How AI Can Help Enterprise Risk Management (ERM)

The Chief Financial Officer (CFO) is responsible for many business activities within an organization, commonly including enterprise risk management (ERM). In fact, Deloitte reported that 55% of surveyed CFOs said they are responsible for their organization’s ERM and that risk-related responsibilities are the most likely to be added to their scope of work within the next three years.

However, whether the ERM formally falls under a CFO or not, the CFO and its organization are key stewards of risk management and mitigation. 

The global ERM industry is projected to grow at a compound annual growth rate (CAGR) of 5.40% from 2022 to 2029, reaching a market value of $6.6billion. This projected growth rate is due, in part, to the ever-increasing recognition that a robust ERM not only helps identify and mitigate current and potential risks, but can also strengthen strategic decisions through the identification of opportunities in addition to threats. 

Similar to other industries, Artificial Intelligence (AI) is influencing and enabling more robust ERM systems where risks can be identified, measured, monitored, and addressed effectively. In this article, we will review what ERM is, the financial risks that fall under ERM, and how AI is or can be used to enhance financial risk management and mitigation.

What is ERM: Definition

Organizations and businesses have been managing, mitigating, and responding to risks arguably since the beginning of commerce. However, in the 1970s, when various management theories were developed, the ERM we know today began to take shape. The next ERM leap forward was in 1985 with the Committee of Sponsoring Organizations of the Treadway Commission (COSO).

This organization, which develops business guidelines for evaluating internal controls, fraud deterrence, and risk management, began analyzing the accounting scandals of the 1970s and 1980s. The resulting COSO 2013 Framework defined ERM as “The culture, capabilities, and practices, integrated with strategy-setting and its performance, that organizations rely on to manage risk in creating, preserving, and realizing value.”

ERM: Financial Risks

The list of financial risks for businesses to mitigate is extensive. Below we will note the 6 most common financial risks and how increasingly businesses are using AI to manage and mitigate their impact. 

1) Credit/Default Risk 

Credit/default risk relates to the likelihood of borrowers defaulting on the principal and interest on their outstanding loans. 

AI Risk Management and Mitigation Assistance for Credit/Default Risk:

  • Real-Time Monitoring:  AI doesn’t take days off and can monitor the many areas of a business in real time. It can be designed to report to the company when certain thresholds have been met or exceeded, or specific events occur. For example, AI can monitor borrowers’ credit rating and history to identify those who first appear to struggle financially. The lender can then take proactive measures to mitigate the likelihood of credit/default risk from materializing. 
  • Predictive Analytics: AI can use statistical modeling from internal and external data to predict what percentage of borrowers are at risk of default and the associated level of exposure.
  • Decision Support: AI can use statistical modeling to determine the risk profile for each borrower to help determine whether a loan should be made and at what interest rate, given the level of risk.
  • Automated Compliance Checks: Each borrower will have conditions in their loan agreements. These conditions may include maintaining a certain credit rating, liquidity, or financial ratios to help prevent default. AI can run compliance checks automatically and report to the lender and the borrower when the agreed loan conditions are not being met.

2) Liquidity Risk  

The first part of liquidity risk is whether businesses have the cash on hand necessary to pay its obligations. The second liquidity risk is market liquidity risk, where a company may need more time to sell assets or security in a down or volatile market. 

AI Risk Management and Mitigation Assistance for Liquidity Risk: 

  • Real-Time Monitoring, Efficient Reporting, and Predictive Analytics: AI can monitor the cash balances in multiple bank accounts. With this information, it can use current and historical operational data and forecasts from AI based FP&A tools to predict if and when it will need external financing to manage the business’s liquidity risk.
  • Decision Support: AI can support businesses making tactical and strategic decisions by providing reliable reporting of current and forecasted cash balances. For example, if a business is considering an acquisition within a specified time period, AI supplies the best estimate of the cash available for the purchase. With this information in hand, the business can decide if it should raise external funding, such as taking on debt or selling equity in the company. 

