial losses that can be covered as everyone in the world have faced financial losses like unemployment, travel cancellation, health issues, business interruptions, etc.
Many of the underlying processes have been witnessing many changes due to the adoption of digital and intelligent automation across functions. The onset of COVID-19 globally has only hastened the process, Insurers can no longer choose between what processes take precedence or when to digitize. As face to face contact, operating offline offices, physical audits and ancillary processes face constraints; these increasingly move to the digital bandwagon. In days ahead, digital transformation will be the saviour and guide of the industry.
But in the crisis, itself lies an opportunity; insurers can use these constraints to devise solutions that can help tide over the crisis and build robust systems for better resilience and challenges of the future. Insurers can take benefit of the situation to accelerate their digital transformation journey and mitigate challenges to their business.
As a fallout of social distancing, much of the sales will have to take place via digital channels, backed by a robust automated underwriting process. To catch up, underwriting which typically involved manual involvement in garnering data from documents has to change radically. From product recommendations to underwriting, most of the processes are expected to move from traditional channels to digital. In this context, Sales & Underwriting automation working seamlessly through the workstream can cut the policy processing time to thrive in the digital space.
To get a perspective on evolving trends in insurance in the post-COVID world, read BRIDGEi2i’s blog here.
Challenges in underwriting
- Underwriting is a process that involves extraction & collation of information about the insured from different sources in structured & unstructured format
- Assessing risk is a manual process and takes a lot of time
- Sometimes due to excessive volume of data, an underwriter can get confused and is unable to measure risk appropriately
- The process is purely based on underwriter’s judgement, and there is no standard process followed
- Importance of capturing market data for optimized pricing models
Underwriting essentially means evaluating the risk proposition of an insurance cover and determining how much an insurer should charge for the same by studying historical data and statistical models. An underwriter typically navigates this process by drawing on their experience and information gathered from various unstructured sources. But the sheer volume of data might cloud manual judgments and here is where automation and digitization could help.
Increased Role of automation and AI in Sales & Underwriting
Insurers are leveraging the benefits of advanced data science skills at several stages of Sales & Underwriting in a digital environment. Right from customer inquiries to issue of policy and fulfilment, the entire lifecycle of Sales & Underwriting is today driven by AI systems.
Various stages in Sales & Underwriting:
- During the early stages of customer acquisition, digital assistants (chatbots, etc.) can help to inform and determine eligibility.
- They can recommend product based on client’s behaviour/questions asked on chatbot using collaborative filtering.
Some insurance products may do better with direct sales via digital sales channels. They are helping broker/agent enablement on the traditional channels with account/customer intelligence powered by digital tools, and better customer insights can be a game-changer.
- Application validation – Automated process to check the required documents availability. (if all the information is provided by client or not)
- Upfront decisioning – if insured can be given insurance or not
The automated process can then be used to parse data sources like structured and unstructured data sources such as – IoT data, claims data, physical proofs, social data, life health data and in a variety of formats such as textual, visual, sensor-based and electronic etc. It’s then possible to arrive at actionable insights without human intervention. The more data an underwriter has at his disposal, the more accurately he will be able to assess risk.
- At the final stages of pricing optimization and quote generation, automation can recommend rates along with application & risk summary. It can also offer cross-sell and upsell opportunities via additional product/cover recommendations as per the client profile.
A digital transformation of underwriting with automation can make it easier to navigate the complexity of data with the help of AI-powered technologies like machine-learning (ML), deep learning (DL), OCR, CV and NLP, etc to estimate the risk impact.
The way ahead for insurers
- Underwriters to spend more time in risk evaluation instead of capturing data from unstructured docs like tax, medical etc.
- Start capturing the new type of data like Twitter feed for a company to assess its market position and reputation.
- Product recommendation based on insurers needs/usage.
BRIDGEi2i’s insurance solutions
BRIDGEi2i’s Insurance Solutions leverage sophisticated AI & machine learning capabilities and domain contextualization to deploy accelerators that help in various stages of automation of the Sales & Underwriting process. We have a skilled team of data scientists and domain experts who have an in-depth understanding of this space to help you in digital transformation.
“By embracing automation powered by AI-led technologies, we can analyze risk better and recommend appropriate covers at scale, in the shortest possible time,” said Anirban Chaudhury, VP, Insurance at BRIDGEi2i. “Automation has been a blessing in disguise for insurers to delegate high-volume, low face value, simple-risk policies, and shift their attention to more high-value and profitable opportunities in insurance.”