Dynamic Simulation, Planning, Strategic Enterprise Management

The riskpro™ dynamic simulation and planning functions cover market scenarios, business strategies and client behavior parameters templates combined with a broad functions library allowing total user controlled flexibility in modeling. These functions can be used independently for market risk or in combination with other riskpro™ analysis methods such as credit risk and FTP. For strategic enterprise management (SEM) analysis, data on costs, operation loss, etc. can be imported from cost analysis systems such as SAP, Oracle Financials, etc. as riskpro™ calculates only the results which are derivable from the concerned financial contracts. The currently implemented analysis methods are described below.

Strategy / Scenario Simulation

Allows the simulation of the evolution of all financial business activities (on-balance, P&L and off-balance) over time into the future (beyond the current business portfolio), based on forecasted market prices, selected business strategies (volume of new production, type of business, pricing), customer behavior (prepayment but also credit risk factors) and expected market behavior. The corresponding strategy and market scenario editors have access to the powerful riskpro™ function editors allowing building links to all the defined parameters (prices, spreads, volume restrictions, etc.).

Behavioral model

Includes inter alia the behavioral modeling like rollover strategies, pre-payments, sales and draw down of remaining principal due.

Monte Carlo Dynamic

Combines Monte Carlo market price scenario generation with strategy simulation. Because of the required high computing need it requires, in case of large contract volume, parallel processing with several processors.

Instrument coverage

All above methods are applied consistently for any type of financial product/instruments from deposits to exotic options.

For more information about riskpro™ Financial Instruments and Product Coverage.

Special riskpro™ strengths

• Full integration of all risk factors (market and credit risk) and return analysis in dynamic simulation
• Model allows to build very simple to very sophisticated analysis
• Balancing mechanism distinguishes between accrual and cash flows
• Consistent treatment of What-If and Monte Carlo analysis
• Allows business driven rolling budgeting and planning budgeting
• Suits needs of simple to very sophisticated institutions
• All results can be stored for later backtesting purposes