Insurance Technology: 22 Trends for 2022

Uncovering the insurance technology trends shaping our industry in 2022.

The Automated Insurer | Digital Transformation

By Mike de Waal | 1 January 2022

Key Points

In this article, our team covers 22 of the most important insurance technology trends we expect to shape the industry in 2022.

One keyword in 2022 will be “digital ecosystems”, a technology strategy that emphasizes best-of-breed components covering each major function in insurance using APIs, microservices, and, web services.

2022 will likely see new applications of artificial intelligence in insurance, as well as emerging but still nascent technologies like blockchain.

As we all remember, 2020 was marked by a drastic redirection of insurance industry resources in response to the COVID-19 pandemic. Then came 2021, when insurers focused on pandemic recovery and meeting customer expectations for digitization and personalization. 2022 will take the industry even further with an emphasis on hyper-personalization and data-driven ecosystems.

While adapting to the latest insurance technologies was a challenging experience for many carriers, those who did are selling more benefits faster and smarter than ever before.

From underwriting and claims to the customer journey and distribution methods, here are the top insurance technology trends our team believes will be beneficial to carriers in 2022. 

Contents

1. Automated Underwriting

It was once common for insureds to undergo in-person evaluations in traditional underwriting. However, this proved a challenge during the pandemic, and many insurers had to embrace new underwriting methods.

The goal of automated underwriting is to streamline information-gathering and reduce as many human touchpoints as possible. Automated underwriting uses tools and techniques like robotic process automation and artificial intelligence to import and correct data, assess risk and determine how much coverage a client should get and how much they should pay in premiums. 

It is important that automated underwriting programs incorporate an insurer’s business rules, halting the process when human intervention is required. To this end, automated underwriting technology should enable granular configuration of roles and permissions. 

The benefits of saving time and money have led to many insurers implementing automated underwriting into their value chain. 

A report by LIMRA says more than a quarter of U.S. life insurers have expanded their automated underwriting practices.

Global IQX’s Underwriting Workbench uses robotic process automation and AI to enable automated underwriting for group and voluntary benefits providers.

Infographic showing statistics on insurance automation technology. 25% of insurers have expanded their automated underwriting practices (LIMRA, 2020). 50% of claims activities have already been replaced by automation (McKinsey, 2021). 65% of insurance leaders expect to spend more on robotic process automation in 2022 (Deloitte, 2021).

2. Automated Claims

The increased use of AI and digitized claims have allowed carriers to streamline disjointed claims management practices, resulting in faster processing and reduced claim wait times. More than half of claims activities have already been replaced with automation. 

In fact, fully digital claims have reduced the average payment time by up to 5.5 days and assisted in achieving the highest satisfaction scores ever measured by The J.D. Power U.S. Property Claims Satisfaction Study. 

Jeff Wargin, Chief Product Officer of Duck Creek, explains more about the value of machine learning in claims processing

Machine learning cannot only improve claims processing – it can automate it. For example, when files are digital and accessible via the cloud, they can be analyzed using pre-programmed algorithms, improving processing speed and accuracy. This automated review can impact more than just claims – it can also be used for policy administration and risk assessment.

Additionally, automating claims can help insurers sell more products to customers. 

For example, say you are creating micro-insurance for farmers. Based on the analysis, you could use data analytics to determine if severe weather, low rainfall, or other factors could damage crops and pay claims. This can reduce settlement costs, enabling insurers to offer more competitive policies. 

3. Customers Seeking More Touchpoints

Many consumers are skeptical of the increased use of technology and automation in the insurance industry. A study by Accenture finds only 12% of insurance consumers trust an automated phone/web service when making a claim, while 49% trust a human advisor when making a claim.

Insurance companies also see customer trust as a critical impediment to business growth today. A report by the PwC found 70% of insurance CEOs believe it’s harder to sustain customer trust in a digital world, and 74% see lack of trust in the insurance industry as a threat to business growth. 

As insurers increase their use of technology and gather more data from consumers, carriers must provide more points of contact to customers to ensure trust throughout their value chain.  

A study by Deloitte finds 57% of insurance customers worldwide prefer to hear from their providers at least twice a year. Yet, only 47% receive contact from their carriers semi-annually. 

For example, an insurer could increase contact points by sending out a quarterly or semi-annual newsletter that informs clients about their latest product offerings and company updates. The newsletters should also highlight that their customer service teams are available to answer any questions they may have. 

Infographic showing insurance technology customer stats for 2022. 15% are satisfied with their insurer's digital experience (Accenture, 2020). 41% are likely to switch providers due to a lack of digital capabilities (PwC, 2020). 57% would prefer to hear from their providers at least twice a year (Deloitte, 2021).

