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Artificial Intelligence In Risk Management

Risk management is an ongoing challenge for the insurance industry. The ever-evolving environment, coupled with an ever-changing regulatory playing field, can be quite a struggle for risk managers and claims professionals alike.

Thankfully, artificial intelligence (AI) may finally offer some relief from the stress of managing risks. AI can gather data from a variety of sources and process it to predict future occurrences or decide on how to react to them in real time.

It provides excellent insights that allow for more effective decision making in all spheres of risk management — compliance, claim settlement negotiations, pricing development, etc.

What Is Artificial Intelligence In Risk Management

Artificial intelligence (AI) is a critical technology that suggests the ability of computers to mimic human cognitive functions. These include learning and problem-solving, planning, decision-making, perception, and language processing.

Often associated with robotics and machine learning, AI is gradually becoming a popular buzzword in many fields — from healthcare to finance.


Risk management is arguably the most significant application of AI in the financial services industry, as estimates reveal that merchant losses from fraud assaults amount to an average of 1.5% of their yearly revenue.

With regards to risk management, AI’s primary objective is to shift the focus from rules-based programming (e.g., black and white decision trees) to machine learning — an advanced form of data analysis that allows for a more “human” approach in dealing with risks. Essentially, artificial intelligence suggests applying some of our most powerful abilities.

Importance Of Artificial Intelligence In Risk Management

The use of artificial intelligence in risk management could provide an increase in productivity and improve customer service. At the same time, there are many other factors to consider as well — such as the risk of cyberattacks, increased fraud and increased cost of insurance.

What decisions companies make regarding artificial intelligence in risk management ultimately depends on their unique business needs and goals.

Benefits Of Artificial Intelligence In Risk Management

The enterprise risk management framework for financial institutions has been evolving rapidly in recent years, driven by advances in AI technologies. A key element of this framework is the risk assessment process, which aims to identify and quantify the risks faced by an organization.


Only 8% of companies are methodically using artificial intelligence (AI), setting these enterprises apart from the competition. Natural language processing is a key technology for implementing risk management systems.

It can help analysts understand unstructured data, such as previous risk assessments, and identify patterns that may indicate risk. This information can then be used to create models that can be used to manage risk more effectively.

1. AI Can Help You Limit Your Exposure To Future Events

AI provides a means to analyze information, discover correlations, and predict outcomes. This involves gathering information from several different sources (texts, e-mails, news stories, marketing data, etc.) and converting it into predictive insights.

Its predictive capabilities are built on the algorithms that can generate “risk scores” through complex calculations using various variables such as: demographic data (age and income), financial data (ranking of assets), political data (electoral maps), and more.

2. AI Can Be A Great Strategic Tool For Planning

Rather than reacting to risk events as they occur, artificial intelligence is capable of helping you monitor and forecast your exposure to risk. It can help optimize the probability that you’ll come out on top in any given situation.

For example, artificial intelligence can help you determine which assets are more at risk and the sequence of events that is most likely to occur. It can also help you make better decisions on the type of coverages (contingent business interruption insurance, etc.) that will be essential in preventing potential losses many months before a disaster strikes.

3. AI Can Play A Significant Role In Risk Mitigation

One of the biggest benefits of artificial intelligence is that it allows you to “think ahead” and prevent risk events before they occur. AI helps by providing predictive models to help avoid the probability of losses.

For example, you can apply artificial intelligence when underwriting policies or determining coverage clauses that may be used in supporting claims. AI can also be applied to individual policies. It can help determine the likelihood that a policyholder will file a claim and how much it could cost if he or she does indeed file one.

4. AI Can Help You Handle Multiple Risks At Once

AI can be used to aggregate data from several different sources (e.g., payment information, credit reports, social media). It can then group various risk factors and create a profile of the underlying risk.

This is useful when managing risks that are related to each other or occur at the same time. For example, AI can help in underwriting multi-peril policies by comparing likely claims against loss-peril premiums in a portfolio.

5. AI Can Help You Adjust Policies To Respond To Evolving Risks

According to research from the McKinsey Global Institute, artificial intelligence (AI) might increase global economic production by $13 trillion annually by 2030. A key benefit of artificial intelligence is its ability to adjust policies proactively as new issues become more prevalent or important in the market.

This is due to the fact that AI can gather parameters, conduct market research and analysis, and translate it into data-driven insights. It can then use those insights to adjust policies to ensure continuous policyholder protection.

6. AI Can Increase Your Profitability

Artificial intelligence can help improve profitability by more closely matching the risk profile of a portfolio with the appropriate coverage levels. For example, you can use data gathered from social media platforms as well as credit reports to detect fraudulent activity and patterns.

The technology incorporates these social signals with financial information and fraud assessment charts to determine if any additional coverage should be added to an existing policy or new policies should be issued.

7. AI Is Capable Of Accelerating Deployment Of Policies

Whether you’re looking to develop a new policy or adjust an existing one, AI can help simplify the process and make it more effective. It helps save a lot of time by allowing for much quicker analysis and decision-making. The technology can also provide pricing data for insurance products more quickly.

