What are the uses of artificial intelligence in the insurance industry?
AI is being used by insurers to offer customers better, quicker, and less expensive services. Numerous AI platforms for insurance companies are on the market, many of which are supported by AI-enabled insurance tools that will aid insurers in efficiently handling tasks and providing excellent customer service.
The insurers that prioritize AI have an advantage over their rivals thanks to AI and machine learning. The most recent developments in the field of AI insurance are summarized here, along with examples of how they are being used in the real world.
Read More: Artificial Intelligence Models
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What Does AI in Insurance Mean?
When insurers understand how to integrate cutting-edge technology into the digital insurance continuum, they will have successfully implemented insurance AI. However, AI can be used for direct marketing, risk management, fraud detection, underwriting, and insurance advice, as well as for processing insurance claims.
The insurance industry now has the opportunity to use AI to create value, cut costs, boost efficiency, and increase customer satisfaction and trust while also reducing costs thanks to consumer behavior and technological advancements.
Benefits Of Artificial Intelligence In The Insurance Industry
Stakeholders in this ecosystem are in agreement about the advantages of applying AI to the insurance industry. In fact, 84% of French investors surveyed agreed that AI would completely transform the insurance industry. Additionally, according to 66% of insurers, AI can increase workforce productivity.
- Insurance companies can increase productivity, cut expenses, enhance customer experience, and save time by integrating AI into their business processes.
- AI can also streamline procedures that are typically time-consuming and tedious, such as underwriting, claims management, fraud detection, and customer service.
- Insurance companies can lessen human error using AI. Due to factors like changing the regulation of information to analyze for fraud prevention, these errors may be frequent.
AI In Different Insurance Industries
With the aid of conversational AI, a response can be modified to take into account the context of the entire conversation. While enhancing the customer experience in the insurance industry, the highly intelligent and personalized approach raises the customer’s trust in the overall service.
By adopting the 24/7 customer service channel, insurers can rely on AI chatbots to deploy insurance processes. Virtual agents with conversational AI capabilities can educate customers about different insurance policies and rank them according to their needs.
Bots with intelligence can understand a customer’s needs and expectations and ask the appropriate questions. Based on their responses, it is simple to determine the customer’s true intent using Natural Language Processing (NLP). The best policies can also be suggested by bots based on the customer’s profile, risk assessment, and type of coverage required.
Insurance AI solutions can be applied across different types of insurance policies:
1. AI For Automobile Industry
The auto industry is about to undergo a remarkable transformation. To stay one step ahead of rivals in the market, automakers all over the world have begun integrating cutting-edge technologies into their products and processes.
Machine learning and AI for motor insurance companies have been seen to work their magic in autonomous vehicles and automate motor insurance underwriting.
The largest general insurance provider in Australia, IAG, uses AI to assess vehicle damage and shorten claim processing times.
To evaluate the effects of auto accidents and expedite insurance claims for clients, the company uses an AI-based system. The support team can determine whether a car is a total loss after an accident, and by avoiding the need to tow the car to a garage for an inspection, they can cut the time it takes to process claims from weeks to days.
Key Use Cases For Ai Auto Insurance
- Predictive Analytics for Manufacturing: Automakers can cut costs by using AI in the production of their vehicles, which also makes the factory floor safer and more productive. It also helps in predicting malfunctions in automotive parts
- Vehicle Maintenance Recommendations: Motor insurance companies use AI and ML algorithms to help make recommendations to drivers about how to maintain their vehicles.
- Driver Behavior Analytics: Numerous useful in-car analytics are available thanks to AI-based automotive applications. In order to prevent accidents, cameras and IR sensors can accurately identify the driver’s actions and send out warning signals.
2. AI In The Health Insurance Industry
Healthcare is about to undergo a radical change thanks to artificial intelligence. Compared to conventional analytics and clinical decision-making methods, AI health insurance has some advantages.
With the aid of artificial intelligence (AI) in health insurance, medical professionals will be better able to comprehend the daily routines and requirements of the patients they care for, and will be able to give them better feedback, direction, and encouragement to maintain their health.