4. Virtual Assistants (Chatbots) and Natural Language Processing (NLP)

Insurers can drastically reduce costs and turn-around time by adopting high-quality digital assistants. According to a study by Juniper, using conversational AI-based chatbots for insurance will lead to cost savings of about $1.3 billion by 2023 across life, property, and health insurance.

A report by Mantra Labs finds 64% of insurers plan to let chatbots handle more advanced customer-facing roles in the next five years, while a Novarica study says 18% of property and life insurers have already used chatbots in their operations in the last five years. 

While chatbots pose great opportunities, many consumers are skeptical about doing business with voice assistants. A study by the Capgemini Research Institute finds 45% of consumers do not believe a voice assistant can understand human reactions, and 46% do not trust voice assistants with the safety and security of their personal information. 

Additionally, consumers still want to communicate with humans. A survey by Userlike found that 60% of consumers would prefer to wait in a queue if it meant they could immediately speak with a human agent. 

A recent blog by Global IQX about chatbots explains more about the importance of balance when deploying this insurance techology; 

Customer experience is a broad discipline encompassing an ever-growing number of channels, both digital and non-digital. Striking a balance between approaches is key, and it will require some trial and error to determine when a chatbot should let a human take over to best meet your customer’s needs.

5. Machine Learning for Fraud Detection

Fraud is a significant concern for insurers as advances in technology allow new fraudulent behaviors to evolve. 

The FBI reports insurance fraud costs insurers $40 billion per year, and every five minutes a fraudulent insurance claim goes uncovered. 

Machine learning for fraud detection has become a valuable way for insurers to detect and prevent fraudulent claims. This has led to claims management and fraud prevention becoming the most prominent areas where machine learning can be helpful for insurers. 

Machine learning prevents fraud by using large data sets to produce predictions based on known outcomes. Although machine learning has helped insurers prevent fraud, there can be impediments to using this technology in insurance. 

A report by Management Events says machine learning can prevent fraud by: 

  • Processing data quickly. 
  • Indicating where connections exist where human eyes can’t. 
  • Applying data analysis applications that can discover new fraudulent strategies.  

A study by Wipro says despite its promise, there are some limitations of machine learning for reducing fraud.  These include not being able to understand unusual context-specific relations between variables related to sales processes, geography, and client segmentation. 

The main issue is there is not a one size fits all approach. Insurers will be challenged to create specific machine learning models based on context.

6. Drones and Robotic Insurance Technology

In 2022, we expect robotics and drone technology will play a more prominent role in many industries, especially in certain lines of insurance. 

The Federal Aviation Administration (FAA) study finds that 2.85 million drones could be in the sky by 2022, and 450,000 will be used commercially. The study also says in 2018, the insurance industry accounted for 17% of all drone applications in the United States. 

Today, many insurers are expanding the use of drones and robotics to offer better risk management and improve claims efficiency.

In commercial property insurance, drones gather data on buildings that would usually require a team of surveyors to review. 

For example, Deloitte says that Betterview, a property and casualty insurtech, used drones to provide more than 6,000 rooftop inspections in two years. 

More recently, Farmers Insurance partnered with Boston Dynamics to test Spot, the company’s notorious robotic dog. Spot is used to perform tasks and get into spaces that humans can’t fit into. For example, the robot can enter tight, dangerous areas and gather data through 360-degree cameras. 

7. Further Deployment of Cloud Computing

Cloud adoption among insurers is becoming more common as carriers seek to minimize costs, improve security, and support flexible digital ecosystems. In 2020, it was reported that 48% of insurers have cloud-native expertise, and Novarica says 75 percent of insurers plan to expand their use of cloud computing in the next year and a half. 

Cloud allows insurers to pull from data sets across systems, such as health scores, telematics data, and user data. Insurers can use these data sets to improve several aspects of their insurance technology organization, such as; 

  • Underwriting: improve accuracy when predicting risk
  • Claims: reduce fraud while processing legitimate claims faster
  • Marketing: boost customer satisfaction and personalize the experience.
  • Sales: generate qualified leads and identify coverage gaps and cross-sell opportunities.

An article by Global IQX explains more about the opportunity cloud presents to carriers;

Big data enables carriers to pinpoint customers’ needs. With thousands of data points available, the possibilities are nearly limitless. Cloud’s capacity and data processing power are indispensable in delivering meaningful, personalized experiences faster and cheaper. According to a 2020 AWS report, enterprises can expect a 27.4 percent average reduction in IT infrastructure spend per user, with a 37.1 percent reduction in time-to-market for new features.

