The insurance industry is one of the most important industries guarding the well-being of the people you serve. However, in this current environment, there are many challenges to overcome for yourself and your clients.
- Remaining cost-effective in shifting economies
- Maintaining and edge against rising competition
- Responding to changes in customer requirements
- Preserving assets during unforeseen natural disasters
- Staying secure amidst everchanging cybersecurity threats
These are just a few of the challenges facing Property & Casualty insurance providers looking to stay increasingly agile, responsive and strong.
To better navigate current potentialities, emerging technologies like artificial intelligence (AI) and machine learning (ML) are helping insurance carriers provide better services for their customers while setting up their businesses for future success. Here is how AI and ML work in Property & Casualty Insurance.
How Do AI and ML Work?
AI uses intelligent machines to simulate human thinking in order to solve problems that are too big for the human mind to grasp. ML takes the data insights uncovered by AI and leverages them to learn without direct programming. These combined improvement capabilities help P&C insurance companies to become more competitive, productive and accurate.
Both AI and ML can be categorized under the umbrella of Intelligent Process Automation (IPA), which describes the use of advanced technologies to manage, automate, and integrate digital processes in daily workflows. Carriers use AI and ML to address complexity issues within different areas of operations, such as policy writing. Advanced intelligence enhances security by detecting when applicant information may be fraudulent.
Other advanced technologies include:
Digital Process Automation
Digital Process Automation (DPA) is a digital technology that can automate one or more tasks in a business process. Many Property & Casualty Insurance Providers use DPA as a way to invoice and process payments. With DPA, processes are partially automated, so it still requires some form of human interaction. Benefits to DPA include:
- Reduced Operational Costs
- Better Customer Service
- Increased Employee Satisfaction
- Better Compliance and Security
Artificial Intelligence
The core function of AI and ML is to replicate human cognition and perform tasks the way a human would with more accuracy and efficiency. Because humans are independent, action-oriented beings, AI and ML capabilities are autonomous and self-improving. AI can handle both complex and repetitive tasks. Some of the benefits to AI include:
- Automation
- Minimize Errors
- Increase Business Efficacy and Efficiency
- Provides Smart Decision Making
- Can Solve Complex Problems
- Can Handle Repetitive/ Mundane Tasks
- Provides In-Depth Research and Analytics
Robotic Process Automation
Robotic Process Automation (RPA) is the technology that builds, manages, and deploys software robots. These robots mimic human interactions with digital systems, software, and customers. These robots can understand processes like navigating systems, understanding what’s on a screen, completing keystrokes, extracting data, and more. These robots can complete a wide range of functions and services. Benefits to RPA include:
- Scalability
- Adaptable to Workflow Changes
- Highly Accurate
- Increased Productivity
- Better Employee Engagement
How Insurance Carriers Use AI
AI is a powerful tool that can impact the insurance industry in many ways. Insurance companies use AI to assist with data migration, claims processing, underwriting, fraud detection, and customer service. For instance, to improve customer service, many providers are investing in virtual assistants such as Chatbots. Chatbots are not AI directly, however, they utilize the power of AI and they represent a simple example to implement in any customer service department that has the potential to drastically improve the communication with customers, the automation of simple requests/ inquiries, and the proper funneling of customers to human representatives when needed.
How Insurance Providers Use ML
A good example of ML implementation among Insurance Providers is the addition of Machine Learning to predict premium prices and losses from their policies. Detecting potential risks early on in the underwriting process allows insurance to make better use of an underwriter’s time. Additionally, improving this process using ML gives insurance companies a huge competitive advantage by providing better policies and saving them money.
Benefits of AI and ML for Insurance Teams
AI helps humans and businesses pull insights from a vast amount of structured and unstructured data sources to implement intelligent solutions that save insurance providers time, money, while improving service for customers. When looking for a cost-effective way to elevate business operations and customer care, insurance companies should consider AI and ML because of the value these solutions deliver for the effort.
Partner With an Industry Expert
AI and ML technologies are becoming increasingly integrated with the insurance industry, particularly in the property & casualty medium. If you want to experience the benefits for yourself, getting started is easy. Talk with OZ, an advanced digital solutions provider specializing in developing custom solutions for the industry.
Our team of experts will work with your business to design the AI and ML services that fit your business model and needs. If you would like to learn more about OZ or any of the types of advanced digital services, don’t hesitate to reach out to learn more.
