Bonanza @Risk
  • @Riskis designed as a web-based application program through (
    /atrisk ) which enables the clients to use Risk anywhere at anytime. Besides, Risk also provides a secured environment for the clients data by applying the following security systems:

The Black Box Concept


Secure Sockets Layer (SSL 128 bit) is a tool used to encrypt private information before securely transmitted via the internet. Private information will be hardly captured and translated by hackers when the information is being exchanged between @Risk and clients.

Auto Logout: automatically logout after 30 minutes of idleness

Browser Control is a system which does not allow users to back to the previous page ( to the previous page that is in a secure mode) .

Furthermore , the @ Risk still allow users to create and keep their own portfolio on the website so as to decrease redundancy when calculating Value at Risk (VaR) and Credit Risk.


Bonanza @Risk : Risk On Demand

Credit Risk
Credit Risk module is developed on Basel II concepts to calculate credit risk of corporate bond.

           Build-in Methodologies  

  • Accounting Base (Financial Ratio with logic regression)
  • Option Pricing Base

   Estimate the following below on both security and portfolio

  • Expected Loss ( EL )
  • Unexpected Loss (UL)
  • Unexpected Loss Contribution (ULC)

   Presented with tables 

Market Risk
Market Risk module is developed on Value at Risk (VaR) concepts to calculate market risk of securities.

  • Calculate VaR on a wide range of financial instruments
    • Equity
    • Fixed Income
      • Bond
      • B/E , NCD and other FI
    • FX
    • Index Futures
  • Facilitate 3 methodologies with centered financial database
    1. Historical Simulation
    2. Variance Covariance
      • Volatility and Correlation forecast (e.g. Equally MA, EWMA)
    3. Monte Carlo Simulation

  • Export volatility and correlation
  • Include Stress Test
  • Include Back Test
  • Presented with graphics and tables
  • Linked with Bonanza Investment by using the @Risk Client