System for Modeling Risk Valuations for a Financial Institution

• US 20150058260A1
• Filed: 10/31/2014
• Published: 02/26/2015
• Est. Priority Date: 02/11/2009
• Status: Abandoned Application

• Current Assignee: Johnathan C. Mun
• Original Assignee: Johnathan C. Mun
• Inventors: Mun, Johnathan C.
• Application Number:
  US14/529,468
• Publication Number:
  US 20150058260A1
• Time in Patent Office: Days
• US Class Current: 705/36.R
• CPC Class Codes: G06Q 10/067 Enterprise or organisation modelling
• CPC Class Codes: G06Q 40/02 Banking, e.g. interest calculation or account maintenance credit or loans G06Q40/03
• CPC Class Codes: G06Q 40/03 Credit; Loans; Processing thereof
• CPC Class Codes: G06Q 40/06 Asset management; Financial planning or analysis

Abstract

A method and system allowing banks and financial institutions the capability to perform advanced credit and market risk analyses required by central banks and banking regulators or supervisors, such that the banks are in compliance with the Basel II and Basel III Accord requirements. This system is both a standalone and server-based set of software modules and advanced analytical tools that is used to quantify and value credit and market risk, as well as forecast future outcomes of economic and financial variables, and generate optimal portfolios that mitigate risks.

Claims

1. A computer implemented system for evaluating financial risk, the system comprising:

a computing device;

a business logic layer residing in a non-transitory memory of said computing device, wherein said business logic layer comprises;

a risk analyzer module for computing and valuing market and credit risks, such as through use of Monte Carlo simulations,

a risk modeler comprising over 600 models for providing risk valuation and forecast results for assets or liabilities, and

a stochastic risk optimizer for performing static, dynamic and stochastic optimization on portfolios, including making strategic and tactical allocation decisions using said optimization techniques,

a user interface for inputting one or more parameters,

whereby said business logic layer selects a relevant model to run from said risk modeler based on said parameters and automatically maps the parameters to any necessary data required to run the selected model,

whereby said business logic layer runs a simulation by applying the selected model to said parameters;

a data access layer residing in a non-transitory memory of said computing device, for accessing, retrieving, or modifying the data mapped to said parameters; and

a presentation layer residing in a non-transitory memory of said computing device, for presenting the computed results of said simulation.

2. The computer implemented system of claim 1, wherein a user can select a model type to run.

3. The computer implemented system of claim 2, wherein a user can select the number of values to produce when running a simulation based on said model.

4. The computer implemented system of claim 3, wherein a user can select one or more time periods, and the duration of said time periods, over which said model will be applied when running a simulation.

5. The computer implemented system of claim 1, wherein said user interface comprises a detailed description and explanation of each model.

6. The computer implemented system of claim 1, wherein the user interface comprises one or more selectable options for choosing a type of analysis to perform, such as a risk analysis on a debt instrument, or a historical or future valuation of an asset.

7. The computer implemented system of claim 6, wherein the user interface displays a set of models available for selection by the user.

8. The computer implemented system of claim 7, wherein one or more required input parameters are listed in the user interface based on the model selected.

9. The computer implemented system of claim 8, wherein a user can map the one or more required input parameters to existing data, thereby creating a model profile that can be stored for future use.

10. The computer implemented system of claim 1, wherein said data mapped to said parameters can be filtered using one or more conditional statements.

11. The computer implemented system of claim 1, wherein running said stochastic risk optimizer requires a user to select a model, input or select one or more parameters (a.k.a. decision variables), input or select one or more constraints, input or select one or more statistics, and input or select an optimization objective.

12. The computer implemented system of claim 11, wherein said static optimization is performed by running a simulation that applies the selected model to changing parameters.

13. The computer implemented system of claim 11, wherein said dynamic optimization is performed by running said simulation a plurality of times, recording the statistical results of said plurality of simulations, and applying said selected model to said statistical results.

14. The computer implemented system of claim 13, wherein said stochastic optimization is performed by applying said simulation to one or more random generated parameters, and running said optimization multiple times, thereby generating forecast statistical distributions.

15. The computer implemented system of claim 1, wherein one or more of said models may be used to calculate the probability of a default.

16. The computer implemented system of claim 1, wherein one or more models may be used to calculate volatility associated with an asset or liability.

17. The computer implemented system of claim 1, wherein one or more models may be used to calculate a financial institution'"'"'s exposure as a result of a default (exposure at default).

18. The computer implemented system of claim 1, wherein one or more models may be used to calculate the probable loss to a person or institution in the event of default of a credit or debt (loss given default).

19. The computer implemented system of claim 1, wherein the results of a simulation or calculation are stress tested.

20. The computer implemented system of claim 1, wherein the results of a simulation or calculation are back tested.

21. The computer implemented system of claim 1, wherein one or more models may be used to determine the likely loss that would result from a credit or debt default (expected losses).

22. The computer implemented system of claim 1, wherein one or more models may be used to determine the value or percentage of a bank'"'"'s portfolio that is at risk given some probability of an event occurring over a specific time horizon (value at risk).

23. The computer implemented system of claim 1, wherein one or more models may be used to calculate the total expected losses for a portfolio.

24. The computer implemented system of claim 1, wherein one or more of said models may be calibrated by manipulating the data mapped to said input parameters.