Although cloud computing provides new ways to modernize businesses, only 40% say they get total value from their cloud investments. Accenture says this stems from security and compliance risks; “security is often seen as the biggest inhibitor to a cloud-first journey—but in reality, it can be its greatest accelerator.”

While teams that take care of your system updates also work around the clock to ensure their cloud platform is secure, this does not mean that the cloud is a silver bullet when it comes to security. 

Insurers preparing for cloud deployments must understand the importance of the shared responsibility model. While cloud infrastructure providers like Amazon, Microsoft, and Google are responsible for the security of the cloud (infrastructure level), SaaS providers and their customers are responsible for security in the cloud (application level). Therefore, cloud security best practices must be implemented and followed accordingly. 

8. Telematics for Usage-Based Insurance

With the usage-based insurance market projected to hit over $190 billion by 2026, telematics are allowing carriers to capture user data and create personalized usage-based insurance products. 

Today, consumers are more willing to share personal data for personalized insurance products and discounts. 

A study by Accenture found 7 out of 10 consumers would share essential data on their health, exercise, and driving habits in exchange for lower prices from their insurers, an increase of 19% from two years ago. The study also found 66% of consumers would also share important data for personalized services to prevent injury and loss—up 54% from two years ago.

Aside from providing usage-based insurance and personalized discounts, telematics can also assist auto carriers in saving money on fraudulent or inaccurate claims. 

An article by Bethan Mooncroft of Insurance Business Canada provides an example. The report says a driver was backing up out of a parking spot and then collided with another vehicle with four people in it. The four people claimed the impact led to them suffering neck injuries from whiplash, and a claim was filed accordingly. 

The auto insurers who received the claim reviewed the data captured from the black box telematics in the vehicle, and it indicated the car was moving at less than one mile per hour when the collision happened. Based on the data, it was impossible that the four people were injured from the accident, and thanks to telematics, the carrier saved close to $15,000 and prevented a fraudulent claim.

9. Smart Contracts: Blockchain Technology in Insurance

Smart contracts and blockchain are becoming more common in the insurance industry’s value chain. 

The recent Smart Contracts Market Research Report from Market Research Future indicates that the global smart contracts market will reach approximately $300 million by 2023. This is a CAGP of 32% from 2017-2023.  

Blockchain and smart contracts allow insurers to automate the execution of an insurance products agreement without any involvement from mediators. 

Traditionally, it can take months for uncontested claims to process. Ivan Kot, a senior manager at Itransition, provides four different ways how smart contracts and blockchain can be beneficial for insurers;

  1. Smart contracts eliminate human interference, lower the risk of manipulation, and allow more transparency. 
  2. It dramatically speeds up claim processing. 
  3. It lowers administrative costs for the insurer. Because of this, companies can lower premiums, increasing market share. 
  4. Both parties cannot lose agreement information. Smart contracts are trackable and irreversible. 

Many carriers have also seen their underwriting programs improve by enabling smart contracts and blockchain. Underwriting improves because insurers can review accurate information on past insurance policies and claims and offer more precise pricing and selections for their insurance products using this new insurance technology. 

While blockchain and smart contracts possess great opportunities for insurers, many are struggling to adapt. In fact, 53% of carriers struggle to understand blockchain and its use cases, 43% have other insurance technology taking priority, and 38% are concerned with its data security. 

Blockchain insurance technology infographic. The global smart contracts market will reach approximately $300 million by 202 (Market Research Future, 2021).
2022 blockchain insurtech infographic. 53% of insurers struggle to understand blockchain and its use cases. 43% have other technology taking priority. 38% are concerned with data security (Intellias, 2021).

10. Extended Reality (XR) Insurance Technology

The launch of the Metaverse got many businesses and insurance companies thinking about using extended reality to their advantage.

XR insurance technologies are changing how companies interact with society, and many insurers use them to their advantage. 

The Franklin Institute defines extended reality as using Augmented Reality (AR), Virtual Reality (VR), and Mixed Reality (MR), to offer and make more additional information about our environment clearer by enhancing our senses or to enable unnatural experiences through artificial intelligence.

A study by Accenture indicates 85% of insurance executives believe it’s essential to leverage XR insurance technology to close the physical distance gap when engaging with employees and customers.

XR technologies provide insurers with an opportunity to transform and improve many aspects of their business, such as: 

  • Training: Insurers can create virtual customers through extended reality to train customer service teams on how to communicate with clients, and walk them through the purchasing process. 
  • Risk Assessment: Underwriters can create XR simulations from on-site images and other illustrations to look for risks in buildings. 
  • Face-To-Face Interactions: Augmented imagery also helps insurers communicate and interact remotely with their clients. 

