In simple terms, Artificial Intelligence (AI) is a set of computerized tools which have been designed to achieve business objectives. AI can help automate labor intensive processes, leading to increased efficiency, lower costs. Companies are using AI to analyze the data they have on customers to predict their behavior, understand preferences and optimize price and product offerings.
AI has helped in transforming large companies and industries by identifying new avenues of growth and profitability. Being an old and highly regulated industry that insurance is, companies are moving away from the manual, paper based processes to adopting modern technologies. AI technology have made great inroads in different sectors of the insurance industry and are lowering costs while increasing efficiency and improving the customer experience. Slowly but surely, the industry is transforming.
One of the key reason why AI will be crucial is the ever increasing “datafication” of business interactions, private life and public life. AI can be used to effectively understand drivers and trends in the insurance industry. According to Deloitte, AI is helping insurers by predicting risk with greater accuracy, customize products and use enhanced foresight to rapidly deploy new products thus reducing time to market to toe along with market/business agility.
The European insurance sector is the second in the world, accounting for 31.6% of global insurance premiums, behind Asia-Pacific (32.4%) and ahead of North America (30.8%). France, Germany and the United Kingdom are the largest players on the European market. Consulting firm McKinsey estimates a potential annual revenue of $1.1 trillion, if artificial intelligence is fully applied to the insurance industry.
According to a recent report by Bain & Company, the EU region is experiencing an insurance boom, as well as significant digital disruptions. Due to the stiff competition from emerging new players, insurance companies are implementing artificial intelligence (AI) powered tools to stay differentiated. Insurers are using advanced analytics, machine learning and other AI-driven tools to elevate the customer experience and also to compete with agile digital newbies. According to a study by PwC, more than 80 percent of insurance CEOs said AI was already a part of their business model or would be within the next three years.
How are Insurers Adopting AI?
Here are four major areas where insurers are implement AI to improve customer engagement, combat fraud and streamline business processes.
- Fraud Detection:
According to the Association of British Insurers, more than half a million insurance frauds, totaling £1.3 billion, were detected in the UK during 2017, while in the US FBI estimates insurance fraud robs the US insurance industry of a whopping $40 billion a year. Insurers are turning to AI driven predictive analysis and machine-learning tools to identify and flag unusual claims, anomalies, patterns thus potentially helping them to reduce the fraudulent claims to protect the bottomline.
- Customer Profiling & Segmentation:
By automating and applying cognitive intelligence to their processes, insurance companies are leveraging the benefits of profiling. Insurers can unify and derive insights from their internal and external customer data, and develop a comprehensive picture of their customers, such as their insurance needs, interests and life stages, for more effective targeting. Insurers can segment their audience based on these attributes, and use deep learning to predict the conversion rates. With deeper insight, insurers can recommend the relevant products for each customer segment.
- Product & Policy Design
One of the key area insurance companies are using AI is improving their product and policy design. Personalization and providing flexibility in choosing these products is very key where AI powered chat-bots and social media listening play a crucial role in this. By analyzing the massive data collected from different sources, insurers can use machine learning to discover customer trends and interests in real time. These insights are then being used to develop and improve product and policy design.
Additional innovations with AI/ML under the hood has helped Insurance companies to offer Usage-based insurance (UBI) model which gives customers significant cost benefits. To know more about UBI check out my earlier post – UBI, On-demand insurance is gaining momentum!
- Underwriting & Claims Assessment
The process of underwriting is often considered as an art based on personal judgment, but AI technologies have entered into this area of insurance, making it a scientific process. Insurers are now using advanced analytics and machine learning, as well as additional sources such as satellites and the IoT devices, to get a more holistic view. Telematic devices, a wearable technology for auto insurance brings significant benefits by reducing the premium and risk exposure thus being a win-win formula for both Insured and Insurer.
Insurance firms using image processing AI to analyze the extent of the damaged vehicle, which helps them to generate a list of repairable and replaceable parts that were damaged in the accident. Within a few minutes, the assessment and the cost are given to the customer, which they can either accept or reject. If the assessment gets accepted, the payment is made within couple of hours directly to the customer’s bank account. Which also means happy customers thus leading to stickiness which is essential in an industry where customer attrition is significant!
Conclusion:
From fraud detection to underwriting, AI technologies are re-imagining every aspect of insurance industry. By reducing the risks and streamlining processes, it’s helping companies increase efficiency and deliver more personalized products and services. While some insurance companies have started implementing AI, there still remains many companies which are yet to find the right use cases for them. To leap from AI mystery to mastery, practitioners need to bridge the gap in understanding the technology’s inner workings and its business value proposition.
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