In the dynamic and competitive financial industry, accurate market risk figures are of utmost importance to ensure sound decision-making, secure financial resources, and maintain a positive reputation. Mistakes in risk management can lead to significant financial losses and damage the bank's credibility with regulators and the public. To mitigate these risks, banks employ teams of analysts to verify market risk metrics before disseminating them to senior risk managers, front office, and regulators. However, the current manual and disjointed process is fraught with challenge, making it necessary to explore innovative solutions.

Overcoming Manual Processes and Time Constraints

The process of certifying market risk figures is currently burdened by several challenges.

First, the verification process involves a laborious manual examination of data at various aggregation levels. This approach is not only time-consuming but also prone to undetected mistakes if “netting” at a granular level.

Another one is triggered by different teams within the bank using specific tools and methodologies, making it difficult to establish standardised data certification processes across the organisation. This lack of uniformity presents a number of problems: on one hand it complicates explanations to regulators on the data certification process, on the other hand the certification quality could differ from one trading desk to the other.

Besides, the current process may not always uncover underlying data quality issues. Consequently, certain anomalies and inaccuracies may go undetected. It could lead to misinformed decisions and delay production of the daily risk metrics due to the rerun from start of all the production once the errors have been corrected.

Lastly, teams often face challenges in accessing comprehensive and granular metrics datasets necessary for conducting thorough analyses. This hinders  not only the means for the operator to analyse where the issues could come from but also  the development of automated and efficient tools and insights based on AI.

AI-Powered Game-Changing Approach: Standardisation, Efficiency, and Cost Savings

Opensee offers a transformative solution to the challenges faced by banks in certifying market risk figures. Leveraging cutting-edge AI technology, Opensee introduces a paradigm shift in the data certification process, empowering risk teams with comprehensive and efficient tools.

Opensee's technology grants risk teams immediate access to granular market risk metrics and deep historical data. This enables analysts to conduct in-depth analyses and identify potential issues efficiently.

It also provides specific tools and calculators developed by its quant teams. These tools facilitate the creation of standardised data certification processes across different risk teams, ensuring uniformity and coherence in the reporting process.

With Opensee, teams can easily configure data quality indicators tailored to their unique use cases and challenges. The platform's dynamic approach empowers analysts to identify and rectify data issues promptly and offers an intuitive data quality dashboard that allows teams to correct data discrepancies in real-time. This proactive approach minimises the time wasted on discovering and resolving issues.

Opensee's AI capabilities alert analysts to unusual metrics behavior at various aggregation levels. The platform provides clear explanations for these variations, enabling analysts to verify errors promptly and communicate effectively with stakeholders.

Opensee's technology revolutionises the data certification process from a time-consuming "needle in a haystack" approach to an efficient "control tower" model.

Empowering Banks with Opensee: The Evolution of Risk Management

The implementation of Opensee yields significant benefits for banks and their risk management processes:

• Cost Savings and Efficiency: By streamlining the data certification process and providing valuable AI-powered insights, Opensee reduces the reliance on a large number of manual analysts, resulting in cost savings for the bank.
• Increased Expertise and Employee Satisfaction: With a reduced need for manual verification, the remaining staff can focus on more value-added tasks, enhancing their expertise and job satisfaction.
• Enhanced Confidence in Market Risk Figures: Opensee's comprehensive and explainable process instills confidence in the accuracy of market risk figures, providing reassurance to management, front office, and regulators.

The quest for precise and reliable market risk figures is a constant challenge in the financial industry. With its cutting-edge AI technology, Opensee offers a transformative solution that empowers risk teams to streamline the data certification process. By providing immediate access to granular metrics, standardised tools, and AI-driven insights, Opensee enhances the efficiency and accuracy of risk management decisions. As the financial landscape continues to evolve, embracing innovative solutions like Opensee becomes paramount for banks looking to maintain a competitive edge and navigate regulatory demands successfully.

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‍About the author: Christophe Rivoire joined Opensee in 2019 as Senior Advisor before becoming Head of Strategy and UK Country Manager. Before joining Opensee, he spent more than 25 years in the Banking industry and especially in Fixed Income Trading in Europe and in the US. He started his career at Louis Dreyfus Finance before joining HSBC in 1998 where he held various responsibilities. Combining Risk, Trading, Technology has always been at the centre of his interests.