The Insurance industry has witnessed a lot of changes in the past decade. As customers demand more personalized services with less time to deliver, the industry has started adjusting its enterprise claims management processes to suit consumer demand and remain competitive.
Insurance companies have begun to rely more on data-driven processes to fine-tune their enterprise claims management processes. With the implementation of data-driven processes comes the need to install systems that collect and analyze data that will drive strategic decisions. The future of the insurance industry lies in the ability to eliminate data silos, ensure the quality of data collected and use advanced data analytics to meet consumer needs.
In this article, we will look at the four ways enterprise claims management will evolve based on advanced analytics.
Ways Enterprise Claims Administration Are Evolving
Enterprise claims administration will evolve more as consumers demand better services and insurers strive to meet their needs, here are four ways this will happen.
Process Automation
While insurance practices before depended on manual processes that often took time to execute, with the advent of new technologies and digitization of insurance processes we will see more prevalence of process automation to augment manual processes that take a lot of time and prevent claims processing. For example, where loss claims usually depended on loss adjusters visiting the site of occurrence and having to collect site data which will be processed and handled by different workers before a loss claim can be paid, we are now seeing the automatic site inspection activities via the deployment of automated drones to get the instant picture of the site of occurrence.
Data collected is automatically transmitted to the data centers where the claims processing will start even before the owner of the insurance policy can file a claim. Automating processes will ensure that the right triggers are set to move along processes that will usually have waited for human intervention, hence saving time and cost.
Predictive Analytics
As insurance evolves with the current demand for lesser time to claims payout, insurance companies are taking the data-driven approach by using enterprise claims management systems. This means that they are collecting more data from their users and using it to predict customer behavior. The ability to foresee a consumer's insurance needs in the future is used to personalize insurance services, detect suspicious behavior in claims management, and hence save money that could have been paid out via false claims or stolen policies.
As a company, understanding the need to have claims management software that can collect quality data, analyze it and present it in such a way that it will enable your company to make strategic decisions is key to surviving the competition and retaining your customers.
Machine Learning & AI
Right now, companies use machine learning algorithms and artificial intelligence to automate simple claims processing using a chatbot. As users seek to receive instant services when they want them, we will see more chatbots and automated backed approvals replacing some claims administration tasks that were usually done manually. Chatbots cannot operate optimally except they have been trained with the right data. Having a claims administration system that collects data and analyzes it will give your company an edge when you want to integrate such a possibility into your business. For example, advanced functionality that is powered by machine learning can be used to process claims that are associated with simple losses that do not have complex layers of analysis. It can review claims, verify policy owners, check for fraud and also authorize a payout. All of this will not be possible except if your company has the right data to rely on.
Preventive Insurance
While most of the insurance processes were usually reactive, the industry is moving toward preventive insurance with the use of telematics and predictive data modeling, companies want to be able to preempt losses and avoid them. Part of preventive insurance is also having the right data to correctly underwrite a policy insurance policy. If data on past behavior is correctly analyzed, you can better predict the likelihood of what the policy insurance holder will do in the future. This gives the insurance policy company a better edge in pricing policies.
Edge Computing
As a company being able to compute data at the point of collection enhances faster decision-making processes, this means that your consumers can get answers when they need them. Edge computing in the insurance industry especially the Claims administration will move the claims processes to the hands of the policyholder, with just a device, a policyholder can impute the incidents as it happens and get instant results without much human interaction. While this may ring bells for the insurer who wants to ensure that the policyholder is not making fraudulent claims, integrating edge computing with other digital technologies like AI and machine learning will ameliorate and reduce such fears.
Aligning Claims Management with Advanced Analytics
The best way for a company to stay competitive is to find out where the future is pointing and align. As an insurance company, your ability to align your company objectives to where the insurance industry is heading as pertains to enterprise claims management administration is the key to staying competitive and relevant in your industry.
