Top 7 Reasons to Transform Insurance Underwriting with AI | Saxon AI
AI and ML / July, 25 2023

Top 7 Reasons to Transform Insurance Underwriting with AI

According to a research report by Accenture, insurance underwriters spend 40% of their time on non-core activities. The efficiency loss due to this is estimated at a whopping $85-$160 billion over the next five years. At the same time, AI has attained a level of robustness and effectiveness that is different from 5 years ago. The economics have brightened significantly, indicating a higher ROI on leveraging AI, especially in insurance and underwriting.

Why the time to reap AI in insurance is now?

The insurance industry stands at the cusp of this major transformation era, where the adoption of advanced technology in the insurance industry can make or break a company. Let’s take the example of agile Insurtech companies. Today’s customers are used to being on their mobile phones and getting things done with merely a few taps on their smartphones. Insurtechs provide customers with just that- a highly streamlined user experience, unmatched personalization, smooth accessibility, no paperwork, and hassle-free services. But behind this hassle-free experience, an enormous amount of work happens in the background. That work tackles security, ensures compliance, verifies data, accesses real-time data, analyzes and provides customized premiums, and more. All this heavy-lifting work is done by Artificial intelligence and Machine learning technologies, not by manually processing humans. As a result, insurers are giving tough competition to traditional insurance companies, and why not?  

Leveraging Artificial Intelligence and all the related tech, Insurtechs have seen a CAGR of 20% in the past few years. However, in the Accenture survey, only half of the insurers admitted to adopting AI or cognitive intelligence in their enterprises. It all boils down to the fact that the window is open now for insurance companies to leverage AI and have a competitive edge over others. 

Insurance Underwriting 

As per a McKinsey report, manual underwriting will become obsolete by 2030 for the majority of personal and small-business insurance products, encompassing life, property, and casual insurance. The advances in cognitive technologies involving machine learning, deep learning, and big data gathered from IoT would make the insurance underwriting process supersonic fast within a minute. It will become the standard approach for processing insurance products via substantially large and connected data streams. Let us consider one aspect of insurance where AI can play an influential role: the insurance underwriting process. 

What are the challenges in manual underwriting? 

Manual underwriting has several flaws, which result in low customer experience, high customer churn, low underwriting efficiency, inefficient risk management, and pricing. Furthermore, in this era of AI, consumers expect 24/7 access, swift delivery, clear information, and more. Insurance companies can level up their game with automated insurance underwriting, which has data-driven risk management and predictive analytics as well. Let us look at the challenges posed by manual underwriting: 

  1. It is a lengthy and cumbersome process. Compared with AI in commercial underwriting, speed and accuracy are not reliable enough. It is error-prone and not a speedy process.  
  1. Complexity is high in manual underwriting. Processing perplexing fine print, errors and omissions in underwriting, long turnaround times, and higher premiums all add up to the unwelcome complexity. Furthermore, there is little product personalization and predictive analytics assistance. 
  1. Lower Efficiency: Do you think assessing the risk variables which come with every new application is easily done manually? It is, in fact, very complex to assess precisely in the manual approach. It is among the most resource-intensive insurance processes that impact productivity negatively. 
  1. Inefficient pricing: Manual underwriting gives way to price inefficiencies, quality issues, and potential procedural errors in risk assessment.  

All these challenges showcase how manual underwriting is a complex, lengthy, and difficult task. Artificial intelligence can overcome these difficulties in several ways. 

What are the top benefits of leveraging AI in Insurance Underwriting?  

AI benefits in underwriting

Minimizing the possibilities of human error

You must have heard the phrase: ‘to err is human.’ So, no matter how intelligent, logical, and sharp humans are, errors are always likely. However, AI and machine learning do not make mistakes, no matter how reductant and routine the work is or how many figures it deals with. Thus, underwriting using AI is of critical importance. AI in insurance underwriting can synthesize large datasets in different formats and thus reduce the probability of errors. 