AI is widely used in healthcare insurance by many businesses.
The Canadian AI insurance company Alayacare serves as the ideal example.
It provides home healthcare professionals with a cloud-based software platform. The platform offers telehealth, remote patient monitoring, back-office functionality, and clinical documentation. Additionally, it aids in the analysis of wearable devices to collect patient data for processing through machine learning technology by providing real-time insights for healthcare professionals.
Key Ai Use Cases In Health Insurance
- Faster Disease Detection: By quickly alerting care teams to problems and detecting them with AI, healthcare insurance companies are able to save lives by quickly discussing treatment options with patients and making decisions.
- More Accuracy in Diagnosis: In the field of health insurance, AI and ML aid pathologists in developing more precise diagnoses and specialized treatment plans.
- AI is a Great Symptom Checker: When a healthcare chatbot is used, it will listen to the patient’s symptoms and health concerns before directing them to the best care possible based on their diagnosis.
3. AI For Life Insurance Claims
The insurance industry is changing along with the rapidly evolving technology world as a result of changing customer expectations. More customer insights are needed by insurance companies, as well as the capacity to use these insights.
AI has the potential to boost profits, boost productivity, and lower risk in the life insurance industry. Artificial intelligence (AI) has the power to reduce mortality, enhance decision-making, and support the creation of profitable, long-lasting client relationships.
Along with personalized pricing, disease severity prediction, submission prioritization, and quick product development, the use of AI in life insurance underwriting can be established.
Life Insurance Ai Help Insurers In Following Ways
- Marketing & Sales: Customers can be segmented, opportunities can be targeted, prospects can be qualified, products can be personalized, and opportunities can be qualified with the aid of an AI solution for life insurance.
- Real-time Engagement: Insurance companies lose money from non-renewals, and AI can forecast this possibility. Inferring the proper renewal price change (RPC) is possible using such predictions.
- Mortality Reserving: AI for life insurance claims can assist you in calculating individual mortality reserving, individual persistence estimating, overall profitability, and cash flow.
4. AI For Customer Communications
As customers no longer put up with drawn-out insurance applications or a complicated claims process, insurers take changing customer needs and expectations into account. For insurance companies, it is crucial to incorporate automation and AI into their customer communication model.
The demand for dynamic products can be met, and insurers can attract a new customer base made up of younger demographics thanks to conversational AI’s ability to enable growth and disruption.
Customer experiences and operational efficiency have greatly improved in the insurance sector thanks to AI in customer communications.
How Ai In Customer Communications Deliver A Transformative Experience:
- Increased Efficiency of Claim Process: AI aids in restructuring the claims process for both new and current policyholders. By relieving the burden on human agents, voice AI can assist in handling high call volumes. McKinsey predicts claims processing will remain the primary function of all insurers in 2030 & AI technology will reduce the overhead associated with claims by 70 to 90%.
- Policy Management: A better customer experience can be achieved by automating frequent customer requests, such as getting assistance with documents, using chatbots that are AI-enabled.
- Generating Quotes: After receiving a quote, customers typically have questions. Insurers can save agents’ time until a more complicated question comes up by utilizing voice AI to assist customers with these requests.
5. AI For Property Insurance Sector
Many different industries are currently using AI-based technology, including the insurance sector, which offers both residential and commercial property insurance. It could revolutionize the way that property insurance operates.
The claims process is accelerated and made more precise with the help of artificial intelligence. Its capacity to automate numerous tasks is increasing overall efficiency, which translates to better results and customer service.
Key Use Cases: Ai For Property Insurance Companies
- Risk Analysis & Underwriting: An improved understanding of potential risks, the best policy and level of coverage for your needs, and strategies to lower your risk of future claims can all be obtained by using AI to analyze data.
- Fraud Detection: AI chatbots assist in automating a number of processes that are frequently the target of fraud and act without the assistance of a human. Additionally, it can mark brand-new policies, aiding in the detection of those who are more likely to commit insurance fraud.
- Automated Claims Processing: Customers can use AI to report claims, record losses or damages, check policies and limits, communicate with customers, and receive updates on the status of their claims from insurers and other parties.
