# Automated information and analysis system for estimating financial risks

FIELD: computer science; finance.

SUBSTANCE: system has workplace for analyst-operator, connected to server via connection line, which server has: means for forming a data set concerning current state of portfolio and payments concerning portfolio tools, means for forming a set of variants for controlling portfolio of financial tools, means for forming database and calculating statistic characteristics on basis of history values of risk factors, means for building prognoses in form of debt coefficients matrix, means for calculating risks and means for forming reports.

EFFECT: lower risks.

10 cl, 3 dwg

The invention relates to computing devices, intended for specialized tasks, in particular for modelling the management of financial instruments, estimated financial risks and management decisions with the aim of reducing them. The invention can be used to control the liabilities and assets of banks, financial institutions, government agencies, and implementing the investment activity of enterprises.

Known control system financial operations in the investment environment, which contains the Central processing unit and management of the investment Fund, the device issuing financial (credit) liabilities device receiving financial (credit) liabilities, device processing and management the Fund's financial (credit) liabilities and issuing means of payment (RF Patent No. 2111535, G 06 F 17/60, 1998). The system is designed for credit and placement of available funds in financial institutions using the system, and guarantee income by reducing the investment risks of the return of funds invested in a particular time.

However, the system cannot be used to reduce the risk of the investor when making transactions on the sale of securities, VA the Utah involvement in the loan or the placing on Deposit of cash resources.

This problem is solved in a computer system Risk Metrics (Introduction to Risk Metrics, JPMorgan, new York, 1995, p. 3), which is the closest to the claimed, and contains the input device, the device receiving data about specific assets, in particular on financial instruments, as well as data about the main characteristics of financial instruments, transactions on instruments, data on historical values of risk factors, device, and means intermediate storage and data processing and output device data.

System Risk Metrics is as follows. Through the input device data enter information about the composition and amount of financial instruments held in the investment portfolio, specifications of all financial instruments (basic settings date maturity dates and amounts of payments of income, currency and so on). Then form the structure of the investment portfolio and schedule of payments, receivable by the investor. The generated data is sent to the storage module. In the module storing data complement information about the historical and current prices of financial instruments and historical values of the risk factors, then, in the module of calculation of statistical quantities calculate the current mn the treatment of the standard deviation (volatility) for each of the risk factors and correlations between different risk factors. The obtained data is sent to the calculation module script and return to the storage module. In the module of calculation they calculate scenarios of the behavior of risk factors based on the estimated values of statistical quantities. The results of the calculations are sent to the module complete analysis, in which for a given portfolio, make a calculation of the likely cash flows on this portfolio. The calculated data in the module is full of risk calculation, which assess the overall risk of the considered investment portfolio. Valued in monetary terms, the risk is passed to the module making decisions based on the mapping data about risks other investment portfolios, or mapping data limits (limiting values) possible risks the user decides to transactions on the market.

The disadvantages of the described system is that it allows to model scenarios of the behavior of risk factors only based on the assumption of normal distribution of the random variables that characterize the behavior of the factors that allows to calculate scenarios of behavior risk factors solely on the basis of such aggregate quantities as standard deviation and correlation coefficients. The system allows to calculate the risk of this then the portfolio and does not involve the formation of different management options portfolio. The system can be used only to evaluate the market risk of the investor.

Object of the invention is the extension of the risk analysis framework by: expanding the range of possible scenarios for the behavior of risk factors by introducing into the base of evaluation of a set of expert change scenarios risk factors that allows you to assess the risks for cases where the distribution of risk factors is not normal; provide automated formation of different options portfolio management; calculation of various types of risk.

When carrying out the claimed invention may be obtained from the technical result by reducing the level of risks in the management of liabilities and assets, enhancing investment performance.

Achieved the task that automated information and analytical system of evaluation of financial risks that contains the input device, the device receiving data about specific assets, in particular on financial instruments, as well as data about the main characteristics of financial instruments, transactions on instruments, data on the historical values of the risk factors, the data carrier, device, and means intermediate storage and data processing and output device data further comprises a means of formation of the of abortion practices data about the current state of the portfolio and the payment instruments portfolio by algorithm input data about the instruments of the portfolio and set operations tools the existing portfolio; the means of creating a set of options for the management of a portfolio of financial instruments through input algorithm set operations tools existing in the portfolio, and a set of operations on the created in this embodiment, additional control tools; tool to create a data Bank and calculation of statistical characteristics of the historical values of risk factors by means of the algorithm of data import and processing algorithms historical data on risk factors and calculation of statistical characteristics; means forming a data Bank according to expert forecasts and the projections on risk factors by means of the algorithm input data values of the risk factors for future points in time, evaluated by an expert, and the algorithm of formation scenarios of weights and forecasts for risk factors; means of calculating matrices debt indicators by calculation matrices debt indicators; means of calculating risks by means of algorithms for the calculation of risk matrices debt indicators on options for the control, verification of the debt indicators limitation, calculation of debt measures and ranking of management options for risk assessments; means of reporting through algorithms generate reports on the data again, calculated by other means system.

In the automated information-analytical system of evaluation of financial risks due to the organization of the functional relationships between cells of memory device data processing means generating a set of data about the current state of the portfolio; means of generating a set of data about the current state of the portfolio and payment instruments; means of calculating matrices debt indicators; means of calculating risks consistently associated with a means of reporting, and the second output means of generating a set of data about the current state of the portfolio is the entrance means for the formation of a data Bank and calculation of statistical characteristics of the historical values of the risk factors connected with the tool to create a data Bank according to expert forecasts and projections risk factors whose output is the second input means of the calculation of the matrices in debt indicators.

Figure 1 presents a block diagram of a computer system for the preferred alternative implementation of the present invention; figure 2 - components of the server computer system; figure 3 - block diagram of the subsystems of the server computer system.

Automated information and analytical system of evaluation of financial risks in accordance with aseason the invention can be made on the basis of a large number of different computer systems, however, it is preferable to use the system in the form of computer network, client/server, depicted in figure 1. The system includes a server 1, which is connected with employment (client computers) 2 operators, analysts and data sources 3, various communication lines 4, for example, fiber optic, telephone, satellite link or other.

