AI: Unlocking the Deeper Essence of Risk Management

AI: Unlocking the Deeper Essence of Risk Management

By Capital Markets CIO Outlook | Friday, June 28, 2019

Organizations are driving transformative initiatives to improve risk management with the aid of artificial intelligence. The domain of risk management is a perfect fit for AI capabilities, as the cyber risk landscape is growing. 

FREMONT, CA: The technology era heralded unparalleled opportunities for the advancements and also unleashed a range of new attacks vectors. For the promise of progress has gone hand in hand with a variety of new perils, Artificial Intelligence (AI)  is set to transform the banking industry using vast amounts of data to build models that improve risk management.  According to the McKinsey Global Institute, this could generate the value of more than $250 billion in the banking industry.  

While AI is still developing, it can be used to mitigate in some key areas. Machine learning can give more informed predictions about risks, and it can be used to build various revenue forecasting models. AI has successfully detected credit card fraud. Financial institutions are using this system that has been trained on previous payment data to monitor payments for potentially fraudulent activity and prevent suspicious transactions. Firms also use automated systems to track traders by linking trading information with behavioral information, including email traffic, and even telephone calls.

AI-driven analytics platform can handle supplier risk by combining various data on supplier's geographical and geopolitical environments through their financial sustainability, and social responsibility scores. AI systems can also be trained to detect, monitor and prevent cyber attacks as they can identify software with certain distinguishing features like tendency to consume a large amount of processing power and then close down the attack.

Apart from the above benefits, AI is considered a source of significant risks that must be managed. Some of the main risks associated with it include algorithms bias, overestimating the capabilities of AI, programmatic errors, legal risks and liabilities, and reputational risks. For this end, firms should ensure that they have appropriate structures in place to manage ethical risks and understand how it is addressing algorithmic bias.

AI presents opportunities when applied right and risks when applied wrong. But real change is happening in the risk domain with AI, and it is indeed a potential game changer for risk professionals.

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