Mitigating Risk

Evolving the Risk Management Discipline

By Andrew Gray, DTCC Managing Director and Group Chief Risk Officer | May 29, 2019

Evolving the Risk Management Discipline
Andrew Gray, DTCC Managing Director and Group Chief Risk Officer

Intelligent resilience is a phrase we coined to describe how risk managers can use strategic data analysis and informed decision-making to more effectively predict future shocks and understand ways to recover efficiently should a market event occur. The concept requires investing in people, processes and technology. Our people would set the strategy and leverage technology for data collection and consolidation. Using artificial intelligence (AI) or machine learning, they could conduct analyses across the extended enterprise by extracting insights from massive data sets, detecting patterns and supporting faster adaptation of risk models through automated learning. Technology opens the door to developing a more sophisticated and predictive risk management program in the future.

Harnessing the Critical Human Factor

Technology is playing a more prominent role in most firms’ risk management programs, but it has certain limitations, particularly when it comes to decision-making. The human element of risk management is essential for setting overall strategy, establishing a strong risk management culture and developing an approach for qualitative decision-making, the delegation of responsibility within an organization, and, of course, ensuring technological complacency is avoided. People are also essential for interpreting the output and applying the right level of judgment to how that information is used. Fintech’s true value is as an enabler of more advanced risk management, but it’s not a substitute for a comprehensive risk management strategy.

Identifying the Pattern of Attack

One of the most promising areas of artificial intelligence (AI) is its ability to identify what we call the “Pattern of Attack” – that is, the indicators, behaviors and sequence of actions of cyber-criminals that could help to identify them or the attacks they launch. Much like a detective uses this approach to solve crimes in the physical world, our team is beginning to use AI to do the same in the digital arena. AI can help us understand cyber-criminals and their actions in a completely different way than previous technologies allowed.

Powering Fintech With High-Quality Data

Robotics and artificial intelligence (AI) can transform how firms manage data, but the power of these technologies is dependent on creating a foundation of high-quality data governed by proper frameworks and disciplines. That’s because there’s an inherent synergy between data and AI. Data is the fuel that powers AI, so the richer the data, the smarter the technology is in identifying trends. The key to this is for firms to adopt a data-driven philosophy – and a rigorous data management program is the first step in building that culture. This will enable the necessary practices, standards and controls to ensure high quality of data, which is not only foundational for the business, but is essential for using advanced technologies to manage risk.

 

 

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