Workplace 2 operator-analyst can be an IBM - compatible personal computer, a laptop computer, using the operating system Microsoft Windows 98 or equivalent. Workplace 2 contains the input device 5 (keyboard, mouse), the device receive data 6 (e.g., memory on hard disks, CD-ROM or floppy drive) on certain assets, in particular on financial instruments: bonds, loans, guarantees (denominated in roubles and other currencies), as well as data about the main characteristics of financial instruments, such as debt (bonds - the number of traded bonds, loans and guarantees - the amount of outstanding debt instrument), operations financial instruments (bonds, the date and the size of the coupon payments on loans - the date and amount of interest payments) and the like, data on historical values of risk factors (under the risk factor refers to some couples who Tr depend on the characteristics of cash flows (for future points in time) on the instruments included in the portfolio arising in the process of borrowing and debt servicing; values of this parameter in the future is not determined, but predicted with a certain probability; an example of a risk factor for bonds denominated in dollars, can serve as the exchange rate of the ruble to the dollar, as it determines the amount of repayment of the bonds in rubles); the intermediate storage device and data processing, which is the memory of client computer 7; the microprocessor 8, and output device data 9 (display, printer).

The server 1 in the preferred embodiment, the system includes a microprocessor 10, a memory 11 and the data carrier 12, located on the physical storage media - magnetic, optical or any other media (in the current implementation, the storage medium is a hard disk of a computer). Server 1 is by means of placing computer subsystems and a single module.

As shown in figure 2, the server 1 contains the means 13 consisting of a resource 14 of the microprocessor 10, the cells 15 of the RAM 11, the segment 16 of the hard disk 12 server) creation of a data set on the current state of the portfolio and the payment instruments portfolio by Sal the rhythm input data about the instruments of the portfolio and set operations tools the existing portfolio;

17 (consisting of resource 18 of the microprocessor 10, the cells 19 of the RAM 11, the segment 20 of the hard disk 12 server) generate a set of options for the management of a portfolio of financial instruments through input algorithm set operations tools existing in the portfolio, and a set of operations on the created in this embodiment, additional control instruments;

the tool 21 (consisting of resource 22 of the microprocessor 10, the cells 23 of the RAM 11, the segment 24 of the hard disk 12 of the server) to create a data Bank and calculation of statistical characteristics of the historical values of risk factors by means of the algorithm of importing data, performing at the operator's request to the device 6 through the device 7), the receiving device 6 (through the device 7) the set of necessary data, and storing data in databases systems, and algorithms for processing historical data on risk factors and calculation of statistical characteristics;

the tool 25 (consisting of resource 26 of the microprocessor 10, cells 27 of the RAM 11, the segment 28 of the hard disk 12 of the server) to create a data Bank according to expert forecasts and the projections on risk factors by means of the algorithm input data values of the risk factors for future points in time, estimated ex is artnum by, as well as the algorithm of formation scenarios of weights and forecasts for risk factors;

the tool 29 (consisting of resource 30 of the microprocessor 10, the cell 31 of the RAM 11, the segment 32 of the hard disk 12 server) calculate matrices debt indicators (spending on debt, amount of debt service costs, spending on debt repayment, amount of funds attraction and so on) through calculation of matrices of debt indices;

the means 33 consisting of a resource 34 of the microprocessor 10, the cells 35 of the RAM 11, the segment 36 of the hard disk 12 server) calculation of risks by means of algorithms for the calculation of risk matrices debt indicators on options for the control, verification of the debt indicators limitation, calculation of debt measures and ranking of management options for risk assessments;

the tool 37 (consisting of resource 38 of the microprocessor 10, cell 39 RAM 11, the segment 40 of the hard disk 12 server) reporting by algorithms generate reports based on data calculated by other means system.

The means 13 associated with the means 17 and 21 through the organization of functional connections between cells in the RAM 15, and 19 and 15 and 23. In turn, the functional relationship of the cells 19 and 31, 31 and 35, 35 and 39 provides a serial communication medium spans the 17, 29, 33 and 37 to each other. The presence of functional connections between cells in the RAM 23, 27 and 31 creates a parallel line connection between the means 13-31 through the 21, 25 and 29, and between cells 27 and 39 additional communication means between 25 and 37. Output means 37 through the intermediate storage device and data processing 7 is connected with an output device data 9 systems.

In operation of the treatment system operator-analyst from the workplace 2 by means of the server 1 via a single unified GUI.

Data sources 3 can be an information system, implemented in the form of databases MS SQL Server 2000, Oracle 8.0, ODBC sources, or the like, of which the data is transmitted via communication lines, for example, fiber optic, telephone, via satellite or other.

On each server tools 1 implemented one computer subsystem, which is a collection of databases for storing data and software modules that are implemented in the server RAM and intended for the organization of the functional relationships between the subsystems, the implementation of the external data input, data transformation and data to other subsystems. Under the data Bank is a set of ordered data located at the physical novtel the x data electromagnetic, optical, or any other media (in the current implementation, the storage medium is a hard disk of a computer). Data banks belonging to different subsystems can be stored separately in different databases, and together in one common database. In practice, a possible implementation of data storage belonging to different subsystems in the form of combining data banks in any combination, i.e. the number of physical databases can be arbitrary. The software module is a separate module of a computer program or a program developed in the RAM of the server.

The means 13 of the server 1 is intended for implementation of the subsystem portfolio structure (41); on the tool 17 is implemented subsystem formation of variants of portfolio management (42); for placement subsystem calculate statistical characteristics risk factors (43) is a means 21 for placing the subsystem calculate scenarios and scales of risk factors (44) - tool 25; to host subsystem analysis (45) - a means 29 for placement subsystem calculate risks (46) - tool 33. The reporting (47) is implemented in the tool 37.

As shown in figure 3, the subsystem structure of the portfolio (41) includes a software module job portfolio structure (48), implemented in the cell is 15 RAM resource usage 14 processor and consisting of module assignments instrumental portfolio structure (48.1) and module calculate the initial parameters of the cash flows on portfolio (48.2); data Bank portfolio structure (49)implemented at the segment 16 of the hard disk of the server, and consisting of a data Bank instruments (49.1) and Bank portfolio data tools (49.2); software module of generation of initial parameters for statistical calculations (50), implemented in the cell 15 of RAM resource usage processor 14, and consisting of a module forming parameters for statistical calculations (50.1), module parameters forming the end calculations (50.2) and module parameters forming risk (50.3). Output subsystem 41 is a set of data about the current state of the portfolio and the payments for each of the instruments included in the portfolio, which are automatically transferred to the subsystem 42, and a set of parameter data for statistical calculations, which are automatically transferred to the subsystem 43.

