How AI Drives Digital Transformation in The Insurance Industry
The Growing Application of AI in Insurance Leads to a Radical Transformation
- Why does the insurance industry require AI now?
- What are the benefits of AI in the insurance industry?
- Top 3 primary use cases for AI in the insurance industry
- Must-have AI technologies for the insurance industry
- Are you ready to ride on the wave of AI?
Digital transformation is not a business decision, it is a survival strategy. The Insurance industry is slowly recognizing that this vital truth is applicable to them as well. As insurers face several strategic and operational challenges due to the COVID-19 pandemic, they are recognizing that technology is the only answer and solution. Armed with this knowledge, the insurance industry is undergoing a swift and tremendous transformation, driven by the burning need to improve customer experience.
Artificial Intelligence lies at the heart of these changes and is fundamental to success. AI tries to solve the age-old problems by integrating them with existing infrastructure or by replacing legacy systems. This article answers some of the pertinent questions that will assist industry leaders in making an informed decision.
Why does the insurance industry require AI now?
Unlike many other challenges that are usually contained to one geographic location, COVID-19 is impacting essentially every corner of the world. It gave the entire planet a crash course in connected living and has made massive changes. Small insurance companies are now struggling to survive the onslaught of new requests and most larger firms may need to downsize to make it through these stressful economic times. In this climate of uncertainty, AI will be one of the key factors that will help winners survive. Until recent times, the insurance industry has only used AI in minimal ways. But there are several processes that could be improved drastically using AI.
1. Marketing and sales:
AI technologies can be used to price insurance policies more relevantly and competitively. It can be used to recommend the most beneficial products to their customers. Insurers can customize the price of their products based on individual needs and lifestyles so that their customers are happy to pay only for the coverage they need. This heightens the appeal of insurance to a wider audience while attracting some newer customers.
2. Risk management:
Neural networks of AI can be used to red flag fraud patterns and minimize fraudulent claims. AI can also be used to improve actuarial models and risks that could lead to working out more profitable products.
Chatbots can be developed to understand and answer the bulk of customer queries over chat, phone calls, and email. This is especially helpful during situations like the pandemic where customers and insurers are unable to meet with each other. This can free up significant resources and time for the insurers that can be used in more profitable activities.
Read our white paper: How can your business use AI to achieve higher profits now?
What are the benefits of AI in the insurance industry?
1. Efficient process:
Currently, we are witnessing the first wave of tangible opportunities. The automation provided by AI is offering insurers reduced costing along with more efficient processes. The work dividends form the first wave of benefits. Monotonous, low-level, hazardous, and long-drawn-out tasks are taken over by machines freeing humans to do the high-level and more productive tasks. It also ensures efficiency without the margin of human error.
2. Accurately measured and priced data:
The role of underwriters is changing as AI is set to re-engineer and amplify insurance underwriting. Powered by the disruptive growth of data, AI has the potential to help underwriters analyze vast amounts of information, locate red flags, and help them make more accurate decisions. While we are not expecting to eliminate human underwriters, working alongside AI systems will ensure that all risks are accurately measured and priced.
Read more: 6 Ways Artificial Intelligence Is Driving Decision Making
3. Claims processing made easy:
Claims processing has long been a pain-point for the insurance industry. Managing claims requires a significant manual effort right from document processing to flagging potential fraud. Restricted movement during the COID-19 pandemic makes this task especially difficult. AI can be used to automate document processing. It can scan complex forms quickly and accurately. The insurance company can cut its claims processing time from weeks to just a matter of minutes. AI can help ensure that rejection of any claim is based on solid reasons. This way, insurance companies can drive cost efficiencies by reducing the number of denials that prevent claimants from going for appeals which insurance companies may ultimately have to settle.
Top 3 primary use cases for AI in the insurance industry
The advent of AI represents a quantum leap in how insurance is bought and sold, and how customers are served. Also, it is creating opportunities for insurance companies to affix their leadership positions within the industry.
Here are five primary use cases. If beginners can use this approach to disrupt the old guard, established firms can stave off new competitors and differentiate themselves from conventional foes.
