{"id":8498,"date":"2024-08-05T17:54:47","date_gmt":"2024-08-05T17:54:47","guid":{"rendered":"https:\/\/www.valuwit.com\/?p=8498"},"modified":"2024-08-05T18:21:34","modified_gmt":"2024-08-05T18:21:34","slug":"ai-in-risk-management","status":"publish","type":"post","link":"https:\/\/www.valuwit.com\/en\/ai-in-risk-management\/","title":{"rendered":"How Global Players Use AI for Risk Management and How You Can Too"},"content":{"rendered":"
A staggering <\/span>80% of business models<\/span><\/a> are currently at risk, according to global consultancy firm McKinsey\u2019s latest data. This statistic underscores the unavoidable presence of risk in any company. More importantly, they occur in various forms, including supply chain vulnerabilities, shifting consumer preferences, product defects, geographical instability, and unforeseen events such as political or natural disasters.<\/span><\/p>\n With the global race to integrate artificial intelligence (AI) in all forms of business, can the technology aid in risk assessment and management?<\/span><\/p>\n To put it simply, risk assessment involves identifying, analyzing, and evaluating risks for a business. Once the risks are identified, the risk analysis stage begins. It helps companies understand the impact of those risks on business operations.\u00a0<\/span><\/p>\n In the risk evaluation stage, companies see the severity of each risk and the consequences of not eliminating that risk.\u00a0<\/span><\/p>\n On the other hand, risk management is a process that takes place after risk identification. It involves how to treat, control, and mitigate the risks identified.<\/span><\/p>\n In other words, risk assessment is a part of risk management. Businesses need to analyze and evaluate to build their risk management strategies.<\/span><\/p>\n For risk assessments, companies often turn to AI technologies such as user and event behavior analytics (UEBA), which detect, analyze, and respond to threats.\u00a0<\/span><\/p>\n Read also: How are Businesses Using Generative AI?<\/b><\/a><\/span><\/p>\n In terms of advantages, AI can process large amounts of data that, done manually, would be prone to human error and not feasible. Using AI for risk management means processing tons of data to identify anomalies, patterns, and risks.<\/span><\/p>\n AI can also forecast potential risks, allowing companies to conduct proactive risk mitigation and management.<\/span><\/p>\n Using predictive analytics can help companies predict trends based on available historical data.\u00a0<\/span><\/p>\n In finance, for example, investment companies use machine learning to predict market fluctuations and credit risks, allowing them to make better investment decisions for the business and for their customers.\u00a0\u00a0<\/span><\/p>\n Roughly 81% of C-Suite executives<\/span><\/a>, in the banking and financial services industries, believe AI is important to their company\u2019s future success, as per research by AI-computing leader NVIDIA.<\/span><\/p>\n Automation and real-time analysis are also among the advantages of using AI in risk management. Using AI, companies can automate data analysis, especially routine tasks, thereby speeding up the analysis process and reducing human error.\u00a0<\/span><\/p>\n Real-time analysis can also provide better and faster solutions for time-bound problems, especially those that require faster response.<\/span><\/p>\n No solution is free of disadvantages. While using AI in risk management, companies should heed the potential downsides of AI and accordingly the results.<\/span><\/p>\n For example, one of the biggest challenges of AI in business, including risk assessment and management, is biased and incomplete data. Both of these will impact the AI technology\u2019s performance in your organization, resulting in inaccurate risk assessments, and, accordingly, skewed outcomes.<\/span><\/p>\n Another common problem is the \u2018black box\u2019 challenge, where companies struggle to uncover how an AI system reached a particular conclusion.<\/span><\/p>\nRisk management vs risk assessment<\/b><\/h2>\n
Pros and cons of using AI for risk management<\/b><\/h2>\n