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Use Artificial Intelligence and Machine Learning Risk Mitigation to Drive Short, Mid and Long Term Planning for Your Reinsurance Team

June 20, 2021

Key Takeaways In This Blog:

  • Integrating AI and ML boosts efficiency in mitigation planning, enhancing security and providing better customer experiences. This translates to a better bottom line.
  • Automating labor-intensive processes with AI and ML allows your team to mitigate risk while also delivering better on critical growth initiatives.
  • AI and ML can spot patterns and anomalies in vast data sets to alert you of areas for growth and adjust strategies for mitigation planning and to pinpoint where to best invest valuable resources.

More insurance providers are now relying on digital solutions and innovative technologies to stay competitive in the current highly volatile marketplace. By integrating Artificial Intelligence (AI) and Machine Learning (ML) into core insurance operations, providers improve their operational efficiency, provide better solutions and build more precise underwriting models. 

What are these technologies and how can your company leverage AI and ML to mitigate risks, satisfy your customers, and ultimately improve your bottom line?

What Are AI and ML?

Artificial Intelligence (AI) refers to the simulation of human intelligence and discernment in machines to do tasks usually done by humans. The machines are programmed to think like humans and mimic human actions such as learning and problem-solving.

Machine Learning (ML) is a type of Artificial Intelligence (AI) that allows self-learning from data for software applications to predict outcomes without human intervention. ML is used to build algorithms that receive input data and utilize statistical analysis to predict the output based on available data.

Insurance Processes That Benefit from Machine Learning Capabilities

The benefits of implementing AI into insurance processes are immense. Apart from time and cost-saving benefits, these technologies can help providers improve Customer Experience and increase their profitability thanks to more accurate customer pricing and reduced fraudulent claims. 

These processes rely on neural networks in which multiple layers of processing are used to extract data, producing progressively higher levels of learning capability.

The following insurance processes can significantly benefit from smart digital technologies’ ability to pull from substantial data sources:

1. Underwriting

In the era of diverse and constantly evolving risks, AI combined with deep learning can help insurance providers streamline their underwriting process and identify risks that can impact their business. AI applications can aggregate large data sets in different formats and apply preset identifiers and models to generate results that human underwriters use to make informed decisions. Additionally, AI and big data analytics help expand the range of data sources available to underwriters, leading to better evaluations of risks. Some of the common uses of AI in underwriting include:

  • Reducing the number of tasks: AI helps in the processing of underwriting submissions, including extraction of information from PDFs, printed documents, emails, thus reducing the work underwriters need to do by hand
  • Making informed decisions: Making risk-prone decisions by analyzing submissions and the related risk data.
  • Submission assignment and triaging: AI’s optimizing and forecasting technologies can help assign specific submissions to the appropriate underwriter with the right skills and training.
  • Evaluation of risk profiles: the Intelligent Automation tools can shift through all kinds of structured and unstructured data and aggregate relevant information for underwriters to use.

2. Claims Management

With thousands of claims, customer queries, and massive amounts of diverse data to manage daily, claims processing undertaken by humans is prone to many errors that creep in due to boredom, lack of focus, and fatigue. By investing in AI and ML-enabled technologies, insurance companies can automate most claim processing tasks for faster claim support to loyal customers with no error margin. AI-powered automated claim support can also liberate insurance companies from costly fraudulent claims by identifying data patterns in claim reports and ascertain if the claims fit established standards and regulations. This not only allows an almost error-free process but also improves it as the AI-powered automated claim support learns and adjusts accordingly over time. Insurers can achieve better claims management by using intelligent technologies in the following ways:

  • Automate claims and damage evaluation
  • Enable real-time question-and-answer services for improved customer experiences
  • Automate fraud detections that utilize enriched data analytics
  • Predict claim volume patterns and plan accordingly
  • Augment loss analysis

3. Customer Service

AI is transforming the quality of customer service interaction. It can grow with your client base, easily scaling and serving multiple customers simultaneously 24/7/365. Additionally, it reduces handling time. When combined with ML, AI learns and adapts, providing proactive and client-specific support. It also authenticates customer identity, easily tracking performance while focusing on and solving complex data-driven problems.

Combining smart technologies with human ingenuity across customer service efforts can be one way to effectively solve complex challenges, develop new products, and create new solutions. That is because, though they do not replace humans, they allow humans more time and bandwidth to do other things that help the business even further.

In a 2021 report by SEMrush, 54% of executives say implementing AI in their workplace increased productivity. 79% said AI will make their jobs simpler and more efficient. In an industry where complexity is a daily occurrence, this can come as a relief. Chatbots (that use AI to optimize efficiency) offer your clients 24-hour service (64%), giving instant responses to inquiries (55%), and answering simple questions (55%).

Additionally, AI and ML-powered technologies help insurers improve their team’s effectiveness by scanning through massive amounts of raw data from research trends. 

Key Takeaway: AI and ML See Things Beyond Human Ability to Grasp and Allow Your Teams to Do More

The combined impact of using AI and ML is helping Property and Casualty insurance companies evolve with their customers and grow in relevance by providing better insurance needs. Both of these technologies detect anomalies and trends and can learn how to respond to enhance the risk management strategies of your company.

Integrating smart technologies into your digital processes is something OZ specializes in by providing solutions that will allow you to achieve personalized policies and underwriting efficiency, speedier and more accurate claims management, and greater satisfaction for customers and staff.  Contact us today to learn more.

 

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OZ is a consulting and technology solutions leader focused on increasing customer engagement & operational excellence by leveraging Intelligent Automation.