The Property & Casualty Insurance (P&C) industry is a rigorous and highly technical discipline. Mistakes in writing insurance policies can cost insurance providers millions of dollars. It is always a fine balance between risk mitigation and providing quality coverage for customers. To mitigate this risk, many insurance providers are implementing Intelligent Process Automation (IPA) to better protect their businesses and their customers.
Intelligent Process Automation is giving insurance companies a sharper edge, and many are using these valuable capabilities to their competitive advantage.
With IPA, insurance providers can automate manual tasks, detect potential fraud, and improve customer support. They can also invoice and process payments, among other benefits, such as policy underwriting and claims management. By turning to automation, P&C teams are eliminating the potential for errors that creep in with manual processes.
Intelligent Process Automation uses advanced technologies to manage, automate, and integrate digital processes. There are three primary technologies in IPA. These include:
Digital Process Automation (DPA): DPA’s primary use is to optimize workflow. It can automate tasks that normally require human interaction. These include functions in management, risk, policy, benefits, product, marketing, sales, accounting, IT, and HR. Every business function and departmental workflow can be improved with DPA, and have a positive impact on the overall business of an insurance carrier. These automated tasks can also extend to help external users, such as customers, vendors, and stakeholders, providing a better overall user experience across many touchpoints.
Robotic Process Automation (RPA): Robotic software emulates human interactions with digital processes. RPA is the process of building, deploying, and managing bots that streamline and automate functions within an insurance carrier. These software robots can perform a wide variety of tasks and functions at a faster and more consistent rate than a human. And unlike their human counterparts, they do not take breaks, get tired, or lose focus due to the repetitiveness of a task. They remain consistent and consistency is key in certain areas of the business. By pairing RPA with Machine Learning (ML), it has the potential to learn and develop over time becoming more efficient.
Artificial Intelligence (AI): AI adds an entire level of thinking to IPA. Unlike DPA and RPA, which emulate human tasks, AI can perform tasks most humans could not easily do. These include recognizing patterns of incredibly large unstructured data sets and summarizing these patterns into valuable insights which in return allow humans to make accurate decisions for the future, based on those insights. When pairing AI with its subset ML, machines can automatically learn from data without the need for explicit programming.
The main purpose of IPA is to allow organizations to automate processes that involve unstructured content. Unstructured content can be in the form of images, texts, raw data, etc. IPA will take unstructured content and make it intuitively structured by using existing machine learning models and proven artificial intelligence programming. Without the need for pre-programmed code or extensive training on large data sets that are out of reach for over 95% of enterprises.
Although the banking and financial industries began adopting IPA technology a long time ago, the insurance industry has been much slower at embracing it. Only recently have insurance companies started launching pilot automation programs that include both RPA and Intelligent Automation. The future impact of these technologies on the insurance industry is expected to be massive.
Areas in insurance where process automation can help include:
Claims Processing: Claims processing is often a highly manual and time-consuming process. Because this process is so labor-intensive, it brings with it a higher potential for human error. By implementing RPA and Machine Learning (ML), insurance companies can optimize the claims processing workflow, including claims intake, assessment, and settlement. This can help minimize friction and cost.
Policy Management: Another common use for Intelligent Automation in insurance is with policy management. Through automation, policy-holders can submit updates to their policy without human assistance. ML can even accurately extract information for voice messages. It can also do things like process run-loss reports, provide analysis for statements, and explain insurability.
Regulatory Compliance: Due to the nature of the business, the insurance industry is subject to a hefty amount of stringent regulations. Intelligent Automation can help companies both maintain and improve their compliance standards. Carriers are beginning to automate compliance processes such as compliance checking, name screening, client research, and validation, and produce regulatory reports.
Underwriting: IPA can assist in underwriting by gathering and assessing data from different sources, then using that information to identify and then mitigate the risks associated with a given policy. These include, but are not limited to, health risks, financial limits, creditworthiness, and duplicate policies. What was once a weeks-long process can be significantly reduced with IPA.
Intelligent Automation allows for a versatile, quick, and accurate service that positively impacts the bottom line and enables better customer service. Industry leaders are adopting IPA at a record pace. This is the perfect time to bring IPA into your organization. However, to reap the benefits of IPA, one must partner with the right automation expert.
At OZ, we specialize in providing highly advanced Intelligent Automation services to businesses, including process automation, AI, analytics, enterprise application integrations, and digital solutions. We will work with your business to find the solution that best fits your needs. If you would like to learn more, feel free to contact us today!
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