Forming sub-system control options (42) includes a software module forming options portfolio management (51), implemented in the cells 19 of RAM resource usage 18 processor; cell 52 RAM server, intended for intermediate storage of data, and Bank d is the R options portfolio management 53, implemented at the segment 20 of the hard disk of the server. Included for subsystem 42 are data on the initial state of a portfolio of financial instruments of the subsystem 41, and an external data set limitations and expert options, portfolio management, entering the system through the device 5 or from data sources 3. Output subsystem 42 - data set options, change the state of the portfolio and the payments for each of the tools included in the revised portfolio, which are automatically transferred to the subsystem 45 and the subsystem 47.

Subsystem calculate the statistical characteristics (43) includes a software module of calculation of statistical quantities (54), implemented in the cells 23 of RAM resource usage 22 processor, data banks of the historic values of the predictable risk factors (55) and storing the statistical values (56), implemented on the segment 24 of the hard disk of the server. Included for subsystem 43 is data generated in software module 50 subsystem 41, and external data about the historical values of the risk factors are coming into the system through the device 5 or from data sources 3. Stored in the cells 24 data Bank subsystem 56 43 data are automatically transferred to the subsystem 44. Output subsystem 43 - Russ is Fannie in accordance with the algorithm of calculation of the statistical characteristics of the data about the mathematical average standard deviation and correlation coefficients for each of the risk factors.

Subsystem calculate scenarios and weights (44) includes a software module of calculation of scenarios of behavior risk factors (57), implemented in cells 27 of RAM resource usage 26 processor, data banks, the expert forecasts (58) and matrix behavior risk factors (59), based on segment 28 of the hard disk of the server, and the cells (60) RAM server. Included for subsystem 44 is the data stored in the data Bank 56 subsystem 43, as well as data about the historical values of the risk factors entered by the operator from the device 5 or entering the system through the device 6 from the data sources 3. Output subsystem 44 is calculated in accordance with the algorithm of processing of historical data on risk factors data matrices behavior risk factors, which are automatically transferred to the subsystem 45 and the subsystem 47.

Analysis subsystem (45) includes a software module forming combinations of triples (61), implemented in the cell 31 of RAM resource usage processor 30 through which is formed a number of combinations of triples (option portfolio management, risk factor, setup); the data Bank memory combinatoric (62), implemented at the segment 32 of the hard disk of the server, and software analysis module (63), implemented in the cell 31 of RAM resource usage processor 30. In software module forming combinations of triples (61) subsystem analysis (45) in the automatic mode enters the following information: data about the options portfolio management of financial assets of the cells 52 memory subsystem 42, data matrix behavior and attitudes of risk factors from cells 60 server memory subsystem 44. After carrying out the calculation according to the algorithm using the standard formula calculation of the debt indicators stored in the cells 31 memory subsystem 45 data matrices debt indicators (costs debt service costs, the cost of repayment, the borrowed funds, etc. for each day of the calculation period risk) are automatically transferred to the subsystem 46.

Subsystem calculate risks (46) includes cells (64) RAM server for storing matrices debt indicators and management options, data banks predefined constraints (65), discounting/airmusic capital (66), store the output options (67), data analysis (68) implemented on the segment 36 of the hard disk of the server, and software modules of the risk calculation (69),constraint checks (70), the discounted/aerovane indicators (71) comparison of alternatives (72), implemented in the cells 35 of RAM resource usage 34 processor. Included for subsystem calculate risks are data matrices debt indicators coming in the automatic mode of the subsystem analysis (45), as well as external data on parameters set limits and parameters discounting/airmusic capital entered by the operator from the device 5 or entering the system through the device 6 from the data sources 3. Output subsystem 46 is calculated in accordance with the algorithm of calculation of risk values risk matrices debt indicators on options for the control, verification of the debt indicators limitation, calculation of debt measures and ranking of management options for risk assessments. Data on the results of the calculations in the subsystem 46 - list of ranked options portfolio management of financial assets, as well as stored in the database 68 matrix debt indicators are automatically transferred to the subsystem 47.

The reporting (47), implemented in cells 39 RAM resource usage 38 processor is designed to generate reports for the various portfolio management under various sections on the basis of the e data obtained at various stages of system operation and automatically sent to the module 47 after each stage of the system operation. Module 47 allows the conversion of incoming information (data) in a graphical or tabular presentation (reporting) and output the received reports to screen, printer or other output device 9.

The effect of information-analytical system for simulation control options financial assets is as follows. In the subsystem of formation of the initial parameters of financial instruments 41 enter the data about the kinds and types of financial instruments. By processing the data using special software subsystem of formation of the initial parameters of financial instruments 41 form a signal containing information about the types and existing at the time of modeling the types of financial instruments and their parameters (characteristics, including risk factors), which is then passed to the subsystem calculate the statistical characteristics of risk factors 43 and the subsystem job options portfolio management 42.

At this stage the system via the display (9) requests the data about the initial state of a portfolio of financial instruments. The system operator enters the required data. For each instrument, wholemeal portfolio, the user puts in data banks portfolio structure information about the amounts and dates of future operations on instruments (bonds coupon payments on loans interest payments), as well as information about the amount of debt (bonds number of bonds held in the trading system; for loans and guarantees - the amount of outstanding debt). Data about the current state of the portfolio and payments on instruments portfolio are recorded in databases (49) manually using standard input devices (5) or using a device receiving data (6) from external data sources (3). To manually enter data into the system, in a software module (48) provides a wizard to create the structure of the portfolio, which displays on the display (9) of the client computer queries about the necessary settings of the portfolio structure, takes input operator data and sends them to the memory of the server, and from there into the data banks subsystem (49.1 and 49.2), where they are stored. To implement the mechanism of import data software module 48 by the operator makes a request to external databases through the device receiving data (6), i.e., software module by the operator requests and receives from the external database, the set of necessary data, which automatically directed to the op is calling the server memory, and from there to the banks data subsystem (49.1 and 49.2), where they are stored. Data about the operations tools are stored in the database on instruments (49.1). Information about the portfolio stored in the data Bank (49.2). Stored in 49 data are automatically transferred into the software module 50 to form the initial parameters implemented in the cell 15 of the RAM on the server, using the resource microprocessor 14 is formed information about the parameters for statistical calculations on the required risk factors (section 50.1), about the time intervals used to calculate risks (section 50.2), on the structure of the portfolio of financial instruments (section 50.3). The generated information is stored in the cells 15 RAM on the server.

