What changes will GenAI bring to risk management?


The introduction of GenAI has brought wide-ranging and disruptive change to a vast range of industries. In the area of risk management, this is no different.

According to Flagright growth manager Joseph Ibitola, the emergence of GenAI is poised to introduce both novel opportunities and challenges within the realm of risk management – and he also believes there are several key areas where GenAI will play a transformative role.

He explained, “Firstly, with an ability to generate sophisticated simulations and predictive models, GenAI could revolutionize the way risk scenarios are modeled and evaluated. This will empower organizations to anticipate a broad array of risks, including some which might have been previously unforeseeable or hard to quantify.”

Ibitola added that the automation capabilities of GenAI could substantially enhance operational efficiency and accuracy in risk assessment. “Instead of manual, time-consuming processes prone to human error, we’ll see highly accurate, fast, and data-driven processes driven by AI,” he exclaimed.

Despite this, he believes that the transformative power of GenaI does not come without its share of potential risks. “The quality and accuracy of the generated models and predictions are entirely dependent on the quality and extent of the training data,” Ibitola exclaimed. “There may be risks associated with data privacy, bias, and misuse of the technology. Furthermore, the adoption of GenAI will necessitate strong cyber-security measures, as more aspects of risk management become digitized and potentially susceptible to cyber threats.”

Ibitola underlined that given the trends towards digitisation and automation, these such changes are likely to be permanent. However, he said that the industry must remember that the evolution of technology is a dynamic process, and the risk management sector must be prepared to adapt to new developments as they arise.

Ibitola concluded, “GenAI holds enormous potential for the risk management sector, but its implementation needs to be handled with great care. Regulators, professionals, and AI developers must work together to ensure the technology is used responsibly and ethically, maximizing its benefits while minimizing its potential downsides. This is an exciting period of transition and transformation, and with the right approach, the benefits of GenAI can be harnessed effectively in the risk management sector.”

Tackling inefficiencies  

One of the chief tenets and uses of ChatGPT and other GenAI solutions to date is its ability to simplify work and more tasks more efficent.

In the opinion of Alessa CEO Holly Sais Phillippi, GenAI can and will have a substantial impact on the risk management sector given the ability to analyse such large volumes of data in a short timeframe.

She explained, “Given the ability to process such large amounts of information it allows for patterns, emerging risks, and correlations amongst different types of risk to be quickly identified, which is much more challenging for a human to detect in a short amount of time.

“Adopting GenAI will lead to more accurate risk assessments and help with improved decision-making timelines. In the industry Alessa plays in, there is a continued concern around the manual efforts risk analysts and risk managers engage in simply to eliminate “false positives”, this technology will significantly reduce those manual efforts and allow the teams to focus on much more complex areas of risk that will have an actual impact to the fight against financial crime.”

Alongside securing more accurate risk assessments and better decision-making timelines, Phillippi believes GenAI will also play a significant role in fraud detection. She explained that fraud loss is well in the billions, and with GenAI it can be trained to identify patterns indicative of fraudulent activities both by analysing historical data and real-time information. This, she explains, will allow firms to react much quicker to potential fraud activities and limit losses.

Phillippi remarked, “As GenAI is rapidly evolving, its impact on risk management will continue to evolve as well, it is permanent and will continue to be refined as the technology progresses. As with any new technology there are going to be early adopters and those that are a bit slower with adoption.

“I think this is especially true for the Risk and Compliance space, while GenAI can and will have a significant impact on the industry over time it will require the industry to become more and more comfortable with the explainability. I am personally excited to see what GenAI will do for our industry over time, early adopters are already seeing an impact to their ability to mitigate risk in a much more efficient manner.”

Philippi emphasised that risk teams strive for the opportunity to make a real impact in the fight against crime. However, there is continued pressure on budgets all while meeting regulatory requirements – and she believes that GenAI can have a substantial impact on helping the industry achieving the ‘why’ in what they do, which is fighting financial crime.

Managing risks

The ability to change financial risk management is two-pronged – in the sense of both from the inside and the outside, claims Muinmos CEO Remonda Kirketerp-Møller.

She commented, “When I say from the inside, I mean it can be used as a tool to perform the tasks required for that role. As risk management is not a generative profession in nature, the from the inside changes should be minor.” She explained that GenAI is especially good at producing content, such as text, images and videos, which are usually not a very large part of a risk officer’s role, whose main task is to identify, assess, and manage risks that the institution faces. Regular AI, Kirketerp-Møller quips, already helps them with that.

Kirketerp-Møller continued, “The main impact can come, therefore, from the outside. The ability of generative AI to “twist” and “re-invent” (to use mild terms) reality can pose, for example, serious KYC challenges. For example, GenAI can create fake news articles, which can challenge data vendors, who sometimes already struggle to detect and coherently filter “Adverse Media”. Fraudsters may also be able to use GenAI tools to create an avatar which can easily fool the human eye on a video-verification call.”

The Muinmos CEO concluded by stating that the main challenges will be to manage the risks GenAI will bring with it, and that will require looking to the market for tech solutions that can mitigate those risks and ensure the industry has a regulatory framework that can handle it.

Pitfalls and possibilities

According to Vladimir Ershov, head of data science and machine learning at Clausematch, the impact of GenAI on risk management will be twofold. “It will revolutionize both the methodologies employed in risk management and the nature of the risks being managed, introducing novel types of risks to consider.

“The integration of GenAI and AI-powered RegTech tools into the risk management sector can yield numerous benefits, including cost savings and enhanced automation. These tools facilitate real-time decision-making, underpinned by comprehensive and multifaceted content analysis,” he exclaimed.

Despite this, he waxed that this transition isn’t without its potential pitfalls. “The increased reliance on automated systems diminishes human oversight, which could potentially lead to biased or opaque decision-making if the AI tools are of substandard quality.”

He concluded by outlining that the incorporation of GenAI in all sectors introduces a new set of AI-related risks that must be duly considered during risk assessment. “Hence, they will necessitate an ongoing evolution or redesign of many risk management strategies to accommodate and mitigate these emerging risks. The changes have already become permanent,” he finished.

Hugo Warner, head of risk advisory at Novatus Advisory, also quipped, “There is a double edged sword when it comes to AI in risk management. On one hand, the tools to control existing risks will become more effective and comprehensive as AI learns to detect risk issues faster and becomes more effective as rate of data collection and processing increased, AI can be taught to identify trends.

“However, on the other, new risks are likely faced, such as fraud, as technology becomes more sophisticated. It will be vital that firm’s using AI within their risk management framework consider both sides and maintain oversight of its uses”.

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