The Top Insurance Technology Trends for 2023 (part 2)

Insurers today are faced with a choice: innovate quickly, or lose market share to competitors and emerging insurtechs.

13. Low-code / No-code Insurance Technology Platforms

Indeed, only?15% of customers are satisfied ?with their insurer’s digital experience and?41% of customers ?say they are likely to switch providers due to a lack of digital capabilities.

Traditionally, digital transformation relied on expensive IT talent to both implement and manage various digital channels. With the growth of low-code and no-code platforms, however, insurers can deploy digital applications more quickly with little or no computer programming.

Low-code/no-code software can reduce application deployment time for insurance technology from several months to a few hours.

In 2023, this will be more pertinent than ever.?2021 research from Appian ?shows IT departments across industries are losing control over their growing digital infrastructure and project backlogs are outpacing the addition of new IT resources. Low-code/no-code platforms are not meant to replace IT departments. Rather, they give IT breathing room to deploy their technical resources more strategically.

This does not mean business units should deploy software solutions independently of IT. Low-code and no-code platforms may run the risk of encouraging “shadow IT” environments – that is, IT projects managed outside of the IT department.

This could result in security and workflow issues, inconsistencies in business logic, and other unforeseen problems. Low-code/no-code solutions should be implemented following software development lifecycle and architectural best practices in collaboration with IT.

Gartner estimates that low-code platforms will make up?65% of application development activity ?by 2024.

14. Predictive Analytics for Competitive Benchmarking and Modeling

Benchmarking has always been critical to quoting insurance policies but is only as good as the data available. In 2023, insurers and distribution partners will be able to do much more with their data using predictive analytics.

Predictive analytics works by taking historical data and feeding it into models that are trained over time (machine learning), generating predictions about trends and behavior patterns. This enables insurance companies to make informed decisions about quoting, workload optimization, product recommendations, and more.

According to?recent data from Willis Towers Watson , 60% of insurers reported an increase in sales due to predictive analytics and 67% reported a reduction in expenses.

This is especially important in employee benefits sales and underwriting.

During quoting, insurers can leverage machine learning algorithms to process historical or synthetic data to identify the most successful sold plan designs for particular group sizes and industries, speeding up the sale of a new plan. Using?artificial intelligence to generate a recommended alternative quote ?provides a valuable benchmark based on reliable data and reduces the guesswork.

15. Expansion of Accelerated Underwriting Programs with Insurance Technology

In traditional insurance underwriting, it was common for customers to take in-person evaluations. However, since the COVID-19 pandemic, this was no longer possible, and many insurers had to embrace accelerated underwriting, supported by digital self-service tools and insurance technology.

In its simplest terms, accelerated underwriting means that some lower-risk applicants can accelerate through the underwriting process without taking traditional tests requiring body fluid (blood, urine, etc.). In addition, because these applicants are at lower risk, they usually do not have severe health conditions that would require an insurer to seek additional requirements.

A survey by LIMRA found?53% of consumers ?are more likely to buy life insurance with simplified underwriting.

The availability of big data, growing population statistics, and limited face-to-face interactions have helped accelerated underwriting programs become most prolific in the?life insurance ?industry.?

Munich Re’s 2021 survey says that?67% of life insurance companies ?now offer the same standard and preferred risk classes as their traditionally underwritten products, up 17% from 2018. These classes allow life insurance carriers to provide coverage to a larger audience.

For example, 83% of accelerated underwriting programs now allow tobacco users to participate in their accelerated underwriting programs, a 16% increase from 2018.

Additionally, predictive analytics and machine learning algorithms in underwriting programs make it easier and faster for customers to obtain life insurance coverage by skipping traditional tedious underwriting processes.

16. Open APIs Enable Growth of Insurance Technology

A report by Accenture says?82% of insurance executives ?agree that open ecosystems allow them to grow in ways that are not otherwise possible, and 58% are actively seeking ecosystems and new business models.

