--The cloud, open APIs and a microservices approach to IT architecture allow for experimentation and the mixing and matching of apps and services into new and improved business solutions.
--Improvements in AI and predictive analytics allow for much more sophisticated insights and smoother interactions with clients.
--No-code or low-code platforms empower insurers to build custom applications and solutions without the need for extensive programming expertise.
--Self-sufficiency enables traditional insurers to position themselves as agile, customer-centric organizations capable of delivering value and staying ahead in a dynamic insurance landscape. It begins with reducing reliance on third-party vendors.
The rise of innovative technologies such as no-code tools, artificial intelligence-powered automation and predictive analytics has helped transform the ways insurers operate and interact with customers.
The solutions leveraged by the industry based on these technologies have helped streamline insurance processes, reduce insurers’ overhead and increase profitability. However, traditional insurers have become dependent on those that offer this kind of technology – a dependence that can induce communication lags, lower productivity and decrease efficiency in the event of a back-end issue.
Thanks to the digital revolution, insurance-related tech is now more accessible, more intuitive and easier to implement than ever. These improvements are being driven by user-friendly interfaces, cloud computing, software-as-a-service (SaaS) models and open application programming interfaces (APIs), among other innovative technologies.
By strategically implementing the following tools and solutions, traditional insurers can achieve a level of self-sufficiency that may have until now eluded them in this digital age.
The Cloud + APIs + Microservices
Cloud platforms give insurers access to software applications, storage and computing power without the need for significant upfront investments in infrastructure, which allows them to leverage advanced technologies seamlessly and remain competitive. By way of these cloud platforms, SaaS providers – which offer software applications in the cloud – enable insurers to access and use sophisticated solutions that are resilient and scalable in a convenient commercial model that enables a best-of-breed approach and can drive innovation by experimentation.
The “microservices” architectural approach creates software applications as a collection of small, independent and loosely coupled services and is used by both SaaS providers and modern IT teams. This approach furthers the “composable business” approach by introducing new, discrete services, allowing for independent service lifecycles and upgrades and enabling the mixing and matching of apps and services into new and improved business solutions.
Finally, open APIs – used to expose the functionalities of individual microservices or SaaS solutions in a standardized way – allow insurers to connect and integrate a wide variety of useful systems and tools. This interoperability lets insurers effortlessly integrate new solutions with existing technology and opens a full ecosystem of tools and best practices to orchestrate, manage, monitor and control the composed solutions.
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AI tools provide insurers with automated decision-making capabilities and intelligent data processing, which in turn lets them maximize their data to streamline underwriting processes, assess risks and enhance fraud detection. It’s for good reason that 49% of insurance executives say AI has helped them operate more efficiently.
Natural language processing (NLP) chatbots and other AI-powered virtual assistants, for instance, improve customer service, streamline inquiries and help resolve issues promptly. Computer vision, another AI-powered solution, automates data extraction from documents, streamlines claims processing through damage assessment, identifies fraud patterns, enhances underwriting accuracy using visual data and facilitates virtual inspections for customer support. By leveraging computer vision and keen AI-powered customer service tools, insurers can streamline operations, reduce costs, improve efficiency and enhance customer experiences.
Considering the vast amounts of data that AI tools can analyze simultaneously, insurers can use them to gain valuable insights into accurate pricing, personalized offerings and efficient claims management – these automations across the value chain allow insurers to focus on more complex and strategic activities and enhance users’ satisfaction and experience, both internally and externally.
Additionally, AI plays a significant role in predictive analytics, which use historical data and statistical algorithms to make predictions about future events or outcomes. AI enables these analytic solutions to parse large volumes of data, identify patterns and make accurate predictions.
Predictive analytics help insurers make data-driven decisions, identify risks and optimize their operations – advantages that have driven higher sales for 60% of insurers thus far and reduced gnawing expenses for 67% of them.
These insights give insurers the necessary information to anticipate customer needs, identify fraudulent activities and accurately assess risks – all in real time. With them, insurers can minimize financial loss, enhance customer satisfaction and improve overall profitability.
While the use of no-code platforms still require reliance on IT and developer teams, and don’t necessarily exemplify the flexibility and agility of the end solution, no-code or low-code platforms are still uniquely able to empower insurers to build custom applications and solutions without the need for extensive programming expertise. In fact, these tools are estimated to account for 65% of application development activity by 2024.
Insurers can use these tools to create intuitive interfaces, automate workflows and develop digital solutions tailored to specific processes across various departments – claims management, policy administration, customer relationships and more. Importantly, no-code tools enable insurers to design and adapt these systems quickly to meet changing industry expectations on their own accord.
See also: Is Going Digital Really THAT Important?
When it comes to pursuing self-sufficiency, there is a case to be made for “building” solutions in-house, rather than buying. Indeed, reliance on external vendors isn’t necessarily in line with a self-sufficient ethos. But the work required to front an in-house solution can be costly, time-consuming and difficult – it’s easier said than done to build a finished product that fits seamlessly into preexisting workflows and product road maps.
Rather, to gain real self-sufficiency without breaking the bank or stretching developers thin, insurers would do well to explore specialized solutions (or point solutions) – those that are highly configurable by non-techs, are open for extensions and use standard modern technologies. This approach ensures minimal vendor lock-in, as well as useful content already out of the box and continuing upgrades.
While each of the digital tools listed above can help improve the various checkpoints in the insurance value chain, their adoption should ultimately fortify their capacity to be more self-sufficient – a key to modern insurers’ success.
Self-sufficiency enables traditional insurers to position themselves as agile, customer-centric organizations capable of delivering value and staying ahead in a dynamic insurance landscape. It can be achieved by first reducing reliance on third-party vendors. This will help insurers reduce external expenses for critical functions, granting them full control when responding to emerging trends, regulatory changes and customer demand.
This flexibility provides insurers with the freedom to develop and implement unique strategies, products and services. Fortunately, there are more than enough AI-powered, low-code and predictive analytics tools insurers can experiment with and ultimately adopt to bolster their internal processes and, subsequently, their bottom lines.