ROV CMOL Risk
CMOL Risk is an IT solution to perform comprehensive analysis for banks on credit, market, operational, and liquidity risks. CMOL Risk takes all of our advanced risk and decision methodologies and incorporates them into a simple-to-use and integrated software application used by small and midsize banks. It simplifies the risk-based Basel II and Basel III requirements providing to managers, shareholder and stakeholder powerful analytics with user-friendly results and compliance reports.
Applies Basel II/III requirements on credit modelling (residential mortgages, revolving credit, wholesale corporate and sovereign debt, and miscellaneous credit), computes Regulatory Capital (RC), Risk-Weighted Assets (RWA), and Economic Capital (EC), given inputs such as historical default data to compute Probability of Default (PD), Loss Given Default (LGD), and Exposure at Default (EAD).
Computes Gross Value at Risk (VaR) and internal simulated VaR with various holding days and VaR percentiles. Includes Central Banking Methodology
Applies ll of Basel’s Operational Risk methods such as the Basic Indicator Approach (BIA), Standardized Approach (TSA), Alternate Standardized Approach (ASA), Revised Standardized Approach (RSA), and Advanced Measurement Approach (AMA) are supported in the software. Monte Carlo Risk Simulation methods are used in concert with convolution of probability distributions of operational risk Severity and Frequency to determine Expected Losses (EL), Unexpected Losses (UL), and estimation of Basel’s OPCAR or Operational Capital at Risk values for the AMA approach.
Models Asset Liability Management approaches to compute Liquidity Gap, Economic Value of Equity (EVE), and Net Income Margin (NIM) based on interest rate risk and liquidity risk, with stress testing and scenario analysis
Provides structural, time-series, portfolio, and credit models on estimating PD, EAD, LGD, credit exposures, options-based asset valuation, volatility, debt instrument valuation, Credit Conversion Factors (CCF), Loan Equivalence Factors (LEQ), and a myriad of other models
Monte Carlo Risk Simulation
Allows accessing to 50 probability distributions, including Extreme Value Distributions (EVT) for estimating and simulating Severity of Operational Losses (e.g., Fréchet, Generalized Pareto, Gumbel, Logistic, Log-Logistic, Lognormal, and Weibull) and Frequency of Operational Risk Events (e.g., Poisson)
- Windows 7, 8, or 10 (32 and 64 bits)
- Microsoft .NET 2.0, 3.0, 3.5 or later
- Excel 2013, 2016, or later is recommended for report extraction but required
- 350MB Hard Drive space
- Administrative Rights to install software
- MAC OS users can run the software as long as they have Bootcamp, Virtual Machine, or Parallels