How AI is Preparing The Insurance Industry For 2022 and Beyond
Have you read about Scott? The customer of the year 2030 who got the AI technology working for him for every second he breathes. Mckinsey published an article titled ‘Insurance 2030—The impact of AI on the future of Insurance’ that introduced us to Scott, and the possibilities that AI brings to this industry.
The article talks about how AI helps him order a self-driving vehicle, shares his potential route with the mobility insurer, suggests routes with lower auto damages, calculates adjustment to the monthly premium, notifies him about the same, and automatically debits the additional amount from his bank. That’s not all!
When Scott accidentally bumps the car, AI determines the extent of damage, instructs him to take pictures, confirms that the claims have been approved, and directs it to the nearest garage. Though the author of the article assures that the above scenario is little beyond imagination, but confirms that the technologies required to turn it into reality already exist. In fact, we are using them currently in the insurance industry for document processing, chatbots, and affective computing.
With the advancements in Machine Learning, Predictive Analytics, Deep Learning, and Big Data Analytics, the applications of AI will accelerate. It will unlock a whole new realm of opportunities for the insurance sector along with improving profitability and delivering enhancing customers.
Current potential of AI in the Insurance Industry
“The real power of AI is in augmenting human capabilities for better decision making, more productivity, efficiency and letting humans focus on higher value-added tasks.”
- Siva Parameswaran, Co-founder, and Chief Creator at purpleSlate.
AI has the potential to affect the insurance industry in multiple ways. In 2021, over 40% of CIOs plan to increase their spending on AI use cases and pilot projects. Over 76% of insurance executives reports that the stakes for innovation have never been higher.
AI is already transforming areas such as underwriting, customer service, claims, marketing, and fraud detection. McKinsey estimates that across functions and use cases AI investments can drive up to a whopping $1.1 trillion in potential annual value for the insurance industry.
AI technology is helping computer systems accomplish tasks that typically require human intelligence. 25% of the insurance industry and its 50-60% of back-office processes will be automated in 2025. With an increase in the number of connected devices like smartphones, fitness trackers, home assistants the amount of consumer data is growing rapidly.
Insurance companies can leverage this data to draft more personalized customer policies tailored to their unique needs. They can evaluate customers’ risk profiles more accurately, create meaningful marketing campaigns and sell the right product to the right customer.
Benefits of AI in the Insurance Industry
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Better Operational Efficiency
Errors are a common occurrence in insurance services, mainly during the claim cycle. With AI at the side, InsurTechs can virtually eliminate human errors and increase operational efficiency. It improves insurers’ business processes and drives down costs by automating underwritings, customer service, and claims processing.
AI applications in chatbots are a great addition to live agents. They can evaluate the information declared by the customer, process and integrate customer info, authenticate documents and potentially make a huge difference to the insurance industry. Apart from this, chatbots can provide support to as many customers simultaneously as necessary.
It can answer their queries, ask questions and make payments with its ability to process and interact in natural language. Finally, AI makes insurance processes leaner, increases efficiency, and provides a better workflow.
Quick Case Study: AI-Powered Chatbot Helped Bank Improve Customer Satisfaction and Productivity
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Fraud Detection and Prevention
Unfortunately, fraud is also a common occurrence within the insurance industry. The FBI estimates that the total cost of insurance fraud (excluding health insurance) is more than $40 billion per year. It costs the average U.S. family between $400 and $700 per year.
AI-powered fraud detection software leverages predictive analytics and text analysis to identify fraudulent claims based on the data captured. It can compare claims against databases to search for unusual patterns and make automated decisions to approve or reject the transaction.
The insurance industry can run quick background checks during the customer onboarding stage and carefully calculate the risks associated with the businesses or an individual. AI also helps analysts make manual decisions by providing visual analysis, queries, reports, and scores.
Turkish insurer, Anadolu Sigorta, recently realized a 210% ROI in just one year after switching to a predictive system. They attributed over $5.7 million in saved fraud detection and prevention costs to the new AI system.
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Underwriting and Pricing
“A lot of manual effort goes into the risk management by the underwriters which are prone to errors and bias. With the advent of AI applications, it has become easier to quickly aggregate large sets of data into various formats. With the use of pre-set identifiers and models, human underwriters can view the results and make more informed decisions without the manual effort of going through each data.”
- Parameswaran Subbaraman, VP Delivery at iLink Digital
AI-driven underwriting systems assist the underwriters by accurately quantifying structured, semi-structured, unstructured, and qualitative data points. Data gathered from social media, news feeds, reliable statistics from public sources, and third parties are used for the analysis. They convey a comprehensive risk profile to the underwriters in a highly interpretable manner. This enables the underwriters to make informed decisions in a quick turnaround time.
AI can also integrate the overall profitability into underwriting decisions. It can focus on customer information individually, as a subset of a product, and as a subset of a particular group. The result is that the overall customer relationship is kept in mind while performing each underwriting task.
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Streamlined Claims Management
Claims management includes a lot of repetitive, standardized, and attention-requiring workflows. These tasks are also prone to errors and inefficiencies and hence need to be reviewed and investigated before approval. Besides, traditional paper-based claims management processes can eat up to 50% – 80% of premiums’ revenues.
With AI and Intelligent Automation, insurance companies can efficiently handle tasks like claim processing, document processing, appeals processing, application processing, insurance pricing, and document verification. They can rapidly process large volumes of documents and check if it fits the regulations.
AI can assess customers’ profiles and suggest an optimal price to quote the right insurance plan, improving customer satisfaction. When it comes to the underwriting process, Computer Vision technology along with IoT data helps insurers to record the asset state at the time of underwriting and keep making adjustments in real-time.