One of the most effective uses of extended reality in the insurance industry was PNB MetLife’s launch of “conVRse,” the first-ever on-demand, virtual reality customer service platform ever created in the insurance industry. 

The platform made customers wear a virtual reality headset and enter a 3D-simulated environment where they could interact with an insurance expert avatar that could address any questions and explain processes.

The “ConVRse,” was launched in 2017. Since then,  the market for XR technologies has grown significantly. A report by McKinsey finds AR and VR are expected to grow into a $95 billion market by 2025, an increase of $85 billion from 2017. 

11. Digital Distribution & Self-service

The pandemic changed how insurance agents communicate with clients and how clients can register for insurance products. 

A study by McKinsey says 90% of life insurance agents’ sales conversations and almost 70% of their client conversations were conducted in person in January of 2020. In May 2020, this number shrank to below 5%.

With the pandemic in full swing, insurers needed to increase their digital capabilities to communicate with clients remotely. Self-service portals enable insurers to improve their customer experience and boost sales. 

Consumer demand for self-service is also on the rise. A report by Accenture finds rising demand for digital insurance premiums and their online distribution is expected to displace US$280 billion of current insurance revenues by 2025

Digital distribution enables customers to purchase insurance products online, speeding up the purchasing process, and improving the customer experience. For example, State Farm’s virtual self-service portal allows clients to buy insurance policies online without taking a medical exam. The result has led to State Farm ranking second in client satisfaction amongst all life insurers. 

Digital distribution allows agents to do business with more clients, allowing insurance companies to lower commission costs per sale. In addition, the desire for superior digital tools amongst agents is more vital than ever as 44% of agents rated investing in digital tools or customer tools as the best way their employers can support them. 

12. Data-first Insurtech Ecosystems

Legacy systems are losing their value as the market rewards dynamic carriers that leverage APIs, microservices, and web services to build ecosystems that offer the right experience on the right platform to the right people. A study by McKinsey indicates ecosystems will account for 30% of global insurance revenues by 2025

Additionally, research from Accenture found 84% of insurance executives say ecosystems are essential to their strategy. These numbers indicate ecosystems will continue to be the insurance industry’s next big frontier for disruption.

The widespread adoption of smart mobile devices and the rise of always-on IoT devices have created a substantial amount of new electronic data. With more data produced than ever before, insurers are presented with a unique opportunity to develop data-first ecosystems. 

For example, auto insurers can use four terabytes of data produced from connected cars to offer personalized experiences to their clients. Life and health insurers are using wearable data that can track a client’s heart rate, sleep habits, how many steps a client walks per day, etc. 

Mike de Waal, CEO of Global IQX, elaborates:

To achieve data dominance, insurers must build up and scale big data ecosystems. These can include analytics platforms, data visualization platforms, business intelligence platforms, artificial intelligence tools, and Internet of Things (IoT) technology such as wearables and smart home devices.

Insurance digital ecosystems infographic. 30% of global insurance revenues will be accounted for by ecosystems by 2025 (McKinsey, 2018). 58% of insurance executives are actively seeking ecosystems and new business models. 84% of insurance executives say ecosystems are essential to their strategy (Accenture, 2020).

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

Insurers today are faced with a choice: innovate quickly, or lose market share to competitors and emerging insurtechs. 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 2022, 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 2022, 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 74% of insurance companies say accelerated underwriting has reduced wait times for policies, 59% say it has diminished policy issue costs, and 37% say it has helped increase sales. 

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. 

Accelerated underwriting infographic. On accelerated underwriting, 74% of insurers said it diminished policy issue costs, 59% said it reduced wait times for policies, and 37% said it helped increase sales (LIMRA, 2018).

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 2022, as the embedded insurance market is projected to reach $3 Trillion by 2023.  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.

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.

Wearable insurance technology infographic. 70% of consumers would share essential data on their health in exchange for lower prices from their insurers. (Accenture, 2020)

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. 

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.

Final Thoughts – The Road Ahead

Now you’re up to date on the top insurance technology trends for 2022. The problem is these technologies are constantly evolving, and keeping up can be a challenge. Moreover, with the enthusiasm surrounding insurtech, it is harder than ever to separate hype from real value. 

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. 

We wish your team the best of luck in 2022!

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Mike de Waal

Mike de Waal is president and founder of Global IQX, an Ottawa-based software provider of AI-driven sales and service solutions to employee benefits insurers.  He has deep experience in both software development and business management skills. Early in his career, he worked as a computer programmer and then went on to become a financial planner and a benefits consultant with giant Manulife Financial before becoming a tech entrepreneur.  He can be reached at [email protected].

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