The Assignment
A mid-level investing bank needed to implement a stress testing framework in accordance with guidelines issued by the central bank.
Our mandate was to develop a collaborative, auditable, repeatable, and transparent stress testing program to meet regulatory expectations, inform on the bank’s risk appetite framework, and improve strategic business decisions.
Our Solution
The solution included the following key features:
1. Stress testing
Our stress testing framework comprised of regular stress tests and scenario analysis with severe macroeconomic global downturn scenarios. We included all material risk types into our stress testing exercises which included portfolio- and country-specific stress tests.
2. ICAAP
Capital plan stress testing was performed to assess the viability of the capital plan in adverse circumstances and to demonstrate a clear link between risk appetite, business strategy, capital plan and stress testing.
3. Scenario Analysis
The stress test framework also consisted of defined macroeconomic downturn scenarios which were based on quantitative models and expert judgments, economic parameters such as foreign exchange rates, interest rates, GDP growth or unemployment rates.
4. Reverse Stress Testing
Reverse stress test were to be performed annually in order to determine the severity of scenarios that would cause the bank to become unviable.
5. Risk Reporting and Measurement
The stress testing framework supported regulatory reporting and external disclosures, as well as internal management reporting, to be presented to senior management as well as to the risk committees, who are responsible for risk and capital management.
Key Takeaways for the Client
A robust stress testing framework that integrated governance, documentation, data quality management, economic scenario development, loss modeling, forecasting, and reporting and incorporated participation of all stakeholders across business units.
The framework was integrated across asset classes and lines of business and enhanced risk management and was customized to the unique strategies and risks of the bank’s portfolio
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Neural Networks for predicting the Financial Markets
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The feed-forward networks are the most widely used architecture because they offer good generalization abilities and are easy to implement.
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We can help our clients deploy Neural Networks to underwrite a loan and decide whether to approve or reject the loan application. This will help Banks to minimize the failure rate of loan applications and maximize the returns on the loans issued.
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