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Improved Customer Experience
“Insurance industry thrives with the humans in the middle, in the form of customers and intermediaries. AI can play such a critical role in improving customer experience, personalizing products, and improving operational efficiency – all towards the bottom-line goals of improving sales, managing risks better, and reducing costs.”
- Siva Parameswaran, Co-founder, and Chief Creator at purpleSlate.
Successful companies plan their entire business around customer experience. With Conversational AI, insurers can elevate their game by providing round-the-clock customer services and personalized assistance. As per Accenture, 80% of insurance customers are looking for more personalized customer experiences. AI provides them the capabilities to deliver a seamless, user-friendly, end-to-end customer experience.
AI-powered chatbots and automated assistants can easily understand customer queries and respond instantly to their basic questions. This helps to cut costs, reduce high touch call volumes and free up human resources for other value-added services.
In addition, Conversational AI educates customers about insurance policies and provides personalized recommendations based upon their needs. It can also offer wellness tips combined with the option to incentivize good habits and appropriate pricing discounts. AI-empowered Intelligent Virtual Agents can even suggest saving money and proactively notify them on renewals, making the whole insurance experience convenient for customers.
Related Reading: How Chatbot Can Help Improve Customer Interactions?
AI Technologies used in Insurance Industry
AI can offer the above benefits only because of many related technologies. Some of which are:
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Machine Learning (ML)
Machine Learning is a branch of AI that uses training computers to identify patterns in data and algorithms to predict outcomes. It provides systems to automatically learn by analyzing unstructured data and using it to drive better business decisions. A major benefit of Machine Learning is that it can effectively analyze structured, semi-structured, or unstructured datasets. It can be used to identify the risks associated with claims, understand customer behavior and detect frauds with higher predictive accuracy.
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Deep Learning
Deep Learning is an application of Machine Learning. It is beneficial to detect damages during an accident and identify anomalies in billing. This helps the insurance industry to detect fraud, provide optimal insurance prices, and reduce costs. It also helps them better understand customer profiles, evaluate risks and provide better customer experiences.
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Chatbots
63% of consumers are more likely to buy insurance from a company if they had the option to message them instead of just calling. From managing claims instantly to delivering customized quotes, chatbots play a curial role in the insurance industry. It simplifies every insurance-related process, enabling human employees to focus on value-added tasks. Chatbots can even forward call to specific agents based on the customer’s needs. This helps the company secure more leads and take their products wider market.
Quick Case Study: Productivity improvement with Birdie, a virtual assistant
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Affective Computing
Affective computing, also known as ‘Emotion AI’, helps the insurance industry to recognize human emotions and act accordingly. This includes identifying changes in facial expressions, eye movements, heart rate, blood pressure, voice volume, tone, or speed fluctuations. It has practical applications in claim automation and processes as it can understand if the customer is lying while submitting a claim.
It can also identify a frustrated customer and direct calls to more expired call agents through intelligent call routing. As per Gartner, 10 percent of personal devices will have Emotion AI capabilities by 2022.
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Natural Language Processing (NPL)
NPL help insurance virtual agents to understand, interpret and respond in written text or speech. It gives them the ability to analyze a large number of claims and create a database for further use. Insurers with help of NLP can speed up decision-making, reduce costs and avoid human errors.
Quick Case Study: NLP solution for a leading Veterinary Hospital
Other technologies helping the insurance industry:
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IoT and Smart Devices
The prevalence of IoT devices and connective capabilities brings in new opportunities for insurers. With a large amount of data to process, they can assess customer profiles, speed up and optimize claims process, eliminate data duplication and eventually reduce customer frustration. Buyers can save themselves from the paperwork and easily track coverage through digital platforms. Insurers can accurately predict potential losses as well as alert customers of the same.
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Robotic Process Automation
RPA empowers insurance companies to build highly responsive processes while decreasing operational costs. It emulates the repetitive, rule-based repetitive tasks that require no decision-making capability. Ultimately your employees can focus on higher-value work that needs human attention.
Future of AI in the Insurance Industry
“We are in the early stages of an ‘AI First’ generation. With serious investments in digital transformation efforts across the globe, almost every business entity today is becoming a ‘data’ company. This data acts as the core fuel to drive the next generation AI efforts.”
- Siva Parameswaran, Co-founder, and Chief Creator at purpleSlate.
Rapid advances in AI technology will bring disruptive changes to the insurance industry. Customer service is the key area to witness a lot of traction on the usage of AI. Smooth-talking virtual assistants will handle a significant portion of the customer calls with ease and in multiple languages.
Other areas that would see significant AI adoption would be hyper-personalized products and services to meet the individual customer needs, risk factors, automated claims processing, and fraud detection. Organizations with a mindset focused on creating opportunities with these technologies will thrive and triumph in the competitive market.
What’s different about the iLink approach?
iLink, with its group company purple slate, is playing a major role in the digital transformation journey of one of the leading Health Insurance providers in the country. We have been part of the complete project life cycle for more than two years now. Right from the ideation to the implementation of a true omnichannel digital interface, including conversational channels.
With our deep expertise and proven business results in Conversational AI and voice-related technologies, we understand what it takes to be a trusted partner to our customers. Have a question? Our team is here to help!
Endnotes
4. https://research.aimultiple.com/digital-transformation-stats/
5. https://www.fbi.gov/stats-services/publications/insurance-fraud
6. https://www.friss.com/customer-story/anadolu-sigorta/
8. https://www.h2o.ai/solutions/usecases/personalized-product-bundling/
10. https://www.gartner.com/smarterwithgartner/13-surprising-uses-for-emotion-ai-technology/