The data from the data Bank 49 are automatically transferred to the subsystem of formation control options (42), and the data generated in the software module 50 automatically transferred to the subsystem calculate statistical values (43).

The subsystem 42 in the automatic mode, data is transmitted on the current state of the debt portfolio of the subsystem 41, as well as from external sources of information enter information about the options portfolio management with regard to the current state of the portfolio. By processing using special software data received from the subsystem 41 and an external source of the information 3, in the subsystem of formation of structure of the portfolio of financial instruments and job options portfolio management 42 model options portfolio management and allocate (or the characteristics of the existing tools, any of the management options that are set from the external information sources analyst) the risk factors involved in put options portfolio management in a specified time period management. Data on the initial state of a portfolio of financial instruments that are stored in the data Bank 49, automatically come in a software module 51, which is implemented in random access memory (11) of the server. Next, for each instrument included in the portfolio, is entered in the system information about the dates and amounts of transactions for changes in the portfolio structure (in numeric form or in the form of formulas dependency of the volume of operations from risk factors). For each option portfolio management operator contains information about additional tools that are not included in the current state of the portfolio is: date and amount (for bond - quantity and price, for loans and guarantees - volume; in numeric form or in the form of formulas dependency of the volume of operations from risk factors) receipt of funds on tools, payment tools on the tool. Filling is carried out by the system operator BP is know using standard input devices (5) (keyboard, “mouse”). This software module 51 provides a wizard control options, which displays on the display 9 of the client computer queries about the necessary settings control options, takes input operator data and sends them to the memory 19 of the server, and from there into the data banks, posted on the segment 20 of the hard disk.

In the data processing subsystem 42, a signal is generated that contains information options, portfolio management, financial instruments, which passed in the analysis subsystem 45.

Data on options for the management of a portfolio of financial instruments remembered in memory (52) server and database management options (53). These data are automatically transferred to the subsystem analysis (45). Also from subsystem 42 in the reporting (47) in automatic mode, data is transmitted from the data Bank options portfolio management (53).

Data on the initial parameters of the portfolio of software module 50 automatically come in a software module 54 that is implemented in RAM on the server where they are automatically transferred and stored in the data Bank storing the statistical values (56). Also at this stage the operator of the system is filling in a data Bank of historical value the deposits predictable risk factors (55). To enter data into the system used by the device receiving data. To implement the mechanism of import data subsystem 43 by the operator's command is a request to the device receiving data containing the database, i.e. requested and received from the external database a set of data that is sent to the RAM of the server, and from there into the database (55) subsystem, where they are stored. Stored in the database 55 historical data for each predicted risk factors are automatically transferred into the main memory of the server where by the microprocessor server processed - is the calculation of the mathematical average (54.1), standard deviation (54.2), correlation coefficients (54.3) (formula shown below in the example of system operation). The calculated data in the automatic mode are sent to the database storing the statistical values (56)where is the memory on the mathematical average, standard deviation and correlation coefficients for each of the risk factors. Stored in the database 56, the data is transmitted to the subsystem 44.

Forecasting based on historical data in the subsystem 44 is carried out using the data obtained in the subsystem calculate statistical'hara the characteristics of (43). The data stored in the database 56, automatically transferred to the software module calculating weights and behaviors risk factors 57, implemented in the server's RAM, which in module 57.1 calculated values for each risk factor, and in the module 57.2 for each risk factor is a matrix of behavioral risk factors, where each interval to calculate the weights is mapped to its relative weight (probability). The calculated data is stored in RAM on the server (60).

From a mathematical point of view the result of this stage of the forecasting risk factor based on historical data is a time series of predicted values of risk factor, as well as time series of theoretical values of the forecast errors. Thus the forecast error grows with increasing forecast horizon, which limits the possibility of long-term forecasting. This method is used generally to predict on a relatively short-term (from one month to one year). Forecasting for longer periods is carried out using a set of expert estimates.

In the database expert forecasts of changes in risk factors (58) recorded numerical data predictive values of risk factors. Data are entered into the database manually using standard the x input device 5 (keyboard, “mouse”). To simplify and unify the procedures for data entry, the system provides the input wizard expert assessments, which displays on the display 9 of the client computer queries about the required values of the predictable risk factor. Stored in the database 58, the expert forecasts are used for the correction matrices behavior risk factors, formed in a software module 57.2. Matrix behavior risk factors are compared with the values of the expert predictions of risk factors and adjusted by the algorithm embedded in the software module 57.

In the calculation of risk factors form and quickly memorize the results of calculation scenarios and scales in the server's RAM (60). Remember the corrected matrix behavior risk factors, where each interval to calculate the weights is mapped to its relative weight (probability) - thus, a tree of the forecast of the risk factor. Matrix behavior risk factors are also stored in the data Bank 59 subsystem 44. The data from the server RAM (60) are automatically transferred to the subsystem analysis (45). Also from subsystem 44 in the reporting (47) in automatic mode, data is transmitted from the data Bank of matrices behavior risk factors (59).

In the analysis subsystem 45 data from subsystems 42 and V automatically transferred to the software module forming combinations of triples (61), implemented in RAM on the server, using the microprocessor, the server produces many combinations of triples (option portfolio management, risk factor, initial setting). The generated data is transmitted and stored in the data Bank of the combinations of triples (62)and automatically transferred to a software module (63), using the microprocessor in the server for each of the combinations of triples according to the standard formula calculation of the debt indicators are calculated matrices debt indicators (cash flow debt service, and cash flows for the repayment of debt, cash flow, fundraising and so on) for each day of the calculation period risk. The calculated matrix of the debt indicators are stored in RAM on the server and automatically transferred to the subsystem calculate risk (46).

