How to Align the Business and Operating Models of an Insurance Company
The business environment in the Insurance Industry is changing at a rapid pace with the democratization of exponential technologies like Artificial Intelligence, Automation, APIs, High Performance Computing, and Big Data. These technologies have become a business imperative making their way into enterprise roadmaps to give the insurance companies a competitive edge against their regular competition and as well as the new pure digital entrants. These technologies by themselves are disruptive and their combined synergistic effect is more than their individual effect on a Cognitive Insurance Enterprise.
There is a lot of data available these days in form of open data, vended data as well as enterprise dark data. The first step is to clearly understand the roadmap initiatives and see where big data can help optimize the key operational business processes, uncover new sources of revenue streams (customer, product, operational, and market revenue), mitigate risk (security and compliance), and create a unique customer experience over your competitors. Creating Proof-of-Concept initiatives is key in showing the C-Suite the value addition of these data sources. After the stakeholders buy-in, an application can be built to deliver the business users the insights derived from this data to enhance their decision making or even automating the business decisions. The insights generated from embedding web analytics service on top of the business platforms help product, marketing, and customer success teams craft exceptional digital experiences that convert and retain users.
Technologies have become a business imperative making their way into enterprise roadmaps to give the insurance companies a competitive edge against their regular competition and as well as the new pure digital entrants
Artificial Intelligence-based models are a very crucial and integral part of the underwriting, customer service, claims, marketing, and finance departments of an insurance company. Artificial Intelligence-based techniques like Natural Language Processing, Reinforcement Learning, and Image Analytics have already proved their value in production improving the quality of decision making with each iteration. There are cases where new disciplines are emerging combining the innovations in spatial science, artificial intelligence methods in machine learning (e.g., deep learning), data mining, and high-performance computing to extract knowledge from spatial big data in a cost-effective manner. These types of interdisciplinary trends are proving to be a great value addition for insurance companies. For example, An Assessment of Building Damage caused by a hazard can be performed using Satellite Imagery and Convolutional Neural Networks.
High Performance Computing infrastructure
The competitive, regulatory and financial factors push an enterprise towards creating a cost effective interoperablehigh-performance computing infrastructure that can handle big data and computationally intensive algorithms required to provide insights in a timely manner to the business users.High Performance Computing infrastructure gives an insurance enterprise the ability to run multiple scenarios and thousands of AI models in minutes thereby empowering data scientists to solve problems and create solutions in a timely manner.
Application Programming Interface (API)
APIs have become a crucial part of the digital transformation of any company. APIs enable unlocking the data to build a foundation for the flow of data across an enterprise. The Machine learning models packaged in APIs derive insights from the data APIs through integration. API connectivity helps integrating several systems to automate a business process which might require several connection points with the enterprise systems. This is very crucial in intelligent process automation where AI, Big Data, and workflow orchestration come together to replace the human bottlenecks.
Automation in an enterprise can be at a task level, department level, or at the business operation level. The advances in robotic process automation are creating a path for end-to-end automation at the business process level like Insurance claims processing. Automation has enabled the ability to sense, respond, and adapt to changes in market dynamics, employees, and customers in real-time. There is a long way ahead to create autonomous systems that operate within an enterprise, but it is very essential to retrain current employees in these technologies to create a win-win situation.
All these technologies in orchestration help align the business and operating models of an insurance company in its transformation into a Cognitive Enterprise built with scale in mind.
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