6. AI For Commercial Insurance
Software that can recognize patterns, extrapolate predictions, and manage information more quickly and effectively can all be created using artificial intelligence, according to programmers.
AI can quickly identify patterns and risk indicators in commercial insurance. The use of artificial intelligence for these capabilities is being embraced by both new and established insurance companies.
Detailed Use Cases Of AI In The Insurance Industry
Investments in artificial intelligence clearly payoff as McKinsey estimates that across functions and use cases The potential annual value that AI investments could create for the insurance sector is staggering at $1.1 trillion.
So what do those billion-dollar deep pockets of value for insurance companies mean?
1. Deliver Efficient Customer Support
To speed up response times and reduce operating expenses, an increasing number of insurance companies are incorporating chatbots into their customer service offerings.
Your team’s productivity increases as a result of the customer service bots’ quick resolution of simple queries, freeing up time for handling more complicated ones.
AI-powered digital solutions are ready to improve every facet of your business by transforming customer service interactions, including online customer experience, loyalty, brand reputation, and the creation of revenue streams.
When used properly, AI can improve the customer experience in almost every area, from data collection to speech recognition and message response times.
By using virtual agents (chatbots) and customized interactive videos, AI makes it possible to provide multichannel customer service 24 hours a day, seven days a week.
Here is how insurance in AI helps in delivering excellent customer service:
- Resolve Frequently Asked Questions (FAQs): AI chatbots can be used to respond to frequent questions posed by users. You can cut the number of support tickets, provide effective service, and reduce business expenses by answering more than 50% of frequently asked questions right away.
- Learning Customer Behavior Patterns: AI in insurance can be used to identify patterns in customer behavior and make future predictions. Based on the time and date of prior activities, the patterns can be used intelligently to offer the service options or information that is most likely to be useful.
- Faster Response Times: Utilizing AI in the insurance industry speeds up customer support agents’ response times. It assists in determining the needs of the customer and providing the agents with the appropriate information, resulting in best-in-class customer service. This task is easily completed by chatbots in the banking industry, and the insurance sector can do the same.
- Utilizing Natural Language Understanding: To better understand customer service conversations, NLU aids in real-time analysis of calls, chats, and emails. AI enables sales representatives to comprehend customer problems and provide faster resolution.
2. Claim Fraud Detection And Prevention
In order to identify insurance scams, artificial intelligence (AI) relies on the detection of false claims. As a result, insurers can create a system for managing claims that are effective and efficient.
Insurance AI algorithms can quickly analyze vast amounts of data to find patterns and identify anomalies that don’t fit the patterns.
AI is already being used in numerous applications, from sophisticated chatbots that provide 24-7 customer service to the variety of machine learning technologies that strengthen processes through automation.
The initial discomfort and reluctance surrounding AI’s implementation in the insurance industry have diminished as a result of increased knowledge and resources about the industry-changing impact of AI, and more and more compelling evidence of the advantages AI can provide is now emerging.
Insurance powered by AI not only automates the scheduling of high-level tasks but also improves customer service by assisting agents in making sound judgments and decisions.
Here is a look at some ways in which AI in insurance is making a difference in fraudulent claim detection and prevention:
- Big fraud schemes: Utilizing AI for insurance allows for extensive cross-referencing and analysis of data points found in internal and external databases. It is an excellent method for making the detection of insurance fraud simpler.
- Fraud Patterns: It would be much more practical to use AI in insurance to detect fraud.
For instance, if someone reports that his smartphone was stolen, a database search can be done to check for any previous suspicious activity. If any are found, a cautionary note can be issued, and more time given to this claim by an expert.
3. Accelerated Claims Processing
Customers now expect real-time, efficient, on-demand claim submission and processing in the digital age.
The insurers now provide new channels for filing claims, such as through submissions made through web portals or mobile devices.
Customers are now helped by insurance AI systems when submitting claims by directing them through the claims submission process.
An AI-powered claims bot, for instance, could examine the claim, confirm the details of the insurance policy, and run it through a fraud detection algorithm before sending wire instructions to the insurance company to settle the claim.