Information about the matrices debt indicators coming in the automatic mode of the subsystem 45, is stored in the server RAM (64), as well as in the data Bank analysis (68). The stored data is transmitted to the software modules of the subsystem(69, 70, 71).

Based on the data stored in the server RAM (64)subsystem in the automatic mode by the microprocessor, the server calculates risk management options portfoliomanager instruments on debt indicators, implemented in software module (69), implemented in the server RAM. The result of the calculation is a matrix of risks, which is automatically sent to and stored in a Bank store the output (67).

Based on the data stored in the server RAM (64), at the request of the operator by means of the microprocessor of the server software module discounted/aerovane indicators (71), implemented in the server RAM is the calculation of the present values of the debt indicators. For settlements also used data on the date to which the conversion, and the characteristics of the discounts/Airbuses capital. These data are entered by the system operator manually using standard input devices 5 (keyboard, mouse). To manually enter data into the system, subsystem 46 provides a wizard parameters discounting/airmusic, which displays on the display 9 of the client computer queries about the necessary settings, takes input operator data and sends it to the data Bank shall/airmusic capital (66). In the calculations, are formed discounted/aerovane value of debt indicators, which are automatically routed and stored in a Bank of storage in the output data (67).

Based on the data stored in the server RAM (64), at the request of the operator by means of the microprocessor of the server software module checks for compliance with specified constraints (70), implemented in the server RAM, checks debt indicators for compliance with specified constraints. For the inspection also used data on the given constraints. These data are entered by the system operator manually using standard input devices 5 (keyboard, mouse). To manually enter data into the system in the subsystem 46 provides a wizard parameters restrictions that displays on the display 9 of the client computer queries about the necessary settings, takes input operator data and sends it to a database of predefined constraints (65). In the calculations, are formed discounted/aerovane value of debt indicators, which are automatically routed and stored in a Bank store the output (67).

The discounted/aerovane performance and conformance to specified constraints are not binding. Their implementation is made only in case the instructions of the operator.

The information saved in the Bank to store the output (67), arrives in programs the first comparison module management options (72). A program module, a comparison of management options implemented in the server's RAM by the microprocessor of the server based on the characteristics stored in the data Bank 67 (risk assessments, matrix of compliance with the restrictions and discounted/aerovane debt indicators), brute force is the ranking of management options. The choice of measure that is used for ranking, by the operator, upon request by the system.

The result of this stage of the risk calculation is the list of ranked options portfolio management of financial assets, which is stored in RAM on the server and transmitted to the reporting (47). Also from subsystem 46 in the reporting in the automatic mode, data is transmitted from the data Bank analysis (68).

In reporting, (47) generate reports for the various portfolio management under various sections on the basis of data obtained at various stages of system operation and automatically sent to the module 47 after each stage of the system operation. Module 47 allows the conversion of incoming information (data) in a graphical or tabular presentation (reporting) and output the received reports to screen, printer or other output device on the O.

Input module 47 in automatic mode enters the following information: data on options for the management of a portfolio of financial instruments of the Bank's data management options portfolio (53) - cash flows for each of the management options, data matrices behavior risk factors from the data Bank of results of calculation scenarios and scales (59), data matrix, debt indicators, the relevant options from the database analysis (68), the list of ranked options portfolio management of financial assets of the subsystem calculate risk (46).

The system operator provides a wide range of choice of construction method and dataset used to build reports.

To reflect the results of operation of the system can be used all available and known display means. These may be related tables, graphs, light and sound signals, software, information, service, or other hints, displaying processes in the dynamics of their behavior on the monitor, etc.

On the basis of the reports received at the stage of reporting, the system operator “RISK 1” selects the control option, which is the most appropriate imposed limitations and has the lowest values of risks. For decision making the system operator ISOE is eshet the following information, formed in the form of reporting forms: calculated at the stage of calculation of risk characteristics for each of the management options and ranking of alternatives portfolio management.

In the above-described steps, the system operator “RISK 1” selects the best option portfolio management. After that, data about the selected version control is entered into the subsystem structure of the portfolio, that is changing the original structure of the portfolio.

Thus, the device system “RISK 1” in accordance with the present invention to make predictive assessments of financial risks and the management of a portfolio of financial instruments to minimize the risks. In addition to the known methods of analysis in the “RISK 1” include: widening the spectrum of possible scenarios for the behavior of risk factors by introducing into the base of evaluation of a set of expert change scenarios risk factors that allows you to assess the risks for cases where the distribution of risk factors is not normal; provide automated formation of different options portfolio management; calculation of various types of risk.

The following examples illustrate the process and results system “RISK 1”, implements the present invention.

Example:

The portfolio is aesica consists of two instruments with the following characteristics:

1. Tool And

Discount short-term bond

The number of outstanding instruments: 250 000 pieces

Price: 84

Nominal value: 100

Currency: Rubles

Publication date: 04.09.02

Maturity date: 05.09.03

2. Tool

Credit

The amount received on the loan: 200 000 000 US $

Currency: US Dollars

Date of raising funds for loan: 04.09.02

The maturity date of the loan: 05.09.05

The borrower must choose one of two options portfolio management, which would have led to reduced financial risk of the borrower:

Option 1:

The operation of the partial early repayment of the tool And

Date: 12.02.03

Quantity: 100,000 pieces

The transaction price depends on the risk factor “Interest rate”

Option 2:

The operation of the partial early repayment of the tool In

Redemption date: 15.12.03

The amount of maturity: 100 000 000

Currency: US Dollars

In addition, the borrower is necessary that the amount of debt in its portfolio would not exceed the value of 6 500 000 000 rubles.