Open?APIs ?(Application Programming Interfaces) are publicly available application programming interfaces that give other developers access to a software application or web service. They also manage how applications can communicate and interact with each other.?

Unlike an open API, A private API is an application programming interface hosted by its own in-house developers. They are mainly used for back-end data and application functions.

Open APIs allow insurance companies to showcase their services to the outside world so external partners can use them and bring added value to their customers.

Companies interconnected through APIs can create an insurance technology ecosystem to offer a best-of-breed customer experience by intertwining digital services provided by multiple companies.

Joris Lochy, a co-founder of Capilever, says providing?open APIs ?to different industry applications can help insurers acquire new customers.

For example, a car dealer that uses open APIs in their applications could partner with an auto insurer to help sell car insurance right through the car dealers app. This would make it easier for customers to buy a car and insurance simultaneously.

17. Insurance Technology for Proactive Risk Management

With?52% of organizations ?agreeing that proactive risk mitigation is as significant as an effective risk response, insurance companies are tasked to find new ways to prevent and mitigate risks for their clients.

Life and health insurance companies are increasing their use of?AI and other predictive analytics to develop more preventative risk measures for their clients.

For example, big data offers revolutionary insight into a customer’s lifestyle, diet, and general health. Its access enables insurers to better understand potential risk factors and even offer preventive and proactive recommendations such as encouraging healthy habits to avoid future health issues. Potentially, an insurer could recommend the insured go to an emergency room because of the acute risk of a heart attack.

Additionally, big data collected from wearable devices can provide critical health and fitness information for life and health insurers. This information is crucial to developing interactive life insurance policies that track fitness and health data wearable devices and smartphones.

18. Embedded Insurance

Insurance should be uncomplicated.

Embedded insurance will become a significant new form of digital distribution in 2023, as the embedded insurance market is projected to reach?$3 Trillion by 2023, and ?Denise Garth of Majesco says?40% of insurance will be embedded ?in the next 10 to 20 years.

Even major non-insurance companies, such as?Amazon , are beginning to offer embedded insurance.

InsTech London defines embedded insurance as;

“Abstracting insurance functionality into technology in a way that enables any third-party distributor (usually a product or service providers in other sectors) to seamlessly integrate insurance products and solutions into their own customer propositions and journeys.”

For banks, car manufacturers, and other distributors, implementing embedded insurance as part of a sale can help increase revenue and improve the overall value of their products or services. This is a win-win for both insurers and distributors as insurers can save money on distribution costs by implementing their products directly into the distributor’s platform.

Embedded insurance technology can also help make insurance easier to understand because, with a few clicks, a customer can get coverage. No complicated process – they can get the right policy they need from day one.

19. Machine Vision in Insurance

Machine vision offers a great opportunity for insurers to automate visual tasks and mitigate fraud.

Machine vision refers to the AI-based analysis (machine learning) of images from sources such as smartphones, satellites, or drones. In simple terms, machine vision is the eyes of applications and machines. It uses software algorithms to assess visual images based on existing data sets already assessed by humans.

According to Insurance CIO Outlook, machine vision can help property and casualty insurers?simplify property assessment ?for claims processing. Traditionally, a claim adjuster would go on-site and assess the situation. By using drones programmed with machine vision, this process becomes more simple and safer, as the drone can use machine vision to obtain images and create 2D and 3D models for claims assessments.

In employee benefits,?machine vision can greatly streamline the quoting process . Many requests for proposal still come in as images and PDF documents that cannot be interpreted as text by a typical computer. Moreover, client information cannot be copied and pasted from this format into the quoting tool, requiring manual rekeying of information by a human underwriter or salesperson whose time is better spent elsewhere.

This is where a machine vision technique called optical character recognition (OCR) comes in. OCR is the conversion of images to text (e.g. a photo of an RFP) into a machine-readable format. This enables insurers and distribution partners to generate a shell quote with information pulled from the RFP and begin working on a quote immediately.

