Thanks to insurtech, a portmanteau of the terms insurance and technology, insurance businesses of today can enjoy a host of benefits. And this is only the beginning. As insurance technology redefining business paradigms and disrupting nearly all segments of the industry and its growth shows no sign of slowing down, a number of insurtech companies are popping up to help businesses leverage the power and potential of technology.
What is Insurance Technology?
Insurance technology or insurtech refers to the usage of technological innovations intended to help insurance companies streamline their operations, offer quality services, and save money. New and emerging technologies like artificial intelligence, blockchain, big data, DLT, etc are key examples of insurtech.
Popular Insurance Technologies
As mentioned above, insurtech encompasses any kind of software or technology used by businesses to automate and enhance insurance services. Some of the most popular insurance technology trends> are as follows:
Artificial Intelligence
Artificial Intelligence refers to the simulation of human intelligence demonstrated by machines. It helps with developing smart machines that are capable of performing human tasks. AI applies methods acquired from aspects of human intelligence, at a much better scale. For instance, it can process large volumes of data concerning customers. The data is then compared and results in personalized solutions for customers. It helps insurers find what is right for their customers.
Apart from helping with service personalization, AI is also used to forecast sales results, analyze policy risk, and manage claims. The insurance technology is getting so popular that its global market value is expected to reach USD 4.5 Billion by the year 2026, growing at a compound annual growth rate(CAGR) of 24 percent.
Machine Learning
While not limited to the insurance industry, machine learning, a branch of artificial intelligence) is a critical aspect for a number of insurtech companies in several ways. The industry, like all the other big industries, is flooded with data with an increasing number of sources like social media, documents, wearables, browsing activities, etc. Also, working with unstructured and semi-structured data can be difficult. Hence, insurance companies struggle in deriving proper value from data. This is where machine learning comes into the picture.
Machine learning can work efficiently with volumes of data. It allows businesses to calculate risks and generate personalized rating assessments. It is also used by insurance companies to boost their operational efficiency, customer service, and accuracy.
Blockchain
This popular insurance technology has a host of practical uses. Blockchain insurance tech makes room for automated collection of data and analysis in real-time. It not only makes the claims process faster but also more cost-effective. A number of blockchain use cases ranging from KYC, claims handling, and fraud prevention are being implemented by insurers across the globe. According to a survey over 80 percent of insurance agencies have either implemented or are planning to implement Blockchain. However, in order to accelerate and facilitate the adoption, agencies can collaborate with a trustworthy insurtech company.
IoT
IoT or the Internet of Things refers to a system of physical devices across the globe that are connected to the internet. The giant network of connected things and individuals collects and shares data about the way they are being used. It has emerged as a useful insurance technology that helps businesses streamline field operations, calculate risk more accurately, boost customer engagement, and avert disasters.
Robotic Process Automation
Robotic Process Automation or RPA refers to a software technology used for building, deploying, and managing software bots that can emulate human actions. A number of agencies are turning to this emerging insurance tech practice for streamlining enterprise operations and reducing costs. RPA eliminates repetitive, tedious tasks, freeing up employees to focus on more valuable work. Apart from automating and streamlining processes, it also helps in policy underwriting, onboarding, and claims processing. By using RPA robots across a series of systems, insurance businesses can increase accuracy and efficiency, reduce labor costs, and explore new avenues of innovation.
Predictive Analytics
Predictive analytics is a commendable insurance technology trend. Also known as advanced analytics, predictive analytics refers to the usage of statistics and meddling techniques for determining future performance and outcomes based on current and past data. Using the insights from predictive analytics can help insurers in a number of ways. For instance, it can be used for identifying insurance claims that can lead to heavy losses.
Better claims management and more streamlined underwriting are the key benefits brought by predictive analytics. However, the adoption of predictive analytics in the insurance industry is still in its early stages. The future of insurance technology looks promising and is expected to help insurers deliver better efficiency, more profitability, and higher engagement.
Key benefits of leveraging Insurance Technology
Here are some ways the smart solutions and services offered by an insurtech company can benefit insurance businesses:
Customer engagement
Chatbots, a prime example of emerging insurance technology, can engage customers through a variety of platforms like desktops and smartphones. Customers can ask questions or inquire about the services in their preferred language and get the appropriate responses without any human bias, delay, or error. This not just helps insurance businesses retain the existing customers but also boosts new customer acquisition. Apart from serving as a knowledge base for customers, smart bots also encourage upselling and cross-selling.
Moreover, AI-driven chatbots can gather information from the customers and transfer it to decision-makers. For businesses that want to keep their customers engaged, informed, and satisfied, chatbots can be a one-stop platform. They mold their communications with the customer as per the past interactions. A number of insurance companies are moving to chatbots for improvising their customer service and generating better business results.
Insurance Underwriting
Artificial intelligence is a leading insurance technology that has significantly overhauled the industry in the past decade. As such, AI-powered underwriting helps agencies overcome a number of barriers associated with manual underwriting. AI reduces the potential for human error and bias and makes room for more operational excellence. In the future, AI and ML are expected to become self-reliant. The human element can then be completely removed and the insurance tech can make decisions on its own.
Apart from AI, big data is also an emerging technology that significantly streamlines the underwriting process. For instance, brokers can compare the driving behavior of the policyholder with big data sets for accurately predicting risk and tailoring policies for each individual. A number of new and emerging insurance companies along with top insurance players are already leveraging the benefits of data and technology to stay ahead of their competition.
Risk assessment
The traditional approach towards risk management significantly relies on the claims history. However, insurance technology opens up new opportunities and ways to make better data-driven decisions. Access to real-time data and advanced analytics can help insurance businesses automate risk factor monitoring. This leads to more accurate and speedier decisions.
Predictive analytics offers cognitive insights and offers granular visibility into risks. For instance, it can alert insurers regarding added factors to be considered for evaluation. Data analytics and ML algorithms can be used to get the complete risk profile of the insured. It helps increase the risk selection efficiency.
Fraud identification
Insurance technology has revolutionized the way fraud is detected and prevented. Technologies like machine learning can easily detect advanced fraud across heavy volumes of data. They can “learn” to adapt to new, unique threats while generating minimum false positives. Apart from ML, AI, Blockchain, and IoT are also popular insurance technologies for fraud detection. The considerable drop in fraudulent claims with insurance tech solutions will bring tremendous advantages to insurance companies in the long run.
Final words
With time to come, insurance technology will touch every segment of the business processes and future-proof the operations. As a result, it is no longer a “nice-to-have” feature, but in fact, is a necessity that will keep insurance agencies afloat as the competition begins to heat up.
