Driving Innovation in Banking.

Bank Risk Dashboard

  • Risk Sentiment Indicator
  • Bank Key Risk Metrics
  • Custom Stress Scenarios

Monitor banks' risk in real-time. Benchmark their public Risk, Liquidity and Capital disclosures. Stay ahead of the public sentiment and react quickly to negative news.

Risk Sentiment Indicator

An index used to gauge the overall sentiment of bank's risk in the media.

Sentiment analysis scans worldwide news sources to identify articles related to each bank. Subsequently, we assess the sentiment of these articles across various aspects such as solvency, liquidity, reputation, and political risk, assigning a score ranging from 0 to 100. This score reflects the percentage of instances in which the bank was depicted in a negative light.

Bank
News Count (14d)
Negative Sentiment
Articles w/Negative Sentiment
HSBC
    Barclays
      JP Morgan
        Societe Generale
          Goldman Sachs
            Credit Suisse
              Deutsche Bank
                Commerzbank
                  NatWest
                    Last updated:

                    How can this be used in your organization?

                    Risk sentiment analysis of media channels can be a valuable tool. Banks can perform sentiment analysis by monitoring various media platforms and sources. Here are some of the different types of media platforms and sources to consider:

                    News WebsitesSocial MediaBlogs and ForumsPress ReleasesIndustry ReportsAnalyst ReportsGovernment AnnouncementsPodcasts and WebinarsAlternative Data Sources

                    Early Warning System

                    Banks can use sentiment analysis to monitor media channels for early signs of emerging risks. By analyzing news articles, social media posts, and other media sources, banks can identify trends and sentiment shifts related to economic conditions, industries, or specific companies. Early detection of negative sentiment can provide a warning of potential financial risks.

                    Customer Sentiment Analysis

                    Banks can use sentiment analysis to understand how their customers perceive their services. By monitoring customer feedback on social media and other platforms, banks can identify areas of concern and make improvements to enhance customer satisfaction and loyalty.

                    Investor Relations

                    For publicly traded banks, sentiment analysis can be valuable in managing investor relations. Banks can use sentiment analysis to understand how their financial performance and corporate announcements are being received by the investment community.

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                    Bank Key Risk Metrics

                    A comparison of Risk KPIs across major Banks

                    Pillar 3 is one of the three pillars of the Basel III framework, which is a set of international banking regulations developed by the Basel Committee on Banking Supervision. These regulations were created to strengthen the stability and soundness of the global banking system. It encourages banks to provide information about their risk profiles and capital adequacy to enable market participants to make informed decisions and contribute to the stability of the financial system. We use the public disclosure of banks under Pillar 3 to benchmark bank's risk KPI and Stress Test bank's resilience to changing market conditions.

                    How can this be used in your organization?

                    Benchmarking how a bank's risk metrics compare to the industry offers several benefits, which can aid in enhancing risk management, decision-making, and overall performance.

                    Identify Areas for ImprovementGoal SettingEnhance Risk Management PracticesStrengthen Regulatory ComplianceImprove Capital AllocationEnhance Decision-MakingRisk MitigationResource AllocationRisk Appetite Definition

                    Optimize Liquidity Portfolio

                    Financial regulators require banks to maintain a minimum level of liquidity to ensure their ability to meet depositor and creditor demands. A diverse range of liquid assets in the HQLA portfolio can spread risk across various asset classes, reducing concentration risk and enhancing overall portfolio resilience. Optimizing its composition can yield additional returns whilst remaining within the risk appetite.

                    Enhance Models

                    Capital and Liquidity calculations involve intricate models, comprising components stipulated by regulators and others built in-house. With our expertise in model development, we can assist banks in identifying areas for enhancement in both their models and overall financial positions. Additionally, we can collaborate with local teams to implement these improvements effectively

                    Reverse Stress Test

                    We can assist in identifying market conditions that might lead the bank to exceed its risk appetite and regulatory thresholds. Furthermore, we can compare how comparable scenarios would impact other banks within the peer group. This analysis can be instrumental in pinpointing vulnerabilities in the bank's risk position, as well as in its liquidity and capital management practices.

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                    Custom Stress Scenarios

                    Create Market Consistent Scenarios to Identify Weakness in the bank's Balance Sheet, Capital and Liquidity KPIs

                    Interact with the charts by dragging any 2 points on the charts to create a new scenario (for example, drag the 2y and the 5y Government Bond points down). This will create a consistent scenario based on historic market correlations. You can then tweak the generated scenario by adjusting the suggested shocks. The severity indicator at the bottom suggests how different the scenario is from historic correlations. The algorithm is based on a multivariate distribution calibrated on at least 10 years of historic data.

                    Market Scenario over time horizon:
                    Scenario Severity:
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                    How can this be used in your organization?

                    Creating severe yet plausible stress scenarios is essential for stress testing a bank's portfolio for several important reasons.

                    Realistic Risk AssessmentEffective Risk ManagementRegulatory ComplianceCapital Adequacy AssessmentInvestor and Stakeholder ConfidenceProactive Risk MitigationAssessment of Complex InteractionsModel ValidationPreparation for Unknown Events

                    Create Scenarios

                    Generate severe yet plausible stress scenarios by introducing shocks to two, or more variables (e.g. the 2-year and 5-year German government bond rates). The models will automatically propagate these shocks to all other relevant variables. Additional inputs can also be provided to tweak the scenario. These scenarios can then be employed within Risk and ALM (Asset and Liability Management) systems to project the changes in the balance sheet, earnings, and other key performance indicators (KPIs) of the bank.

                    Risk Factor Expansion

                    Expand the scenarios provided by the regulators to market factors that are required by bank's internal models. The EBA, or the Bank of England stress tests typical provide 100s of variables in the definition of their Stress Scenarios. These then need to be expanded to 1,000's of variables for the bank's internal stress testing systems. We can help with the expansion using our model to ensure consistent scenario across variables.

                    Fast Stress Tests

                    By generating stress scenarios in real-time and applying to publicly disclosed risk information we can execute top-down stress tests in real-time. The accuracy of the stress test result can we further enhanced by working with a bank's internal data while maintaining the speed and immediacy of real-time execution.

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                    Team

                    RiskView is maintained by three experts in the field of Risk, Data and Economics who spent decades in senior roles at Investment Banks, Asset Manager, Sovereign Agencies and Large Corporations across Europe

                    • team

                      Dmitry Shibaev

                      Risk Expert

                      Dmitry spent 15 year in Investment Banking between London and Amsterdam. Most recently as Head of Stress Testing at NatWest Markets in Amsterdam, and prior to that held a number of senior roles in Risk, Treasury and Front-Office.

                      LinkedIn
                    • team

                      Paulo Rosario

                      Data Expert

                      Paulo has 15 years working in Data at major financial institutions . He is one of the original founders of the AI&ML community at M&G Prudential one of the first AI teams in the city of London. More recently he has been the Head of Indices & Data Science at Skytra-Airbus.

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                    • team

                      Ricardo Santos

                      Economist

                      Ricardo is an economist with 15+ years' experience, worked for EIB, ESM, BNP Paribas, Portuguese Budget Office, and Caixa Geral de Depositos. Focuses on banking, macro/sovereign, and climate risk monitoring, with models assessing risks in 150+ countries.

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