Machine vision can also be used to improve the speed and accuracy of?damage assessment and claims evaluation. For example, when a customer damages their vehicle, they can simply send a picture of the damaged area to their auto insurer, and the AI’s machine vision will analyze the images to determine the damage and claim amounts.

It can also help reduce fraud in claims assessment. Fraudsters usually think low-value damages go under the radar and are not assessed as thoroughly as higher-value claims. The neural networks can identify and filter out patterns of fraud cases or suspicious damage reports.

Additionally, machine vision also improves underwriting. It does this by intaking data from satellite images to find attributes insurers might find value in. Based on its findings, risk can be assessed leading to cost reduction for policyholders, higher quality of care, and improved fraud detection.

20. Health Wearables

The demand for health wearables is booming as advanced insurance technology allows people to monitor their health progress and get rewards for healthy living.

These services track a wealth of data, such as daily steps, sleeping patterns, activity levels, heart rates, calories consumed, UV levels, temperature preferences, when people are home and not, distance traveled in cars, etc.

A report by CCS Insights finds that shipments of wrist-worn wearables will hit?232 million units in 2021 , a growth of 20% from an already solid 2020. Of sales in 2021, 142 million units will be smartwatches and 90 million will be simpler fitness trackers. Additionally, wearables growth to continue over the next few years and shipments to reach almost 380 million devices in 2025.

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Indeed,?95% of underwriters ?want to improve the quality and accuracy of data around underwriting submissions.

Data collected from wearables can provide critical health and fitness information. This information is vital to developing interactive life insurance policies that track fitness and health data through wearable devices and smartphones. In addition, the data gathered can give complimentary coverage or improved rates for both individuals and employee benefits using health and risk scores.?

Wearables can also help insurers mitigate claims fraud and, more importantly, enable them to transmit data to warn customers of possible dangers in real-time. For instance, some IoT wearables can proactively alert people with diabetes on possible odd joint angles, foot ulcers, and excessive pressure so they can get treatment before things get worse.

Life insurance policyholders pay their premiums on average for 20 years. However, with the adoption and use of fitness trackers, they may be able to live healthier and longer lives. Lower mortality and morbidity can help insurers boost profits while improving insured health and wellness with predictive care and early diagnosis.

21. Automated Renewal

Automated renewal provides insurers with an opportunity to help existing clients renew their policies faster than ever before.

A study by Deloitte finds?69% of insurance leaders ?expect to spend more on processing and data acquisition in 2022, while 65% expect to spend more on robotic process automation this upcoming year.

Automated renewal applications can limit the need for carrier intervention for stock quotes, automatically queuing quotes for manual review, and auto-generating policy renewal packages.

Additionally, automated renewal applications can connect with policy administration and claims systems by leveraging data for re-calculations at the anniversary of a policy’s renewal. This allows insurers to not worry about tracking renewals and the manual preparation of renewal quotes and letters.?

This has proven to be especially beneficial for employee benefits insurers as they can reduce renewal turnaround and touchpoints by?75% with automated renewal .

22. Automated Workload Balancing for Quotes

During high-load periods like open enrollment for employee benefits, the high volume of quotes requiring underwriter review can slow down processes due to an inefficient allocation of human resources. In fact,?30-40% of an underwriter’s time ?is spent on administrative tasks, such as rekeying data or manually executing analyses.

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With AI,?workload recommendations can now be generated automatically . Carriers can train machine-learning models to assist sales and underwriting managers in suggesting the most effective distribution of quotes across the underwriting team.

AI can take an individual underwriter’s current capacity and performance history into account when making recommendations. Additionally – and this is really cool – it can be used to prioritize quotes with the highest chance of closing based on past successes.

Identifying these resource efficiencies with AI is essential to improving sales and underwriting productivity. In fact,?49% of insurance executives say AI ?has helped them operate more efficiently, and 35% say it has helped them increase revenues.

