Traditional, static enterprise risk management (ERM) frameworks struggle to keep pace with the lightning-fast decisions and ever-shifting landscapes of modern markets. To forge a more dynamic risk management environment, Chief Risk Officers and Heads of Trading require scalable, adaptable, and resilient risk management technology.
This survey was conducted during a webinar hosted by Quantifi and Risk.net on ‘Dynamic Enterprise Risk Management: Turning Risk into Opportunities’. More than 200 individuals registered for the webinar and were invited to participate in the survey. The speakers were David Arnold, former Chief Risk Officer, Société Générale Corporate and Investment Banking, Jacqueline Llanos, Managing Director – Head Enterprise Model Validation, Credit Suisse, and Alexei Tchernitser, Director, Product Management, Quantifi.
Staying ahead of the curve
Which features would you like to see improved or added in your ERM solution?
Streamlined risk reporting is essential for effective decision making. Customisable dashboards can greatly enhance usability by allowing users to view risk in a format that suits their needs. A reporting framework that allows users to drill-down to trade level and specific risk data further enhances understanding and provides actionable insights, leading to more effective risk management strategies.
Real-time risk monitoring plays an important role in trading performance, risk management, compliance, and maintaining transparency in financial markets. Being able to calculate and report in real-time gives organisations visibility into how positions are performing so they can react swiftly to changes in price movements and market sentiment. Integrating real-time risk data across various business units enhances decision-making, fosters agility, and ensures compliance with regulatory standards.
Quantifi’s live risk framework is built on a modern scalable architecture designed to calculate both trade and portfolio level pricing, P&L, and risk in real time, on both simple and complex products.
Scaling up
Scalability is an essential aspect of an ERM solution as it means the system can handle large amounts of data, more complex risk scenarios, and more extensive regulatory requirements without compromising performance or accuracy.
How satisfied are you with the scalability of your ERM solution?
It is important for banks to regularly assess the scalability of their ERM solutions to ensure they can keep up with growing demands and changing risk profiles. Key features of a scalable ERM solution include managing large volumes of data efficiently, maintaining speed and accuracy of analytics, and automation capabilities. With scalable ERM solutions, banks can maintain robust risk management practices, protect their assets, and sustain customer trust. These solutions can also support better decision-making by providing timely and accurate risk insights, essential for strategic planning and operational efficiency. They enable seamless integration with other systems, facilitating a comprehensive approach to risk management. Additionally, scalable solutions can adapt to future technological advancements, ensuring banks remain competitive and compliant with industry standards.
Adopting cloud: balancing risk and reward
The results highlight uncertainty in migrating systems and activities to the cloud. This uncertainty is less likely to be because of a lack of confidence in the technology but rather risk, security and regulatory concerns. Data security concerns are top of mind for banks. Ensuring compliance with stringent regulatory standards and safeguarding client data are critical challenges that banks must address when transitioning to the cloud.
Is your bank considering transitioning to cloud-based ERM solutions for better scalability and flexibility?
For banks that want to modernise their risk architecture, cloud technology provides tangible benefits. The scalability of cloud infrastructure enables risk managers to save considerable time on risk calculation and therefore focus on other business priorities. Not surprisingly, calculation-intensive areas of risk management e.g. valuations, and counterparty risk simulations, are typically the first movers to cloud-native implementations. Other benefits of cloud include easier access to applications and data, reduced IT costs, and increased flexibility.
In an interconnected world, where risk now has many dimensions, cloud-based architecture and practices allow banks to manage and mitigate risks intelligently. Artificial intelligence is becoming integral to cloud technology. It enables banks to automate processes and workflows, and generate real-time insights.
By embracing cloud solutions, such as Quantifi, banks can proactively address emerging threats and uncertainties while optimising operational efficiency and resilience in an increasingly complex environment.
Sizing up third-party technology solutions
When evaluating third-party technology providers for enterprise risk management, banks prioritise different factors.
Which factors do you consider most important when evaluating third-party technology?
Regulatory compliance features, customer support, and cost-effectiveness were not considered significant factors.
Reliability ensures the technology consistently performs as expected, minimising operational disruptions. Scalability is crucial as it allows the technology to handle increasing workloads and adapt to the bank’s growing demands whilst maintaining performance.
A proven implementation track record indicates the technology can be rolled out quickly and integrated smoothly into existing workflows, systems and tech stack. Together, these factors ensure the technology can support the complex and evolving risk management requirements, providing a robust, adaptable, and dependable solution.
Quantifi’s implementation process is designed for success. A key element of this is the experience of the client service team. We have a well-defined approach to implementation that ensures all risks are identified upfront and carefully managed. This is a result of significant investment in tools that facilitate the process, including out of the box interfaces and configuration.
Tech-driven transformation: AI, ML, and Data Science
In today’s digital age, the financial sector is undergoing a transformation powered by data analytics, artificial intelligence (AI), and machine learning (ML). These technologies are changing trading and risk management in finance.
How do you perceive the role of technologies, e.g., AI, ML, data science in trading and risk management?
The majority of respondents acknowledged the transformative power of technologies such as AI, ML, and data science in trading and risk management. Algo trading is one area benefiting from advances in AI and ML. These technologies enable the development of sophisticated algorithms that can analyse vast amounts of market data at unprecedented speeds, identifying patterns and making predictions with high accuracy. GenAI is set to transform many industries, with banks being key beneficiaries. By enhancing modelling analytics, automating tasks, and integrating unstructured content, GenAI is changing how banks operate, including how they manage risks and stay compliant with regulations.
This whitepaper, ‘Generative AI in finance: market insight extraction’ by Lumerafields and Quantifi, illustrates how Large Language Models (LLMs) can be used via Retrieval Augmented Generation systems (RAGs) to refine and systematise market insight extraction by gathering relevant information from datastores at inference time to enrich prompts. Data science plays a crucial role by providing the tools and techniques to manage and analyse large datasets. It helps in deriving actionable insights from complex data, enabling better risk assessment and management. Advanced data analytics can identify potential risks by analysing historical data and spotting trends that might indicate future market volatility.
Accelerate transformation
Quantifi’s philosophy is to leverage standard, robust technologies and benefit from the significant innovation occurring in technology. Unlike systems saddled with years of legacy code, Quantifi is designed from the ground up using the latest, most advanced technology and design patterns to ensure optimal performance. This approach gives clients significant advantages in performance, scalability, usability, and ease of support. It also has a major impact on Quantifi’s ability to rapidly turn around enhancements and new features.
Trusted by 5 of the 6 largest investment banks, Quantifi’s enterprise risk solution is a real-time platform that supports cross-asset trading, front-to-back operations, position and risk management (market, credit, counterparty, and liquidity risk), limit management, and regulatory reporting. An integrated analytics library generates results matching top-tier banks for even the most complex derivatives.