How AI in insurance help to streamline claim processing:
- The current state of claim processes handled by numerous employees can be improved by implementing AI-based chatbots.
- Touchless insurance claim processes, which are powered by artificial intelligence, can eliminate needless human involvement and can report the claim, document damage, update the system, and get in touch with the customer all by themselves.
- Typed forms from scanned documents can be accurately captured using document capture technologies and optical character recognition.
- Insurance AI can now read the handwritten text at a level that is superior to human ability.
- From claims routing to approvals, many steps in the claims process are currently being automated with success.
This is how insurance providers use AI, and because it is such a simple process, customers can submit their claims without any hassle.
4. Insurance Pricing And Underwriting
A key component of insurance is underwriting, which allows insurers to evaluate risk and set premiums for accepting it.
Researching the risk profile of the customer in-depth is necessary for evaluating and pricing risk. As a result, manual underwriting takes a lot of time, is prone to mistakes, and may result in ineffective pricing. Because of this, AI is a good fit for processes like risk pricing and underwriting.
With AI in insurance, the process of estimating risk is more accurate and efficient, giving users of the technology a competitive edge.
56% of insurance executives believe that Operations would be more productive thanks to AI.
Artificial intelligence applications help insurance companies run processes more quickly and profitably, from deep learning to RPA and chatbots.
These are the most significant ways AI in insurance enhances underwriting.
- Efficient Application Processing: Underwriters can automate data collection, data extraction, form completion, and other repetitive tasks with the aid of insurance AI.
- Better Risk Assessment: Underwriters can better comprehend the risk connected to customer profiles by utilizing AI and ML models in insurance along with other analytical techniques.
- Deliver Frictionless Customer Experience: Given that customers expect real-time service across all digital touchpoints, AI in insurance has the potential to significantly accelerate underwriting workflows.
- Improved Profitability: AI-based automation processes decrease operational costs, customer churn, and customer retention expenses while increasing underwriting profitability.
5. Claims Reserve Optimization
Without a doubt, in order to thrive in the current digital era, insurance companies must dive in headfirst and adopt digital and AI technologies.
Insurance companies must streamline their claims operations due to the inefficiencies in the claims registration process, which is one of the biggest problems in claims management. The repetitive and data-intensive process causes operational inefficiencies.
How AI-based Insurance solutions help in claim reserve optimization
- Handling Claims Estimation in Real Time: Utilizing ML and AI in the insurance industry reduces the amount of time that is typically lost in gathering the data necessary for claim analysis.
- Early Detection of Fraud: Utilizes artificial intelligence (AI) to detect insurance fraud and assists in removing the manual effort and time-consuming claim processing procedures that cause claims to be delayed.
- Inspect Hazardous Locations: Utilizing AI in insurance reduces safety risks for claims examiners and false compensation claims while also assisting in damage assessment.
To differentiate themselves in the crowded market, businesses are embracing AI-based insurance solutions. Every insurer wants to increase revenue and cut costs. They have to embrace new business practices and innovative technologies.
6. Personalized Recommendations
Customers have a range of needs, tastes, and lifestyles. They anticipate customized rules, loyalty schemes, and advice based on their unique preferences and characteristics.
Customers who are engaged and pleased are 80% more likely to renew their existing policy.
Personalized insurance plans are now being offered by insurers through tools built using machine learning and artificial intelligence models that have been trained on specific customer preferences.
By implementing insurance chatbots, or virtual assistants, you can ensure that customers have adequate coverage and provide a first-rate experience by offering machine-generated insurance advice.
Voice bots can interact with customers and advertise tailored offers. The customers will be kept on the platform and won’t be acquired by rivals thanks to this. Personalized recommendations are also shared, and additional insurance policies are sold.
7. Prediction Of Customer Churn
It is clear that the cost of acquiring new customers is significantly higher in the insurance sector than in many other industries. Keeping an existing customer is much less expensive than finding new ones.
Insurance companies are using AI-based churn prediction solutions to forecast when customers may leave, allowing them to take preventative action to keep their customers.