8. AI Can Help You Deal With A Wide Range Of Risks

Artificial intelligence is capable of handling complex risks that were previously considered impossible to deal with. Some common risks include cyber attacks, the physical impact of climate change, labor shortages, customers’ exposure to new threats, etc.

Risks Of Artificial Intelligence In Risk Management

As of 2019, just 10% of SMBs had successfully incorporated AI into their operations. Financial services firms are turning to AI solutions to help automate business processes and improve data classification.


AI tools can help identify patterns and trends in data, making it easier for businesses to make decisions. AI systems can also help businesses automate tasks, freeing up employees to focus on other tasks.

1. Artificial Intelligence Can Cause More Harm Than Good

Unlike humans, machines do not always make the best decisions when it comes to risk management. Artificial intelligence requires an inordinate amount of data for which human employees are ill-equipped.

This can lead to false positives or negatives in determining whether something has merit or not. One example is when AI is used to predict a claim will be filed. In some cases, this can lead to the issuance of inappropriate insurance coverage or the underwriting of policies that do not adequately address risk factors.

2. Artificial Intelligence Cannot Assess Negative Scenarios

By definition, artificial intelligence is dependent on positive information and data points — something that’s very limited when it comes to assessing the likelihood or impact of negative events. To be effective, artificial intelligence systems must be able to handle both positive and negative scenarios.

This is why some insurance companies are experimenting with artificial intelligence in claims management. The technology can help provide a more holistic view of the claims process when it comes to looking at different claim types (e.g., unsold and damaged inventory claims, etc.).

3. Artificial Intelligence Cannot Consider Human Interactions

Machine learning-based AI capabilities have already started to be included into platforms like Trello to anticipate the repeating behaviours of their users. Even though humans are responsible for most of the underwriting and claims decisions, AI can’t take into account the various human interactions that occur during those processes.

If a human makes an error or omission, it could cause an error or omission in an AI decision-making process. Most companies are still learning how to accurately use AI these days.

4. AI Will Assume Power By Default

Companies have been using automation for years to control and manage risk. Some of the most prevalent examples include self-driving cars, automated financial services technology (e.g., robo-advisors, automated trading), etc.

In many cases, these technologies have enabled us to reduce unnecessary costs, improve product performance and provide better customer service. It’s no surprise that these systems are now being used in a wide range of insurance processes as well.

But some are concerned that AI will assume power too quickly as a result of the removal of well-trained human employees who can provide more objective advice on complex computational issues such as financial modeling and uncertainty assessment (i.e. determining the likelihood of a claim being filed).

As we’re seeing today, there’s a lot of hype regarding AI in the insurance industry. However, the reality is that most companies are still experimenting with it and the results are very promising. As more real-world data is gathered, more accurate assessments will be made about how to use this technology in different ways.

5. AI Could Cause Increased Fraud

In many cases, AI can be programmed to overlook potential fraud and prioritize claims that appear to be legitimate. This can result in increase premiums due to questionable claims or overcharges on existing policies.

6. AI Could Have A Negative Impact On The Customer Experience

Just as AI can help create more personalized experiences for customers, it can also have a negative effect when used inappropriately. For example, if you’re using AI to provide pricing information, the technology may inadvertently lead to customers receiving inaccurate quotes or others being denied coverage due to a variety of factors that are difficult to predict.

In the end, this could lead to bad reviews that discourage people from purchasing a new policy and may even cause some policyholders to terminate their policies.

7. AI Increases Risk Of Cyber Attacks

You’ve probably heard about how AI is becoming more sophisticated with each passing day. One of the reasons for this is because of the increased use of cloud computing. AI is also dependent on human employees for providing data to train the algorithms.

One serious concern for companies using AI in risk management is the increased risk of cyber attacks. Some experts expect that an estimated $2 trillion will be spent on cybersecurity in 2021 and it’s not just the insurance industry that will be impacted.

8. AI could experience excessive fraud

In the organisations surveyed, 40% were still exploring the potential applications of AI, while 11% had not yet begun any activity. Only 32% of them were active. Companies are already realizing that they must do a better job of managing fraud and other criminal activities by their employees, agents or customers.

The use of AI could lead to more fraudulent activities being overlooked because it doesn’t have enough data to make accurate assessments based on past incidents.

Final Note

The use of artificial intelligence in risk management is here to stay. AI offers a variety of benefits that can help improve the underwriting and claims processes, increase customer satisfaction, reduce costs and improve business performance.

Companies are grappling with what to do with this new and disruptive technology. How will they decide to use this emerging technology? Should they embrace it or avoid it altogether?

In some cases, you may see artificial intelligence being used in an attempt to predict or manage future claims or consumer behavior. Some companies are developing AI-powered models that can monitor consumer behavior in order to predict new claims and detect patterns related to fraud.

Last Updated on October 8, 2023 by Parina Parmar


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