These 5 Emerging Technology Trends Are Disrupting the Insurance Industry in 2022

Digital development in insurance is reshaping the way insurers do business. Insurtech is advancing quickly, and successful companies must adapt to the changes. Here are some of the most exciting emerging technologies that can significantly impact insurance in 2022.

• Predictive Analytics
• Artificial Intelligence (AI)
• Intelligent Automation (IA)
• Robotic Process Automation (RPA)
• Conversational Chatbot Interfaces

Although some of these digital insurance developments may have more impact than others, they all have the potential to disrupt the status quo. Insurance companies that embrace these new technologies can deliver a more personalized, cost-effective, and secure customer experience.

The insurance industry is arriving at the forefront of adopting emerging technology to improve the customer experience. Insurtech solutions provide new ways to interact with customers, improve underwriting processes, automate claims handling, and optimize business operations.

Businesses in the insurance industry that aren’t leveraging Insurtech are likely still using outdated legacy systems and archaic paper-based processes. These companies can’t survive modern consumer expectations unless they stay updated on emerging technology.

Updating legacy systems once or implementing a one-time technology solution isn’t enough to stay relevant in an increasingly competitive and tech-driven industry. Continual process improvements and enhanced customer experiences require the ongoing adoption of technology.

A new age of industrial competitiveness in which firms compete based on their infrastructure is emerging. Growing investments in technologies are ushering in new business.
Predictive Analytics, Artificial Intelligence, Intelligent Automation, Robotic Process Automation, and chatbot technologies are placing tremendous capabilities in the hands of individuals and enterprises.
Below are five emerging trends expected to disrupt the insurance industry in 2022 and beyond.

The increase in data and the rise of Analytics have created new opportunities for insurers to understand customers better than ever before. Predictive Analytics can improve the customer experience and underwriting decisions if done correctly.
Many insurers utilize predictive analytics to collect data and better understand or forecast client behavior. But there are other valuable applications for Predictive Analytics as well, such as:

• Pricing and risk assessment
• Identifying which consumers are likely to cancel
• Detecting fraud
• Prioritizing claims
• Identifying outlying claims
• Predicting purchasing trends

Many insurers find that predictive modeling strategies increase revenues and accuracy.

While several carriers are experimenting with artificial intelligence, just a handful effectively expanded these capabilities throughout the industry. AI enables businesses to re-engineer critical operations to be more predictive. As AI and algorithm building become more mainstream, these capabilities will only improve.

Applying AI to fundamental processes can streamline distribution, underwriting, claims, and service tasks, resulting in a “human in the loop” paradigm. These applications boost efficiency and allow for higher-quality interactions with consumers.

Most carriers fail to capitalize on the value of their data assets, such as claims histories and distribution relationships. But in addition to re-engineering fundamental operations, AI can help develop data-driven goods and services.

Intelligent automation (IA) blends RPA with other sophisticated technologies like AI, analytics, optical character recognition (OCR), and intelligent character recognition (ICR) to develop self-learning, self-adapting processes. Another term for intelligent automation is hyper-automation.

Hyper-automation is a hot topic among insurance executives and business leaders. By automating more business processes, insurers can dramatically improve productivity and customer satisfaction while reducing costs and risks. These advantages make hyper-automation a priority for the insurance industry.

Historically, the insurance industry has been challenged with manual processes and legacy systems that are difficult or impossible to integrate with new technologies. These challenges have limited the ability of insurers to differentiate through technology and forced them to rely on core competencies such as underwriting expertise and claims handling experience.

Today, insurers find ways to utilize intelligent automation tools that dramatically boost productivity and human satisfaction. As they do so, they are also gaining a competitive edge needed to become leading insurance providers.

Robotic Process Automation (RPA) is a tool that allows anybody to set up computer software or a “robot” to mimic and combine the activities of a human engaging with digital systems to complete a business process.

RPA, like people, uses a user interface to take data and operate programs. The technology interprets, triggers responses, and communicates with other systems to perform repetitive tasks.

Using the UiPath Robotic Process Automation solution, companies can automate their business processes in legacy systems, including transaction processing, data migration, operating mainframe applications, and other manual tasks where cost reduction, accuracy, and speed are critical.

Businesses across industries are leveraging RPA as a fast, low-risk starting point on their path towards the Digital Workforce of tomorrow. RPA empowers people to focus on higher-value, strategic initiatives by automating routine, repetitive tasks usually performed by knowledge workers today. From back-office processing to customer service, RPA is helping companies around the world transform how work gets done.

AI bots can be programmed with more advanced functionality like sentiment analysis to identify users’ emotions based on their words or tone of voice. They are often equipped to access specific databases when needed and can even connect users directly with a live person for additional support.

Unlike rule-based chatbots, which follow a strict algorithm and only respond to specific commands, artificial intelligence chatbots use machine learning and natural language processing to generate more human-sounding responses.

For example, when a customer says, “I have an issue with my policy,” the bot might ask for clarification on what exactly is wrong. Then, the chatbot would perform a search through the company’s database to find the most relevant information to serve up as a solution.

Over time, AI chatbots become more intelligent and better able to answer questions and resolve issues without human assistance. AI also allows bots to learn from each interaction they have with customers. This capability cuts down on the number of incoming support tickets and reduces wait times for customers — all while improving overall customer satisfaction.

Disruptive goods and services alter how insurers interact with their clients. Companies must extend their capabilities through strategic and intuitive partnerships to satisfy changing customer expectations.

RD Global helps businesses reach out to clients in new ways, using future-ready technology and streamlined practices.

By shifting from a reactive risk-averse approach to a proactive style of risk minimization, players in the insurance industry can position themselves for long-term success and growth.