Financial Risk is defined as the uncertainty of a capital investment. Our systems for risk management aims at estimating and managing the main financial risk types of a financial branch. Risk distribution and corresponding risk capital allocation are assumed to be as follows:
Other risk types, in regard to the last economic crisis, include liquidity risks of assets and spread risks of assets and derivates. Risk Engine and Risk Framework cover a set of internal models that calculate risks measured and managed financial institutions.
Our solutions for risk management and risk mitigation use technological, human and organizational resources and follow international principles and standards (ISO 31000). Risk management includes identification, assessment, and application of measures, in order to minimize, monitor, and control the probability and/or impact of loss events.
Our Risk Management solution covers the most relevant risks, both in the financial and in the non-financial branch, since risks in non-financial institutions can be expressed in the last stages, in terms of financial risks. For example, the risk of price changes in materials, buildings, services, etc., is in fact market risk, in the same way as risk of changes in share prices.
The architecture of our solution shows a straight structure for calculation of various risk, integrated with other supporting modules within the entire risk management system. The main modules for Value at Risk (VaR) calculation include:
A set of supporting modules is used to produce the needed calculation data from primary market data:
Modules Portfolio management (Link to Portfolio Management in Risk Engine) and Market risk, via Monte Carlo and/or historical simulation (Link to Market Risk in Risk Engine), are presented in Risk Engine as well.
The data flow shown ensures the calculation and simulation of various risks, as well as the preparation of primary data, coming from the evaluation environment outside the system:
The functionality of regulatory requirements is ensured via the following modules and models:
|№||Module List||Models and Functionality|
|4||Rating and scoring||
The current coverage of Solvency II functionality is shown in the figure below. The coverage includes market risk, default risk, life underwriting risk and the calculation of BSCR (Basic Solvency Capital Requirements) and BCR (Basic Solvency Capital Requirements). Тhe calculated Basic Solvency Capital Requirement (BSCR) is adjusted for loss absorbency, using Equivalent Scenario or Modular Approach for each risk category. Solvency Capital for Operational Risk is considered in the calculation of Overall Solvency Capital Requirement (SCR) and Minimum Solvency Capital Requirement (MCR).
Ratings and scoring, within one or several internal or external rating systems, estimate the credit standing of counterparties. Rating estimations are needed as a measure for the ability to serve loans and other debt transactions in the credit risk calculation. Risk Framework offers solutions for estimation of private and corporate ratings, based on balance sheet data and soft factors. Country specific factors and criteria can be defined to consider particular economic environment conditions. Scoring results can be mapped to rating levels, using unified master rating scales. Certain rating levels are determined by early warning signals and corresponding KO-criteria. Official external information about counterparties can be included. In addition, scoring models evaluate the quality of the applied collateral, as the relation between planed debt redemption and debtor incomes. In this way, scoring can be used within the loan allowance procedure.
The quality of the produced rating and scoring is enhanced by adjusting rating and scoring models based on historical losses of a debtor pool, as well as produced ratings and PDs of the rating and scoring modules.
Advanced Measurement Approach (AMA) for operational risk is calculated via the Monte Carlo Simulation, using the Copula approach on non-normal distributions. Simulation distributions for severity and frequency for every loss event type are adjusted, based on the economic capital. This capital is calculated either according to those loss event types or to historical loss data base that accumulates internal or external loss data for the past 5 years.
We permanently adjust and improve the implemented financial and mathematical models for capital risk evaluation and control, following new standards and regulations. Additional models are currently being developed, for example:
Actual data for every interested currency:
Additionally, for pricing of options or embedded options, implied volatility data is required. A set of relevant market factors is obtained from the pricing model for every separate instrument type.
The market data given in FAQ 1, in addition to credit risk:
For every issuer or contract, the following assignments are created:
All models are based on the Gaussian Copula, so they can work with non-normal distributions.