3) Foreign Investment Risk  

The risk of investing in businesses or assets in foreign countries.

AI Risk Management and Mitigation Assistance for Foreign Investment Risk:  

  • Real-Time Monitoring, Efficient Reporting, and Fraud Prevention: AI can monitor the online reputation of the company or investment vehicle, as well as report any suspicious transactions or discrepancies in the provided financial information. 
  • Decision Support: AI can support business decisions before investing in a foreign country and handle subsequent decisions. AI can quickly scour sources and identify the main risks of doing business in each foreign country considered for investment. It can also use predictive models to forecast important financial information such as cash flow and earnings before interest, taxes, depreciation, and amortizations (EBITDA). With this information, a business can decide if it will continue to do business in a foreign country or exit. 

4) Currency Risk

The likelihood of losing money when exchanging currency from one country of business to another. 

AI Risk Management and Mitigation Assistance for Currency Risk: 

  • Real-Time Monitoring and Efficient Reporting: AI can keep a real-time account of fluctuation in exchange rates and report to the business when it has reached or pre-defined threshold.   
  • Decision Support: AI can calculate the Forex gain or loss at any time the business is considering an exchange. It can also determine the Forex gain or loss considering any Forex hedge the business has employed. 

5) Fraud Risk 

There are many different forms of fraud; however, it can be generally defined as illegal activities undertaken by a company or individual(s) to cause a gain or loss.

AI Risk Management and Mitigation Assistance for the Risk of Fraud: 

  • Fraud Detection and Prevention: AI can analyze large amounts of transaction data for irregularities that may signal potential fraudulent activities. With possible fraudulent activities being flagged earlier, businesses can mitigate the fraud risk much earlier and reduce the potential financial impact. 

6) Interest Rate Risks 

The risk of paying higher interest rates on outstanding debt. Interest rate risk has reared its ugly head since Q1 and Q2 of 2022 as countries work to reduce inflation through material increases in their lending rates. 

AI Risk Management and Mitigation Assistance for Interest Rate Risks:

  • Real-Time Monitoring and Efficient Reporting: AI can report any interest rate changes and estimate the business’s current and projected cost increase exposure. 
  • Decision Support: With the information above, businesses can decide how best to mitigate interest rate risks. This could include selling assets to reduce debt levels, and adjusting their capital structure to reduce debt by increasing other forms of capital, such as selling equity in their business.  


Enterprise Risk Management (ERM) is a business function that has gained tremendous importance over the past decades as the world becomes more complex, with new risks to be managed and mitigated. Thankfully, artificial intelligence (AI) can help organizations manage new and potential risks more efficiently and effectively through the automation of complex tasks, better accuracy, and actionable insights to inform decision-making processes. 

Frequently Asked Questions (FAQs)

How Can AI Help Risk Assessment?

In the finance industry, AI is a game changer due to its ability to quickly process large amounts of data and recognize potential risks that may otherwise have gone undetected. Unstructured information can be scrutinized in order to identify patterns, trends, as well as establish foreseeable events or risk possibilities. This greatly improves accuracy when it comes to forecasting from complicated datasets while providing advanced risk analysis capabilities at the same time.

Will Risk Management Be Replaced by AI?

Risk management is something that should be handled by experienced ‘human’ professionals. AI shouldn’t act as a substitute for the human element.

How Does AI Help Business Management?

AI can help boost business efficiency through automation, target marketing efforts more effectively, and predict customer requirements. It can also improve the speed of operations and decrease mundane tasks to free up employees for more meaningful activities.

What Role Does Real-time Monitoring Play in Enhancing Risk Mitigation Strategies with AI?

The importance of real-time monitoring in terms of risk mitigation for AI systems cannot be overstated. Proactive steps taken by organizations to monitor their AI on a continuous basis can help them avert potential issues before they arise, and thus prevent any costly errors or disruptions down the line. With effective tracking measures that immediately pick up on risks as soon as they emerge, companies are able to take action to manage and mitigate the identified risks.