AI in Risk Management

December 13, 2022

When it comes to risk management, artificial intelligence (AI) is quickly becoming a game-changer. By automating repetitive tasks and analyzing data more efficiently, AI is helping insurance professionals and risk managers free up time to focus on more strategic initiatives.

Understanding What AI Is

Artificial intelligence (AI) technologies are computer systems designed to simulate human thought processes. Often referred to as machine intelligence, this technology is expected to pervade all aspects of our daily lives and could make our economy more efficient and flexible, improve healthcare, and make new kinds of products possible. Artificial intelligence has come a long way since the term was first coined in 1955. Although AI has a reputation for being decades away from realization, AI has actually made enormous strides in recent years. It has now moved beyond the research lab and is being deployed in commercial applications. Technologies associated with AI are now being used in areas such as image recognition, natural language processing, robotics, and data mining.

As with onboarding any new tech, process, or policy, the key is maintaining an open mind. Try to see what it can do to make the job easier, faster, and more equitable for all parties involved. AI can offer speed and efficiency that we’ve only dreamed of in the risk management field, and we’re just now seeing the beginning of it. 

AI is also bringing new challenges to the industry. As AI-powered technologies become more ubiquitous, it’s important to understand how they work and how they can impact the insurance sector. Here’s a closer look at AI in risk management and insurance.

The risk management industry, like many others, is experiencing a tectonic shift in how work is done. AI is enabling insurance professionals and risk managers to optimize their time, resources, and strategy to make more impactful decisions. In the risk management sector, this can come in the form of machine learning algorithms that allow computers to identify patterns and make predictions based on those patterns. This is particularly helpful when it comes to analyzing large data sets and making sense of them quickly. In areas such as insurance claims, decision support systems can look at a wide range of data and make suggestions based on that data. They help the decision-making process become more efficient and accurate by providing information that is relevant to the decision being made.

Benefits of AI in Risk Management

AI can help insurance companies identify risks more quickly and accurately. By automating the tedious and time-consuming tasks of data collection and analysis, AI can help risk managers identify patterns and trends that would otherwise be difficult to spot. By analyzing data more quickly and thoroughly than human underwriters can, it can help identify risks that might be missed. AI can also help price policies more accurately based on a deeper understanding of the risks involved.

AI can process significantly more data and make better conclusions based on that data, so when a human reviews the results, it’s more likely that they’ll be accurate. Computers can help us manage risk and make better decisions when they have access to all relevant data and can process it quickly. AI can help us manage risk and make better decisions by being more inclusive and flexible. Computers don’t get tired, so they can make decisions around the clock.

AI can also help to personalize insurance products and services. By analyzing customer data, AI can help insurers develop products and services that are better tailored to customer needs. This can lead to increased customer satisfaction and loyalty.

In addition, AI can help insurance companies automate claims processing. By using data to flag potential fraud and streamline the claims process, AI can help insurers save time and money. As it continues to learn, which is key to the functionality of AI at its core, it will further be able to help our industry, among others, become more efficient and eliminate bias. 

Challenges of AI in Risk Management

Of course, AI is not without its challenges. As with any new technology, there is a learning curve involved in understanding and utilizing AI effectively. Additionally, AI is not yet able to replicate the human element of risk assessment, which means that there is still a place for experienced insurance professionals in the underwriting process.

The insurance industry is built on trust, and we all know that when something goes wrong, it’s catastrophic. AI has the potential to make a lot of people’s jobs easier, but there’s always a risk that people will take it too far and trust it too much. AI is only as good as the data that goes into it. If the data is inaccurate, then the AI will make inaccurate conclusions based on that data. If the data contains biases or is incomplete, then it will make decisions that are not fully representative of the data available. When there are errors in the AI itself, it might make the same mistakes over and over again without being corrected. If it is not properly monitored and managed, it might make the same mistakes over and over again without being corrected.

There exists the concern many share that AI presents a situation where we are automating our own jobs away. While this is true in some fields, it shouldn’t have a profound effect on our vertical. According to Risk Management Magazine, “For risk management to be successful, it is imperative that human intuition and input be the guiding force when it comes to decision making. Technology is simply the vehicle that allows for increased visibility and agility. Therefore, to overcome this hurdle, organizations need to lay bare this fact and reinforce it throughout onboarding so that they can overcome any cynicism and drive optimal buy-in throughout the workforce.”

Bottom Line

AI is coming, and it’s coming fast. It’s not just for tech companies anymore; it’s impacting various industries across the board. The risk management industry is no exception, and AI is poised to transform this field. Now, that’s not to say that AI will completely replace risk management professionals. In fact, it’ll likely have the opposite effect: it’ll allow professionals more time to do strategic work, while computers do the grunt work. This can only lead to better results and a more efficient industry.

If you’re contemplating using an AI tool to help your risk management process, do your homework. Make sure whatever you’re contemplating using is bias-free. Ask around. Look for reviews. Call current customers. Analyze for bias as this can be the biggest issue facing any AI tool; you want to know the code it’s based on is free of any preconceived notions so it can do its best work for you and your business. 

myCOI uses OCR and industry-leading knowledge you can’t find anywhere else to analyze certificates of insurance (COIs) to make your compliance piece simpler, faster, and more accurate. There comes a point where human data analysis needs to be handed off to computers; if you’re managing just a few COIs, that process is fine to do manually, but if you’re looking at tens or hundreds of COIs on a regular basis, automating that process needs to be a consideration of yours. Choose the partner who pioneered the space — myCOI makes it easy. Book your demo today! You won’t regret it. 

Previous Page Next Page
This field is for validation purposes and should be left unchanged.

Search by Category

Can You Spot a Fraudulent COI? It’s Harder Than You Think.
ACORD 27 Form
You Must Verify Insurance Compliance More Than Once a Year
Contractor Proof of Insurance: Why It’s Important To Get It
Commercial Insurance Certificat: Everything You Need To Know
Subcontractor Insurance Requirements & Types of Insurance Needed
LLC Certificate of Insurance
General Liability Certificate of Insurance