23. Omnichannel Customer Experiences

53% of insurance customers ?aged 18–24 use digital channels to interact with insurers. However, 15% say lack of digital capabilities is the topmost challenge while interacting with insurers.

In 2023, each insurance interaction should be part of a unified omnichannel experience.

An omnichannel customer experience occurs when multiple marketing and service channels work independently to strengthen the customer experience. As these channels interact and work together, multichannel becomes omnichannel. Omnichannel enables seamless interactions with consumers through all online and offline channels. This includes every touchpoint in the customer lifecycle, such as websites, social media, live chats, phone calls, and in-person assistance.

Insurers can enable omnichannel customer experiences by:

●??????Assisting customers across their preferred online channels.

●??????Connecting offline and online experiences.

●??????Tracing customer activity across different channels.

●??????Enabling progressive autofill forms to limit repetitive form filling for other devices or platforms.

●??????Using customer data to target specific individuals with personalized products and campaigns.

By building omnichannel insurance ecosystems for marketing, sales, and customer service, carriers can assist prospects and customers at every stage of their buying journey and win customer loyalty.

24. Digital Twins

Digital twins are a computer program that uses real-time data to enable computerized representations of virtual simulations that can predict how a process, service, or situation will perform. For example, a digital twin can create a digital replica of people, houses, cars, entire cities, business operations, and healthcare procedures, to name a few.

Such programs often integrate big data from the internet of things, artificial intelligence, and software analytics to enhance the output.

As a result, digital twins are becoming a staple in the P&C and auto insurance industries to derive virtual data and evaluate and predict risk scenarios before they happen. In fact, most insurance companies are missing out on anywhere between?35% to 65% in value ?by not realizing the full potential of digital twin investments.

Digital twins can help insurers expand their datasets for everyday risks such as car accidents, heart attacks, and catastrophic event damages before they happen. As a result, digital twins can improve risk assessment and underwriting accuracy.

For example, P&C insurers could create a digital twin of a prospect’s home and enable simulations to see how different categories of hurricanes would affect it. Then, based on the simulations, the insurers could identify and evaluate risks for potential losses before they happen, therefore enabling them to price premiums more accurately.

In addition, digital twin technology can create a replica of an insurance company’s organization by simulating an insurer’s firm’s activities and day-to-day tasks. This can help insurers evaluate their operations and provide insights into which processes they can automate or be more efficient in.

25. E Signatures

Insurance transactions need many signatures for legal, compliance, and security purposes. But as the world becomes increasingly remote, it doesn’t make sense for consumers or agents to deal with paper-based signatures.

Many carriers and businesses from other industries are investing in eSignature solutions to streamline customer experiences and eliminate overhead expenses like physical paperwork. In fact, the global eSignature market is projected to reach?$9 billion by 2023.

By using electronic signatures, whatever needs to be signed within insurance processes can automatically be done whenever and wherever. eSignatures can also make it easier for customers to navigate processes with convenient reminders and simple actions.

This can be especially helpful in improving customer experiences and claims processes for health insurers. For instance, a plan member may be at the hospital getting treatment, and right from their hospital bed, they can process their claim through an e-signature on their phone instead of waiting to get home for files to be sent to them.

Furthermore, eSignature technology increases mobility and speeds up the entire movement of the insurance process. In this day and age, where everything seems to be very fast-paced, this is truly an advantage, given how it makes operations more efficient.

Final Thoughts – The Road Ahead

Of course, emerging trends and technologies only have as much value as the core systems that support them. Insurers also need modern, cloud-based systems for?underwriting, rating, and processing new and renewal business ?before investing heavily in various insurtech trends.

Without state-of-the-art internal systems covering major functions, the competitive edge provided by AI, predictive analytics, chatbots, drones, blockchain, and IoT will be blunted.

All the best in 2023!