Business Analyst (Financial Industry Risk & Regulatory)

Question 1

Explain ‘Basel III’ regulatory standards.

Answer 1

Key components:
i. Minimum capital requirements: Higher capital reserves to cover potential losses.
ii. Leverage ratio: A non-risk-based measure to limit excessive leverage.
iii. Standards like the Liquidity Coverage Ratio (LCR) and Net Stable Funding Ratio (NSFR) to ensure banks maintain adequate liquidity.

Question 2

How to perform data validation?

Answer 2

• Testing and validating the accuracy and reliability of existing credit risk models.
• This ensures that the models perform as expected and provide accurate risk assessments.
• Example: Running historical data through the model to see if it accurately predicts past credit defaults.

Question 3

What are other regulatory standards related to Financial Services?

Answer 3

Dodd-Frank Wall Street Reform and Consumer Protection Act
i- Volcker Rule: Limits banks from making certain kinds of speculative investments.
ii. Consumer protection: Establishment of the Consumer Financial Protection Bureau (CFPB).

Sarbanes-Oxley Act (SOX)
- Internal controls: Requires companies to establish robust internal controls over financial reporting.
- Auditor independence: Strengthens rules to ensure the independence of auditors.

Question 4

Explain ‘Climate Risk Scenario Analysis’

Answer 4

• Analyzing how different climate scenarios, such as increased temperatures or severe weather events, might impact the financial stability of an organization. This helps in understanding potential risks related to climate change.
• Example: Assessing the financial impact on a bank’s mortgage portfolio if sea levels were to rise significantly.

Question 5

Explain “Stress Testing”

Answer 5

• Conducting simulations to evaluate how extreme but plausible (credible) adverse conditions, including those related to climate risk, could affect the financial health of an organization. This helps in preparing for potential financial shocks.
• Example: Simulating the impact of a prolonged drought on agricultural loans to determine the bank’s exposure to climate risk.

Question 6

What do you know about ‘Data Analytics’ and ‘Data Massaging’?

Answer 6

Data Analytics:
1. Using statistical and computational techniques to analyze large datasets and uncover patterns, trends, and insights that inform risk management decisions.
- Example: Analyzing transaction data to detect unusual patterns that may indicate potential fraud.

Data Massaging:
1. Cleaning, transforming, and organizing raw data into a more usable format for analysis. This involves correcting errors, filling in missing values, and reformatting data.
- Example: Converting various formats of financial transaction data into a standardized format suitable for analysis.