Corporate Risk Modeling

Macroeconomic Models

To understand the key drivers at macroeconomic level that impact the credit portfolio performance, i.e. country specific macroeconomic models. These models are typically used in fine tuning the business strategy and conducting the stress testing of the portfolio.

Industry Specific Models

To measure the risks at Industry level and to align risk strategy with business strategy. Industry specific inputs may be directly taken into the customer specific models.

Early Warning System (Model)

We also help our clients to validate the existing models either developed in-house or purchased off-the shelf, to provide independent assurance to our clients.

Independent Model Validation

We calibrate the models output with “master Rating Scale’ of the client. We also help to develop the ‘Master Rating Scale’ for the clients to ensure meaningful differentiation of risk within the risk grades.

• Through the Cycle (TTC) Calibration
• Point in Time (PIT) Calibration (Required for IFRS 9 Compliance)

Obligor Models

For corporate banking depend on the business activity of the client. We support our clients in developing the comprehensive ‘Risk Model Landscape’ suited to their respective portfolios along with the models.

• PD Models - By size, activity based models, counterparty risk models & specialized lending models.
• LGD Models - By Business Segments & Collateral Type. Our LGD models take care of all the possible states post default for assessment of LGD i.e. restructuring, liquidation and cure rate, to assess the overall LGD.
• EAD Models - For Off-Balance Sheet Product Categories

Model Calibration

Typically ratings generated from standard models with significant time lag, to overcome this limitation we develop ‘Early Warning System’ for our clients which helps them in proactively identifying the weak borrowers at an early stage. This helps them to proactively reduce their exposure or limit their exposure to such accounts.

• Data Extraction: This includes extracting obligor data, calculating financial ratios, extracting other input factors and performing data quality checks.
• Rating Methodology and Factor Analysis: This includes reviewing in detail the portfolio of the bank, factor selection on the basis of various statistical analysis methods, discussion and finalization of the input factors with the client.
• Model Development and Calibration: This includes finalizing the structure of the model, transformation of raw score to a comparable scale, estimating weights of the factors or parameters and calibration of the portfolio etc.
• Results and Documentation: This includes testing the results of the model and documenting the model development or validation approach in detail.

Profitability

• Enables the bank to measure & better price the risk – ‘Improved Transaction Pricing’
• Profitability could be measured and compared consistently across different segments
• Allows for assessment of ‘Risk Adjusted Return on Risk Capital’ for different segments
• Empowers the bank to exercise better controls resulting in lower credit losses
• Allows measurement of effects of collaterals on profitability of transaction/obligor
• Increased discriminatory power of models will result in corresponding reduction in losses
• Allows to compete in the international market with ‘Globally Active Banks’

Risk Differentiation

• Leads to increase in risk differentiation among obligors, products, portfolios, businesses etc.
• Provides improved capability for setting and monitoring risk limits – ‘Proactive Risk Management’
• Increase in the overall quality of the bank’s lending portfolio over time
• Enabling an automated credit decision making environment

Risk Differentiation

• Improved ‘Turn Around Time (TAT)’ for credit approvals
• Credit function to focus on only ‘Borderline Credit Cases’ – Improved effectiveness/efficiency
• Proactive portfolio monitoring & remedial management to limit the losses
• Enables advanced ‘Business Intelligence’ and ‘Analytical Insights’
• Helps to enhance ‘Risk Culture’ across corporate banking group
• Increased quality in data capture enables better data analysis and improved decision making