Use Case 1: Always-on customer service
Insurance companies are expected to meet the customer’s expectations themselves. Gone are the days when we companies used to delegate customer service to brokers or agents. Customers expect to reach their insurance providers through any channel-like website, email, mobile app, voice call, chat, social media, etc. It’s become mandatory for insurance providers to possess multi-channel capabilities to handle queries and attend service requests. This is where AI comes to the rescue enabling insurance firms to be on the job 24/7. Always-on, multi-channel service available through chatbots, and customized interactive tools will be your secret sauce to exemplary customer service.
Read more: How AI is Redefining the Future of Customer Service
Use Case 2: Automate processes that are difficult to automate
Insurance companies employ a large workforce to manually perform operational processes. Variations in products, state-specific rules, and lack of adoptions of standards across the value chain previously made it harder to automate the process. With AI, it is now possible to predict and continuously improve the process by leveraging ML thus automating the processes effectively. By combining RPA tools with cognitive technologies, insurance companies can automate processes such as customer service requests, endorsements, and claims-processing, and provide a faster turn-around time.
Use Case 3: Continually improve the value from data
Predictive models help insurance companies determine business-critical aspects such as the maximum possible loss, probability, and pricing. However, as the companies innovate products, reach out to newer customer segments, and address new risks, these predictive models quickly get outdated making it difficult to keep up with changes. AI makes it possible to provide a feedback loop for machines to learn and adapt to ever-changing insurance business needs.
Read more: How Blockchain Enables the Insurance Industry to Tackle Data Challenges
Must-have AI technologies for the insurance industry
AI has become the cornerstone of digital transformation for the insurance industry. Leveraging AI technologies can help insurance companies address various issues that they may encounter. These are some must-have AI technologies in the insurance industry:
1. Image analytics
Insurance companies must carry out inspections to validate their decisions based on actual facts. This helps them spot any existing or potential risks and support their customers in risk management. This can be very time-consuming. The use of AI focuses on the reduction of inspection time and increases the surveyor’s productivity. It can be applied in property and casualty insurance to analyze the images of cars at the accident scene, determine the parameters, and assess replacement costs.
Advanced image analytics enables quick analysis of photos to determine parameters crucial from the perspective of life insurance. These parameters enable insurers to decide whether medical underwriting is required or not and provide an instant quote and formulate policies.
2. Internet of Things
IoT allows insurance companies to cross-sell to existing customers. They could offer discounted insurance to existing customers. There are several IoT backed devices that can detect and alert a customer when there is an issue within their home or commercial property. Integrating IoT with AI, insurance companies can offer a far superior service and enhance the customer experience.
3. Machine Learning in underwriting
The automated process eliminates the tedious and error-prone job of dealing with unstructured documents and extracts information from them to make business decisions. AI, ML, and Deep Learning can help in extracting such information, aligning it to common vocabulary, and making that information accessible through virtual assistants or search engines. This way underwriting now becomes an automated process that lasts just a few seconds.
4. End to end automation
AI helps insurers automate complex processes, end to end. Using RPA, you can tackle simpler and repeatable tasks. For example, the claims assessment process can be automated to enable the assessor to receive evidence through more advanced AI-based techniques.
Insurance companies receive data from brokers in a variety of formats and require many people to convert the data to a standard format. AI can map this data accurately allowing insurers to reduce inefficiencies in their processes. It can also improve data quality by detecting gaps and addressing those gaps in the incoming data.
Read more: Scalable Benefits of RPA in Banking, Insurance, and Logistics
5. Machine Learning for price sophistication
Price optimization techniques with the help of ML and GLMs help insurance companies to understand their customers, allows them to balance capacity with demand, and drive better conversion rates.
6. Connected claims processing
Advanced algorithms can help insurance claims to be automated which allows insurers to attain high levels of accuracy and efficiency. Data-capture technologies can replace manual methods. Evaluation of the validity of a claim is also made much simpler.
Read more: 5 Steps to Gain Business Value with AI Adoption
Are you ready to ride on the wave of AI?
Rapid advances in AI will lead to disruptive changes in the insurance industry. The winners in AI-based insurance will be those who harness the power of new technologies. Most importantly those companies who do not view disruptive technologies as a threat to their current business will thrive in the insurance industry. Get started on making sure you are one of them! Contact us to adopt the power of AI into your insurance business.