Rather than manually underwriting, the human underwriter can become the human-in-the-loop (HITL) in the automated underwriting process. They can analyze the outcomes by applying the predetermined identification and models and make an informed decision based on the data. AI is algorithmically self-reliant, and machine learning allows it to learn from past errors. Hence insurance underwriting with AI is faster, scalable, and very much effective. 

Enhanced understanding of risk

The best practices for insurance underwriting require a large variety of data sources. In this case, using AI in underwriting can expand access to various data sources and augment them, optimizing risk evaluations. Insurance businesses have already seen benefits from implementing AI in their departments, such as introducing big data, machine learning, and predictive analytics models and algorithms. By using these solutions, they minimize the time-consuming due diligence processes. 

Combating cyber threats 

There is an increased number of cyber threats to enterprises. Keeping up with them is an endless struggle for insurers. However, machine learning-based fraud detection systems can keep up with these new threats. AI-assisted underwriting brings improved security and cutting-edge insurance coverage features. 

Tackling customer churn and boosting the customer experience 

Having AI in underwriting can help insurance companies to enhance the customer experience even during the sales process. That would nurture customer loyalty right from the very start. Insurers can create a long-term retention roadmap involving tailored individual account service, appealing pricing structures based on risk-sharing, and practical loss control strategies.  

Moreover, AI frees up the underwriters’ time, allowing them to interact with complex customers. Underwriters can now focus on working with more intricate customers.  

Leading commercial insurance companies are already improving the capabilities of their underwriters with Artificial Intelligence so they can do more high-value tasks. They are also integrating AI-based cognitive technologies to speed up the underwriting process and post-sales services.  

Opportunities to acquire new businesses 

AI in underwriting integrates into bigger insurance value chains. As a result, there is enhanced cross-platform visibility and new cross-sell possibilities based on the insights from centralized data lakes. Insurers are better equipped to bring about a positive customer experience. 

Underwriters can reach out to clients with a personalized plan before filing an application, thanks to integrated AI-enabled technologies. For example, by tracking customer inquiries to the NLP-powered chatbot, underwriters can get a comprehensive picture of the customer’s journey. This allows underwriters to consider a variety of consumer issues. 

Apt and fair pricing 

According to a case study by McKinsey, a small business owner seeking commercial property and casualty insurance obtained coverage amounts from five different carriers. Surprisingly the coverage amounts differed by 233% for almost the same risk. Several businesses, such as AIG, lose $75 million daily due to losses from the commercial line alone. This situation demonstrates the price inefficiencies affecting the commercial insurance industry. Losses occur when the insurer is not able to capture the risk profile adequately.  

In these circumstances, automated underwriting offers superior risk visibility. The underwriters suggest the finest pricing options and coverage terms, as they act as qualified gatekeepers in charge of making course corrections. 

Higher Profitability 

AI-powered insurance underwriting increases profitability by supporting underwriters in generating lower loss ratios, higher converting quotes, and optimal resource utilization, ultimately maximizing overall underwriting efficiency. So, leveraging automated insurance is a sure-shot method to have highly impactful reforms to be profitable.  

A plan for AI-powered underwriting transformation can help businesses cut costs and improve employee satisfaction. In such an insurance enterprise, the underwriters’ role enhances as they share their valuable expertise in business development and add value.  

Key takeaway 

AI in insurance underwriting is definitely here to stay. However, we must keep the following ideologies in mind when moving forward. Firstly, enterprises that create tech products must ensure that the products are tailored to the real-world needs of insurers. Secondly, the tech should accommodate present underwriters with apt training demonstrating how AI-driven tech helps them perform underwriting much more efficiently. It is more of an AI and human underwriters’ collaboration where they automate tedious tasks, meanwhile, incorporate complex data models and predictive analytics.  

If you are looking for insurance underwriting solutions, check out Saxon AI, where we create AI-enabled automation services called digital co-workers, especially for your use case. Our digital co-worker Adeline is an insurance underwriter who can help you achieve extraordinary results while reducing 70% of manual work for the underwriters.  

You can talk to our team to find out more about our solutions, especially our digital co-workers. 

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