System operation:

System via the display (9) requests the data about the initial state of a portfolio of financial instruments. Data about the current state of the portfolio and payments on instruments portfolio are recorded in databases (49) manually using standard input devices (5 or using a device receiving data (6) from external data sources. The Bank data storage instruments (49.1) downloads data about the current state of the portfolio of the borrower:

1. Tool And

Discount short-term bond

The number of outstanding instruments: 250 000 pieces

Price: 84

Nominal value: 100

Currency: Rubles

Publication date: 04.09.02

Maturity date: 05.09.03

2. Tool

Credit

The amount received on the loan: 200 000 000 US $

Currency: US Dollars

Date of raising funds for loan: 04.09.02

The maturity date of the loan: 05.09.05

A program module, calculate the initial payment options portfolio (48.2) based on the obtained characteristics are determined by the operations tools (initial settings payment flows), that is:

The instrument And date of transaction host (04.09.02), the number of outstanding instruments (250 000), the transaction price allocation (84 rubles), currency (the ruble), the transaction date maturity (05.09.03), the number of redeemable instruments (250 000), the price of redemption ($100).

Symbol: the transaction date of a loan (04.09.02), the amount of borrowing (200 000 000 USD), the currency (the US dollar), the transaction date maturity (05.09.05), the amount of repayment (200 000 000 USD).

Data is stored in the Bank portfolio data tools (49.2). Data on portfolio transferred from the Bank portfolio data (49.2.) in the software module is the formation of initial parameters for statistical calculations (50), which records data on the dependence of some characteristics of the tools from risk factors. In this example, the threads on the tool depend on the risk factor “U.S. Dollar”.

Next, the system continues in the subsystem of formation control options (42). The data from the data Bank 49 subsystem 41 received in a software module forming the management options (51) subsystem 42. Based on this information and the information (dates and amounts of transactions for changes in the portfolio structure) from external data sources in a software module (51) is formed options portfolio management. In this case, the software module forming the management options (51) are formed two options for the portfolio management of the borrower:

Option 1:

The operation of the partial early repayment of the tool And

Date: 12.02.03

Quantity: 100,000 pieces

The transaction price depends on the risk factor “Interest rate”

Option 2:

The operation of the partial early repayment of the tool In

Redemption date: 15.12.03

The amount of maturity: 100 000 000

Currency: US Dollars

The amount of repayment in rubles depends on the risk factor “U.S. dollar”

The entered data are stored in random access memory (52), and then stored in the data Bank management options (53).

Next, after passing this the surface of the forming structure of the portfolio and the options portfolio management system operation goes into the step of calculating statistical characteristics, which is implemented in the subsystem calculate the statistical characteristics of (43). From external data sources (3) are imported historical data on the two above-mentioned risk factors:

1. US dollar

2. Interest rate

A program module, the calculation of the statistical characteristics of (54) is:

• - calculation of the mathematical average is calculated by the formula:

whereis the mathematical average of the risk factors

x_{i}is the i-th historical monitoring by risk factor,

n is the number of observations in the historical range of risk factor.

The risk factor “U.S. Dollar” mathematical average is 27.98;

• - calculation of the RMS according to the formula:

where δ_{x}is the standard deviation for the risk factor,

is the mathematical average of the risk factors

x_{i}is the i-th historical monitoring by risk factor,

n is the number of observations in the historical range of risk factor.

RMS risk factor, “the Dollar is equal to 2.40;

• - calculation of the correlation characteristics (correlation of the two risk factors, the autocovariance). The formula for the correlation of two risk factors:

where corr(x,y) - adjusted ient correlation of the two risk factors

δ_{x}that δ_{y}is the standard deviation of the risk factors

,is the mathematical average risk factors

x_{i}, y_{i}is i-Tye historical observations on risk factors

n is the number of observations in the historical range of risk factor.

Then the calculated statistical characteristics,that δ_{x}that δ_{y}, Corr(x, y) are sent to the data Bank by the values of the statistical units (56).

Next, the operation of the system continues in the subsystem calculate scenarios and weights (44), where the software module random simulation values (57.1.) for each vector on the basis of historical data and statistical characteristics calculated values of risk factors that are passed to the software module forming matrix predictions (57.2), which are formed of a matrix of behavioral risk factors. An example of the generated matrix of forecast risk factor “U.S. Dollar” are presented in the table:

The probability (weight) | The values of the risk factor (US dollar) in date | ||||

04.09.2002 | 24.09.2002 | 14.10.2002 | 03.11.2002 | ||

Scenario 1 | 0.0465 | 31.6000 | 31.4207 | 31.2855 | 31.1508 |

Scenario 2 | 0.0844 | 31.6000 | 31.4207 | 31.2855 | 31.5809 |

Scenario 3 | 0.0877 | 31.6000 | 31.4207 | 31.7175 | 31.5376 |

Scenario 4 | 0.1501 | 31.6000 | 31.4207 | 31.7175 | 32.0754 |

Scenario 5 | 0.0826 | 31.6000 | 31.9565 | 31.7753 | 31.6385 |

Scenario 6 | 0.1502 | 31.6000 | 31.9565 | 31.7753 | 32.0754 |

Scenario 7 | 0.1469 | 31.6000 | 31.9565 | 32.3171 | 32.1338 |

Scenario 8 | 0.2516 | 31.6000 | 31.9565 | 32.3171 | 32.6818 |

The risk factor “Interest rate” also, the forecast.

Later in the database expert forecasts of changes in risk factors (58) from external data sources (3) are entered numerical data expert predictive values of risk factors. Example values of the numerical values of e is startlogo forecast risk factor “U.S. Dollar” are presented in the table:

The probability (weight) | The values of the risk factor (US dollar) in date | |||||

04.09.2002 | 01.01.2003 | 01.01.2004 | 01.01.2005 | 01.01.2006 | ||

Scenario 1 | 0.4000 | 31.6000 | 31.9700 | 33.3000 | 33.6900 | 33.6700 |

Scenario 2 | 0.4000 | 31.6000 | 31.5200 | 33.0400 | 34.7800 | 36.5400 |

Scenario 3 | 0.2000 | 31.6000 | 50.5900 | 65.1000 | 80.1900 | 98.2100 |

Then, on the basis of expert forecasts of changes in risk factors “US Dollar” and “Interest rate” from the Bank data of 58 matrix of conduct these risk factors are adjusted in software module (57).

Correction matrices behavior risk factors is one of the following methods:

- Embedding short tree at the initial step

Interpolation of long wood on the last step.

- Extrapolation of long tree short or using the black-Scholes

As an example of the calculation results using correct and matrix behavior risk factor “U.S. Dollar” method of embedding this matrix in the first layer long wood (matrix behavior risk factor “U.S. Dollar”, based on expert judgement).