Leading indicators, such as shifts in app and rewards program usage, a change in how frequently a customer contacts customer support, changes in income, or shifts in life circumstances, can be found with the aid of AI and machine learning algorithms.
By observing changes in work habits and employee satisfaction, the algorithms can also predict employee attrition.
Thus, it is a win-win formula for both insurance companies and customers.
AI-related Trends Shaping Insurance
Our businesses, homes, cars, and even ourselves are already equipped with the underlying technologies of artificial intelligence. The disruption caused by COVID-19 altered the adoption timelines for AI by dramatically accelerating digitization for insurers. Organizations had to adapt almost immediately to support remote workers, expand their digital capabilities to support distribution, and improve their online channels. Even though the majority of businesses probably didn’t make significant investments in AI during the pandemic, the increased focus on digital technologies and a greater openness to change will make it easier for them to integrate AI into their workflows.
Explosion Of Data From Connected Devices
Sensor-equipped equipment has long been commonplace in industrial settings, but the number of connected consumer devices will skyrocket in the coming years. Along with new, expanding categories like clothing, eyewear, home appliances, medical devices, and shoes, the penetration of existing devices (like cars, fitness trackers, home assistants, smartphones, and smartwatches) will continue to rise quickly. Up to a trillion connected devices, according to experts, will exist by 2025.2 With the avalanche of new data these devices will generate, carriers will be able to better understand their customers, leading to the development of new product categories, more individualized pricing, and an increase in the real-time delivery of services.
Increased Prevalence Of Physical Robotics
Recent exciting developments in the field of robotics will continue to alter how people interact with their environment. Future manufacturing and commercial insurance products will be drastically altered by additive manufacturing, also known as 3-D printing. Carriers will need to evaluate how the widespread use of 3-D printed buildings by 2025 alters risk evaluations. Furthermore, in the following ten years, commercially viable programmable, autonomous drones, autonomous farming machinery, and improved surgical robots will all be available. Much more common standard vehicles will have autonomous features, like self-driving capabilities, by 2030. Carriers will need to comprehend how risk pools will change as robotics becomes more prevalent in daily life and across industries, how customer expectations will change, and how new products and channels will be made possible.
Open-source And Data Ecosystems
To ensure that data can be shared and used across industries as it becomes more commonplace, open-source protocols will start to appear. A number of public and private organizations will collaborate to build ecosystems that will allow them to share data for a variety of use cases while operating within a common regulatory and cybersecurity framework. Wearable data, for instance, could be transferred directly to insurance companies and connected home and auto data could be made accessible through companies like Amazon, Apple, Google, and a number of other consumer electronics producers.
Advances In Cognitive Technologies
Convolutional neural networks and other deep learning technologies, which are currently primarily used for unstructured text, voice, and image processing, will advance to be used in a wide range of applications. These cognitive technologies, which are loosely based on the human brain’s ability to learn through decomposition and inference, will become the standard approach for processing the incredibly large and complex data streams that will be generated by “active” insurance products tied to an individual’s behavior and activities. Carriers will have access to models that are constantly learning from their environment and adapting to new product categories and engagement strategies as a result of the increased commercialization of these technologies, allowing them to react in real-time to changes in underlying risks or behaviors.
Future Of AI In The Insurance Industry
Following the pandemic, the insurance sector is under intense pressure.
Neither artificial intelligence (AI) nor other related technologies are a “silver bullet” solution to all the underlying stressors. However—
The use cases for AI in insurance discussed in this post have a great deal of potential to increase operational effectiveness, control costs, and allow insurance companies to shift to product lines with enhanced technology and customer experiences that are centered around the digital world.
For both insurers and their clients, AI is set to completely disrupt the insurance market. Customers might benefit from a smoother user experience and more reasonable prices.
By streamlining their procedures or introducing AI-powered auto insurance policies, insurance companies may be able to reduce costs. It is only a matter of time before these advancements become a reality because the potential of AI is limitless.
The insurance sector is changing as a result of AI. As a result, they can set their policies at a safer level. Some insurance companies are already utilizing AI technologies to make more accurate risk predictions.