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November 22nd , 2024

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TRENDS IN THE INSURANCE INDUSTRY

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New Models and Customized Products

The digital economy will increase the relevance of usage-based, on-demand, and 'all-in-one' insurance lifestyle solutions. Customers will choose individualized insurance coverage over the existing one-size-fits-all options.


Today, insurers lose more than 80% of their premiums due to distribution expenses. Digital models will render intermediaries in the insurance value chain, which are distinguished by their reliance on human effort, obsolete.


In the long run, flexible coverage alternatives, microinsurance, and peer-to-peer insurance will become realistic possibilities. Reinsurers will give risk capital to digital companies directly, and legal frameworks will allow for shorter value chains.

The insurer-insured relationship will be reimagined via lifestyle applications. As they integrate data from numerous sources, Application Programming Interfaces (APIs) will enable the creation of insights-driven products. A deeper knowledge of client habits will result in more accurate risk assessments, tailored premiums and value on a long-term basis for a better customer experience and brand loyalty, as well as fewer fraudulent claims.

AI and Automation for Claims Processing

Robotic Process Automation (RPA) and artificial intelligence (AI) will take center stage in insurance, owing to increased data channels, improved data processing capabilities, and developments in AI algorithms. Lemonade, for example, uses AI and behavioral economics as essential parts in its business strategy. While artificial intelligence removes brokers and paperwork, its behavioral economics skills limit fraud, resulting in reduced time, effort, and expenses.


Tyche, another InsurTech startup, has employed an AI-infused claim likelihood model in underwriting to precisely evaluate risks and increase profitability. Bots will become commonplace in both the front and back offices to automate policy servicing and claims administration in order to provide faster and more customized client care. For example, the virtual assistant of a major auto insurance in the United States responds to consumer inquiries about plans and payments. Jim, Lemonade's claims bot, examines and pays out property claims in three seconds or less. SPIXII, an automated insurance agent, engages with consumers using a mobile app and other communication platforms to assist in the acquisition of the appropriate policies.


Artificial intelligence and automation will have a significant influence on and enhance business results in areas such as customer experience, cost optimization, operational efficiency, market competitiveness, and emerging business models.

Advanced Analytics and Proactivity

Premiums will become increasingly tailored as new sources of tech-enabled data such as the Internet of Things, mobile-enabled InsurTech apps, and wearables become available. With the connected devices market expected to develop rapidly over the next five years, Property and Casualty (P&C) insurers will be able to extract real-time and precise data on individual customers' loss risk. This will enable them to respond proactively with quick and highly tailored solutions.


A relationship between a European insurance firm and Panasonic is an excellent example. Panasonic's sensors provide smartphone notifications to both the insurer and its consumers, allowing for speedy and informed problem resolution.

Drone and imaging technologies will make it easier for insurers to collect high-resolution photographs for remote and accurate property estimate and analysis. A few major car insurers in the United States used drones to inspect the damage caused by Hurricane Harvey. Using drones, an Australian insurance firm was able to resolve 90% of large damage claims in 90 days. 

Furthermore, insights will be derived from data set interactions in order to provide greater granularity in individual risk profiles and safeguard insurers from new risk exposures. A U.K.-based insurance firm, for example, uses predictive analytics to simulate complicated consumer behavior, improve price accuracy, and drastically cut decision time. A U.S. insurer uses a telematics device to send real-time feedback to drivers in order to encourage safe driving. Customers have saved up to 40% on their purchases as a result of this.

To dynamically segment consumers and needs, model behaviors and find exceptions, change policy rates, improve company strategies, and uncover new growth prospects, advanced analytics will be used. Automation, artificial intelligence, and machine learning may be used to turn insurers into active risk managers.








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