Corrected the behavior matrix of risk factor “U.S. Dollar” looks as follows:

The probability (weight) | The values of the risk factor (US dollar) in date | ||||||

04.09.2002 | 03.11.2002 | 01.01.2003 | 01.01.2004 | 01.01.2005 | 01.01.2006 | ||

Scenario 1 | 0.4000 | 31.6000 | 32.0692 | 31.9700 | 33.3000 | 33.6900 | 33.6700 |

Scenario 2 | 0.6000 | 31.6000 | 32.0692 | 31.5200 | 33.0400 | 34.7800 | 36.5400 |

The algorithm embodied in a method of embedding a short tree in the first layer long, the Association provides several scenarios matrix behavior risk factors in one. This procedure depends on the choice of intervals partitioning the values of the risk factor on the terminal layer short tree (last date matrix behavior risk factor) and on the second layer of long wood (second date matrix behavior risk factor, based on expert judgement).

The partitioning is carried out by ledouxnebria.

Let v_{1}<...<v_{n}values (atoms) of the risk factor on the terminal layer short tree with_{1}<...<c_{k}values (atoms) of the risk factor on the second layer of a long tree.

An appropriate interval partitioning [a_{i}b_{i}) are selected so that each of them contains exactly one corresponding with_{i}and extreme points (a and b in the previous notation) lay so that the intervals partitioning covered the atoms v_{1}<...<v_{n}. If each interval of the partition contains at least one atom ν•then the probability that any one of the long branches of the tree after changing the pairing will not be reset. If the interval [a_{i}b_{i}does not contain atoms ν•then in the pair “killed” by zeroing the probabilities of all paths that go on the first layer of the node with_{i}.

As standard split system of pairwise disjoint intervals is proposed: the endpoints of the intervals of the partition to take the midpoints of the segments [c_{i}c_{i+1}]; the extreme points a and b to set coincident with atoms ν_{1}and ν_{n}.

Matrix behavior risk factors “US Dollar” and “Interest rate”, corrected by the method of embedding a short tree in the first layer long do online is Amati (60), and then in the analysis subsystem (45) and in the data Bank behavior risk factors (59).

In software module selection and formation of triples (61) receives information on options for the portfolio management of the borrower (Option 1 and Option 2), models of behavior risk factors “US Dollar” and “Interest rate” and the installation, sampling and formation of triples (Option 1 - “Interest rate” and the unit risk factor, Option 2 - “Dollar and unit risk factor). The generated triples are stored in the data Bank triples (62).

Then three arrive in software analysis module (63), where on the basis of the received information is the calculation of the matrices debt indicators for each date during the entire period of risk calculation. The calculated matrix of the debt indicators are stored in RAM on the server and are automatically transferred in the subsystem calculate risk (46). Since operations management options Option 1 and Option 2 depend on the matrices behavior risk factors, which are presented in the form of scenarios with a probability of implementation for each option control will be calculated for several scenarios of debt indicators probability of realization. For example, Option 2 will be presented several scenarios of behavior of the debt indicator, ka is the principal debt:

Probability | The value of the debt indicator (principal) date | ||||||||

M | ... | M | ... | M | ... | M | ... | ||

Scenario 1 | 0.4000 | 6 415 336 209.49 | ... | 6 425 758 703.73 | ... | 6 415 336 209.49 | ... | 6 436 863 013.70 | ... |

Scenario 2 | 0.6000 | 6 326 861 633.22 | ... | 6 384 572 263.05 | ... | 6 326 861 633.22 | ... | 6 349 986 301.37 | ... |

Next, the resulting matrix be received by the Bank data matrices and options (64) subsystem calculate risk (46). From the database 64 information comes in the software module of calculation of risk, where is the calculation of such characteristics as:

• - the expected value of the debt indicator. Is calculated by the formula:

where Ex is the expectation, the expected value of the debt indicator,

p_{j}- the probability of the j-th scenario of the debt indicator,

x_{j}- the value of debt show the La on the j-th scenario,

m is the number of scenarios.

• - standard deviation of the debt ratio. Is calculated by the formula:

where δ_{x}- the standard deviation of the debt indicator,

Ex - the expectation, the expected value of the debt indicator,

p_{j}- the probability of the j-th scenario of the debt indicator,

x_{j}- the value of the debt indicator on the j-th scenario,

m is the number of scenarios.

So as a result of calculations in the software module calculation (69) both versions portfolio management is a matrix of risks and transmitted to the Bank data storage (67):

The risk of harakteristika | Source control | Option 1 | Option 2 |

The mathematical expectation of the variable “primary duty” | 6 620 726 027,40 | 5 630 547 019,50 | 3 310 363 013,70 |

MSE index “primary duty” | 26 884 931,50 | 20 954 254,80 | 13 442 465,70 |

In addition to calculating risk characteristics, the calculation of risk is calculated given the debt indicators, and checking for compliance with the restrictions. Consider the validation sample debt indicators variant the control limits.

The Bank data set parameters restrictions” (65) are the limit values in the debt indicators. Thus, according to the conditions of example, the main debt management options must not exceed the amount of 6 500 000 000 rubles. From a Bank of predefined constraints (65) this restriction together with information on debt indicators from the data Bank of the matrices and the options passed to the software module constraint checks (70)where the checks and send test results to the Bank to store the output (67). The Bank store the output (67) also contains information calculated in the software module of calculation of risk matrices risk.

Information matrices of risk management options and the test results are transferred from Bank storage (67) in the block comparison management options (72), where according to the criteria of minimizing the risks and compliance with limits equal control options:

- The smallest expected value of principal: Option 2.

Lowest RMS (risk): Option 2

- To comply with the limits: Option 1 and Option 2.

Simultaneously with the data on options for the control of other modules in the module reporting 47 is transmitted to the ranked list of management options. Based on the ranked list of management options, a report is generated, focusing nekotorye the user decides on the implementation of the management option. Other reports generated in the module 47 are minor.

The best option portfolio management of the borrower acknowledges Option 2, which is ranked in the list of management options generated by the system, occupies the first place.

