AI has been around for way longer than we think. As a basic concept, Artificial Intelligence can be referred to the ability of machines to learn and make decisions based on data and analytics. However, using strategically, AI has the potential to make enormous differences in the way we go about our work.
With AI, the world of business has been constantly evolving and becoming innovative. Across multiple sectors, from Healthcare to Transport and Banking to Engineering, Artificial Intelligence (AI) is changing the way businesses interpret both internal and external processes. AI is already transforming businesses, regardless of size and scope, helping create opportunities for higher development. It is reshaping companies and redefining rules in industries. Whether it is implemented in automating business processes or data analytics for transforming risk management, AI is changing traditional ways of business administration.
THEN: Traditional Risk Management
Many companies have been overcoming the challenge of monitoring risk for decades with the help of risk management. Risk Management is the continuous process of identifying, analysing, evaluating, and treating loss exposures. It monitors risk control and financial resources to reduce the adverse effects of loss. However, traditional risk management practices resulted in several challenges such as manual processing of data, Limited Data Analysis, Absence of Real-Time Monitoring, Subjective Human Judgement, Complex Models, Cybersecurity risks and regulatory compliances.
Companies today have access to more data than ever before. According to Forbes, the amount of data generated and consumed had increased by 5000% between 2010 and 2020. Protecting data alongside managing it requires big task force. To their advantage, AI possesses the power to enhance risk management.
NOW: AI-Driven Risk Management
AI is no longer a mere exception; it has become a necessity. Most companies are navigating alternatives to improve Risk Management. Automation, Artificial Intelligence and Machine Learning are high demands in the market as it is creating waves in the business sector. According to recent studies, the AI trust, risk, and security management market was valued at $1.7 billion in 2022 and is projected to reach $7.4 billion by 2032, growing at a CAGR of 16.2%. This substantial growth heightens the value that AI brings to the table in identifying and managing business risks.
Another survey claims, “Companies that take a more holistic approach to AI, focusing on achieving three business goals, see greater success than those that take a singular approach.” Leaders benefit greatly from AI and tackle those three business outcomes together: Enhanced Decision Making, Business Transformation, System Modernization. AI can handle and analyse large volumes of unstructured data at faster speeds with considerably lower degrees of human intervention. Therefore, it allows organizations to build competency around customer intelligence, successfully implementing the strategies and lowering potential losses.
AI powered solutions can provide following key benefits:
- Improved Forecasting and Predictive Analytics:
AI enables more accurate forecasting by analysing vast datasets and identifying patterns, trends, and correlations that may be challenging for traditional models to detect. Machine learning algorithms can predict potential risks helping organizations anticipate and proactively address emerging threats. AI and Internet of Things (IoT) combined sensors can predict machines’ performance and maintenance needs, resulting in better operational decisions.
- Enhanced Fraud Detection:
AI-powered systems such as Cognitive Analytics excel in detecting unusual patterns and anomalies in financial transactions, making them highly effective in fraud detection. Advanced machine learning algorithms can adapt and evolve to new fraud patterns, providing a dynamic defence against evolving risks. As this system is used regularly, it will learn to detect even more complex fraud, making it the biggest advantage for risk management.
- Optimized Credit Scoring:
With AIs, Computer become smarter. It can improve credit risk assessment by considering a broader range of variables and evaluating complex relationships among them. AI being objective, analyses the available public, private and consent-based data and utilises this to calculate the risk associated with an individual or business. The use of alternative data sources and real-time information enhances the accuracy of credit risk evaluations.
- Automated Compliance Management:
AI streamlines compliance processes by automating the monitoring of regulatory changes and ensuring that risk management practices align with evolving legal requirements. Natural Language Processing (NLP) capabilities enable systems to analyse and interpret regulatory texts, facilitating adherence to complex compliance frameworks.
- Cybersecurity Threat Detection:
Making AI responsible for making accurate decisions, limited to your requirements, is a way of protection. AI plays a crucial role in identifying and responding to cybersecurity threats by continuously monitoring network activities and identifying suspicious behaviour. It can assess explainability, robustness, bias, fairness, and transparency. It can detect new, previously unseen threats based on their ability to learn from evolving patterns of cyber-attacks.
- Supply Chain Risk Management
Supply Chain disruptions has the potential to put business into risk, causing reputational and financial damage, threatening organizational viability. AI can deliver powerful optimization capabilities required for accurate capacity planning, improved demand forecasting, enhanced productivity, lower supply chain costs, and greater output.
- Scenario Analysis and Stress Testing:
AI enables more sophisticated scenario analysis and stress testing by considering a broader range of variables and their potential interdependencies. It can further simulate various scenarios, helping organizations assess the impact of different risk factors on their operations.
Ram is a Cloud Security Expert with 30+ years of IT experience, holding 26 patents in Infra, AI-ML, and Automation. He’s a Wipro Fellow, an Independent Consultant for Fortune 15 companies, and has won international awards for Automation. Ram’s cost rationalization work benefited enterprises like Citi Bank, Credit Suisse, and UBS.