Blockchain and Artificial Intelligence in the Insurance Industry

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Applications of Blockchain And Artificial Intelligence Technologies in The Insurance Industry
Executive Summary
Dwindling traditional profit pools, shifting competitor landscapes, and growing customer expectations are forcing traditional insurance companies to reconsider their business models by integrating digital technologies. One digital technology that promises to reshape the 300-year-old insurance industry in terms of enhancing customer relationships, delivering faster claim payments, reducing operational costs, and gaining competitive advantage is Artificial Intelligence (AI). The growing datafication of nearly all private and public life means that insurance companies have a trove of information to help guide their design of products that better align with customer needs (Deloitte). Given the prominence of data as the new gold, the role of AI in converting big data into actionable business knowledge and insights is key. The cognitive abilities of AI technology are advantageous to insurance companies in terms of developing more accurate customer risk profiles, faster contract processing systems, streamlining payment verification, lowering customer acquisition costs, combating fraudulent claims, and coming up with tailored insurance products.
AI has the potential to improve underwriting processes by conducting an in-depth examination of a broad range of pertinent factors to come up with accurate risk estimates and policy prices. The technology’s ability to assess all pieces of data in a granular and intricate manner means that insurers can develop tailored premiums that address the unique needs of each customer. Besides, AI has the potential to verify all claim details and identify instances of deception in a prompt manner thereby deterring fraudulent claims while also streamlining contract processing (Eling et al.). On the whole, AI has the potential to improve insurer processes of assessing risk, detecting fraud, processing claims, developing product offerings, all while heightening customer satisfaction levels. Another digital technology that is bound to revolutionize the insurance industry is blockchain technology. Unlike the traditional insurance industry where the terms of agreement between the insurer and the customer are regulated by a central decision-making body, the blockchain works according to the rules set by both parties.
The terms of the contract are accessible to all parties and stored in a safe and incontrovertible manner. Moreover, the rules encoded within the blockchain through smart contracts are enforceable automatically without any human involvement. All these features of the digital technology improve accountability, transparency, security, and efficiency in the insurance industry. By eliminating intermediaries in the insurance industry, blockchain technology can enhance insurance value chain through innovating business models that allow for faster development of new products and markets and more effective approaches to risk assessment, insurance agreements, and claims management. On the whole, the application of blockchain technology in the insurance industry will result in elimination of human error, faster processing of insurance claims, reduction in fraudulent claims, fewer operational costs, new business opportunities, heightened customer experiences, and low pricing of insurance products.
Analysis
Artificial Intelligence
While the insurance industry as a whole has been slow in embracing AI, the technology is slowly becoming a common catch phrase among agile insurance companies keen on resolving their insurer pain points, heightening customer satisfaction, and gaining a competitive edge. A recent survey by Deloitte indicates that more insurers are realizing the growing importance of cognitive computing in the insurance industry: ninety-five percent of insurance executives are planning on beginning or continuing their AI investments while another ninety-eight percent hold that cognitive capacities of AI are bound to disrupt the sector (Deloitte). These sentiments are not misplaced given the already demonstrated importance of AI in assessing risks, detecting fraud, reducing human error, improving customer service, and hastening claims processing among pioneer insurers. The insurance industry has historically depended on underwriters to evaluate customers’ insurance risks. This process of accessing the insurance risks is fraught with losses emanating from inaccurate information provided by clients resulting in poor risk assessments on the part of the insurer.
AI has demonstrated to be an effective tool for poring through abstract sources of information including social media postings and SEC filings among other pertinent data sources to improve evaluation of insurance carrier’s potential risk. The ability of AI to thoroughly examine various information sources, that are not easily accessible, and identify highly relevant information has allowed insurance companies to make accurate risk assessments and develop more suitable premiums. Developing appropriate premiums is a critical facet in the insurance industry and therefore the importance of AI in coming up with more individualized exposure models cannot be understated. In addition to the issue of limiting risks and increasing profit margins, customized premiums result in higher customer satisfaction as compared to standard liability policies since clients only pay for coverage they really need (Sk). Moreover, the increased digitization of people’s behavior and activities has resulted in massive and complex data streams, which can be leveraged using AI to provide useful insights for new risk categories.
Another advantage of AI in the insurance industry relates to its cognitive ability to discern patterns that are likely not to be detected through human cognition thereby stopping fraudulent claims. Insurance companies lose billions of dollars every year to fraudsters and an estimated ten percent of overall claims expenditure is spent on fraud related issues. The outdated rule-based systems and human-led data science that most insurers rely on to detect fraudulent insurance claims are ineffective against the intricate schemes hatched by white-collar criminals. AI has demonstrated its ability to determine the veracity of claims asserted by clients and in doing so helping insurers identify fraudulent claims. For instance, if a driver involved in a road accident claims that the slippery conditions brought about by raining adversely affected his braking instance, it is possible for AI to check weather reports in the area and confirm if this was the case (Deloitte). It is then possible for insurers to invalidate the claim if the driver’s report is shown to be false. Lemonade, a New York property and casualty peer to peer insurance, uses AI powered claims analysis to ascertain the genuineness of insurance claims within minutes.
The insurer’s AI system features eighteen anti-fraud algorithms that run image and video analyses to confirm or disprove the details provided by customers. Another application area of AI that relates to the other competencies is that of reducing human error. The distribution chain in processing insurance claims is winding and complex: several human analysts are involved in examining the data between the carrier and the insured. It is not uncommon for human error to be introduced in the manual process and therefore insurance companies have had to contend with the business risk of expensive clerical errors (Eling et al.). For example, in the case of Lemonade, human data scientists would require several days to iterate their analysis of customer claims as opposed to AI which can detect any inconsistencies in the underlying data within a much shorter time. AI can eliminate human error as information is passed from one source to the other as well as reduce the time taken in analyzing claims. Through algorithms, AI bridges the gap between the insurer and the insured while eliminating any errors introduced by human specialists when combing through the details provided by the customer.
AI can quickly analyze the images, text, and historical data in a claim to determine the veracity of the facts, over and above, predict the potential costs involved. Faster and error-free claims processing is a critical aspect of customer service in the insurance industry and therefore the ability of AI to effectively deal with complex insurance claims within a relatively short time is a big advantage for insurers. AI also guarantees fast cycle times in claims adjudication by assuming the painstaking process of damage inspection. Property insurance companies have to regularly assess damage and provide accurate repair cost estimates to customers. Damage estimation is more difficult and time-consuming when the asset in question requires a more wholesome picture than what the human eye can capture (Laurinavicius). There are AI-based claims management systems that can quickly process damage costs using geospatial data, HD video and imagery shot by drones, as well as IoT data sets like object position, pressure, temperature, and more. All these datasets combined with AI algorithms allow for a more accurate and faster appraisal of insurance claims.
For instance, Tokio Marine, a Japanese auto insurance company, uses an AI-based computer vision with advanced image recognition for examining and assessing damaged vehic...