1. Automated information and analytical system of evaluation of financial risks, which contains at least one operator workplace-Analytics, including the input device, the device receiving data on financial instruments, data about the main characteristics of financial instruments, information on transactions with financial instruments, data on historical values of risk factors, intermediate storage device and the data processing and output data, while the operator's workstation analyst connected through the communication line to the server containing the means of creating a set of data about the current state of the portfolio of financial instruments and payments on instruments portfolio; means forming set options for the management of a portfolio of financial instruments; the instrument of formation of a data Bank and calculation of statistical characteristics of the historical values of risk factors; a means to create a data Bank according to expert forecasts and the projections on risk factors; means of calculating matrices debt is x indicators the means of calculation of risks and the means of reporting, and the means of creating a set of data about the current state of the portfolio of financial instruments and payments on instruments portfolio, the tool will generate a set of options for the management of a portfolio of financial instruments, the means of calculation of the matrices debt indicators tool risk calculation consistently associated with a means of reporting, the second output means of generating a set of data about the current state of the portfolio of financial instruments and payments under the instruments of the portfolio is the entrance means for the formation of a data Bank and calculation of statistical characteristics of the historical values of the risk factors connected with the tool to create a data Bank according to expert forecasts and the projections on risk factors, output which is the second input means of the calculation of the matrices in debt indicators.

2. Automated information and analytical system of evaluation of financial risks according to claim 1, characterized in that the means of forming a data Bank according to expert forecasts and the projections on risk factors associated with the means of reporting, the output of which through the intermediate storage device and data processing is connected to the output device.

3. Automated system p the claim 1 or 2, characterized in that the means forming the data set on the current state of the portfolio of financial instruments and payments on instruments portfolio is intended to implement the subsystem structure of the portfolio, which includes: module job portfolio structure, consisting of module assignments instrumental portfolio structure and module calculate the initial parameters of the cash flows on portfolio data Bank portfolio structure, consisting of a data Bank instruments and Bank portfolio data tools, as well as the module of generation of initial parameters for statistical calculations, consisting of a module forming parameters for statistical calculations, module parameters forming the end of the calculations and module parameters forming risk.

4. The automated system according to claim 3, characterized in that the means of creating a set of options for the management of a portfolio of financial instruments is intended to implement the subsystem formation of variants of portfolio management, which includes the module of generation options portfolio management associated with database management options portfolio.

5. The automated system according to claim 4, characterized in that the means forming the data Bank and the calculation of the statistical characteristics of the historical values of factors R is ska is intended to implement the subsystem calculate the statistical characteristics of risk factors, includes a module to calculate statistical values associated with a data Bank of historical values of the risk factors and the Bank storing the statistical values.

6. The automated system according to claim 5, characterized in that the means of forming a data Bank according to expert forecasts and the projections on risk factors is intended to implement the subsystem calculate scenarios and scales of risk factors, including calculation module behavior scenarios risk factors associated with the database expert forecasts, and the Bank data matrices behavior risk factors.

7. The automated system according to claim 6, characterized in that the means of calculation of the matrices debt indicators is intended to implement the subsystem analysis, which includes serially connected module forming combinations of triples (option portfolio management, risk factor, initial setting), the database storing combinations of triples and the analysis module.

8. The automated system according to claim 7, characterized in that the tool risk calculation is intended for the subsystem implementation of risk calculation, which includes serially connected module storage matrices debt indicators and management options, the module of calculation of risk, the Bank will store the output options and the comparison module options.

9. The automated system of claim 8, wherein the subsystem risk calculation further comprises a database of predefined constraints and the module checks for restrictions connected with the storage module matrices debt indicators and management options and Bank store the output options.

10. The automated system of claim 8 or 9, characterized in that the subsystem risk calculation further comprises a data Bank discounting/airmusic capital and module discounted/aerovane performance comparison of options connected with the storage module matrices debt indicators and management options and Bank store the output options.

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FIELD: formation of payment documents.

SUBSTANCE: the information meaningful for the payment document is introduced in the computer of the financial settlements and check-out center, the payment document is formed in the form a text and the first dot-and-dash code line and introduced in the electronic data base, the document is displayed for payment to the payer, the payer introduces the information on the quantity of consumed resources and the sum of payments to the document according to the acting tariff rates, these data are introduced in the cash register of the payment reception center with the date of payment, types and sums of payments, these data and the second dot-and-dash code line with these data on the document are represented by means of the cash register, it is sent to the financial settlements and check-out center, the first and second dot-and-dash code lines are read out, the information is compared with the electronic base, entered together with the information on reception of the payment in its electronic data base.

EFFECT: automated formation of documents with due account made for payments determined by the floor space, quantity of people living there and the quantity of the consumed resources.

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FIELD: measurement technology.

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FIELD: formation of payment documents.

SUBSTANCE: the information meaningful for the payment document is introduced in the computer of the financial settlements and check-out center, the payment document is formed in the form a text and the first dot-and-dash code line and introduced in the electronic data base, the document is displayed for payment to the payer, the payer introduces the information on the quantity of consumed resources and the sum of payments to the document according to the acting tariff rates, these data are introduced in the cash register of the payment reception center with the date of payment, types and sums of payments, these data and the second dot-and-dash code line with these data on the document are represented by means of the cash register, it is sent to the financial settlements and check-out center, the first and second dot-and-dash code lines are read out, the information is compared with the electronic base, entered together with the information on reception of the payment in its electronic data base.

EFFECT: automated formation of documents with due account made for payments determined by the floor space, quantity of people living there and the quantity of the consumed resources.

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FIELD: formation of payment documents.

SUBSTANCE: the information meaningful for the payment document is introduced in the computer of the financial settlements and check-out center, the payment document is formed in the form a text and the first dot-and-dash code line and introduced in the electronic data base, the document is displayed for payment to the payer, the payer introduces the information on the quantity of consumed resources and the sum of payments to the document according to the acting tariff rates, these data are introduced in the cash register of the payment reception center with the date of payment, types and sums of payments, these data and the second dot-and-dash code line with these data on the document are represented by means of the cash register, it is sent to the financial settlements and check-out center, the first and second dot-and-dash code lines are read out, the information is compared with the electronic base, entered together with the information on reception of the payment in its electronic data base.

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