LISTED COMPANIES

FIELD OF THE DISCLOSURE

[0001] The present disclosure generally relates to a method and a system for providing financial ^' forecasting of a listed company, and more particularly, to a method and a system for providing financial forecasting of a listed company based on financial forecast models that may be manipulated.

BACKGROUND OF THE DISCLOSURE

[0002] It is important these days to have an adequate understanding about business entities or companies or any business organization before making any financial investment. One of the primary requirements for making an informed investment decision is not only the ease of access to historical financial data on the company in question, but also have the ability to assess future financial performance of the company. The reliance on historical data to drive future financial forecasts, requires a high level of accuracy and integrity in the historical data set as well as transparency in the forecasting methodology applied to each historical line item. This ensures that a timely and accurate financial decision may be made within the sohere of ODDortunitv.

[0003] Existing tools and corporate analytics systems predominantly deliver analytical capability on merely historical financial performance of companies, with little to no capability to run elaborate financial forecasts and estimates, in a well structured and transparent fashion. Such existing solutions and tools also have limited capability to generate financial forecast models related to companies without intensive user interference and analytical throughput. More specifically, such tools may also have limited capabilities to allow the user to manipulate the financial forecast models for providing a financial forecast of the company. Thus, existing tools require time consuming research inputs from their users.

SUMMARY OF THE DISCLOSURE [0004] In view of the foregoing disadvantages inherent in the prior-art, the ' general purpose of the present disclosure is to provide a method and a system providing financial forecasting on a range of stock exchange listed companies that is configured to include all advantages of the prior art and to overcome the drawbacks inherent in the prior art offering some added advantages.

[0005] An object of the present disclosure is to provide an advanced tool for providing financial forecast model on a publicly listed company, with the view to deliver forecast manipulation capability, via the software interface, to the user; in order for the user to adjust the future expected financial performance of the company based on their understanding and expectation of future performance on a series of underlying variables that impact the performance of the company in question.

[0006] Another object of the present disclosure is to provide a tool for providing financial forecasts on a company in a user friendly manner.

[0007] Yet another object of the present disclosure is to provide a tool, which includes personalized features that enable a user to select stock exchange listed companies of their interest in a manner suited to their requirements. [0008] To achieve the above objective, in one aspect, the present disclosure provides a method for providing financial forecasting on a listed company. The method includes receiving name of a company from a user from a list of companies made available to the user. Further, the method includes locating a financial forecast model corresponding to the requested company. The financial forecast model is capable of being manipulated by the user and the financial forecast model is capable of being utilized for determining future expected financial performance of the company. Furthermore, the method includes providing the financial forecast of the company based on the forecasting capability of the financial forecast model. [0009] In another aspect, the present disclosure provides a computer program product embodied within a computer readable medium. The computer program product encodes a computer program of instructions for executing a computer process for providing financial forecasting on a range of stock exchange listed companies. The computer process includes receiving name of a company from a user from a. list of companies made available to the user. Further, the computer process includes locating a financial forecast model corresponding to the company requested, wherein the financial forecast model is capable of being manipulated by the user, and wherein the financial forecast model is capable of being utilized for determining future expected financial performance of the company. Furthermore, the computer process includes providing the financial forecast of the company based on the forecasting capability of the financial forecast model. [0010] In yet another aspect, the present disclosure provides a system for financial forecasting on a listed company. The system includes a receiving module configured to receive name of a company from a user from a list of companies made available to the user. Further, the system includes a locating module configured to locate a financial forecast model corresponding to the company, wherein the financial forecast model capable of being manipulated by the user, and wherein the financial forecast model is capable of being utilized for determining future expected financial performance of the company. Further, the system includes an application module configured to provide the financials of the company based on the financial forecast model and the historical data corresponding to the company.

BRIEF DESCRIPTION OF THE DRAWINGS

[001 1] The advantages and features of the present disclosure will become better understood with reference to the following detailed description and claims taken in conjunction with the accompanying drawing, in which:

[0012] FIG 1 is a flow diagram of a method for providing financial forecasting of a listed company, according to an embodiment of the present disclosure;

[0013] FIG. 2 is a flow diagram of a method for generating a financial forecast model, according to an embodiment of the present disclosure; [0014] FJG 3 is a block diagram of a system for providing financial forecasting of a listed company, according to another embodiment of the present disclosure; [0015] FIG 4 is a snapshot depicting validation of the collected data and notification of the user in case of violation ;

[0016] FIG. 5 is a flow diagram, which explains the process of validation of the collected data;

[0017] FIG 6 is a snapshot depicting how a user may change assumptions of a parameter in the method 100;

[0018] FIGS. 7 and 8 are snapshots depicting how a user may view the financial statements as released by the company;

[0019] FIG. 9 is a snapshot depicting a summary report generated by method 100; [0020] FIGS. 10-13 are snapshots depicting how a user may be provided with an option of summary report either based on predetermined estimates or based on his/her estimates;

[0021] FIG. 14 is a snapshot depicting company screening based on a screening criteria;

[0022] FIG 15 is a snapshot depicting a peer group analysis of companies;

[0023] FIG. 16 is a snapshot depicting analysis of impact of a change in an independent variable on a given dependent variable in a created scenario;

[0024] FIGS. 17 and 18 are snapshots depicting summarizing of a comparison between companies in particular portfolios/sectors/indices/regions; [0025] FIG. 19 depicts the logical diagram of the system 200 of FIG 3; and [0026] FIG. 20 diagram depicts the architecture diagram of the system 200 of FIG 3.

DETAILED DESCRIPTION OF THE DISCLOSURE

[0027] The exemplary embodiments described herein detail for illustrative purposes are subject to many variations in structure and design. It should be emphasized, however, that the present disclosure is not limited to a particular method and system for providing financial forecasting on a range of stock exchanged listed companies as shown and described. It is understood that various omissions and substitutions of equivalents are contemplated as circumstances may suggest or render expedient, but these are intended to cover the application or implementation without departing from the spirit or scope of the claims of the present disclosure. Also, it is to be understood that the phraseology and terminology used herein is for the purpose of description and should not be regarded as limiting.

[0028] The use of terms "including," "comprising," or "having" and variations thereof herein is meant to encompass the items listed thereafter and equivalents thereof as well as additional items. Further, the terms, "a" and "an" herein do not denote a limitation of quantity, but rather denote the presence of at least one of the referenced item.

[0029] The present disclosure provides a method and a system for providing financial forecasting on a range of stock exchange listed companies. The term financial as mentioned herein includes both historical and forecasted figures of key indicators of the company. Suitable example of the key indicators may include, but not limited to, financial ratios, fixed working capital, income/revenues, profit/ loss, net interest income, and the like. More specifically, the present disclosure provides a method and a system for providing financial forecasting on a range of stock exchange listed companies based on financial forecast models that may be manipulated by the user. It should be understood that the term 'forecasting' as used throughout the present disclosure relates to predicting future key performance indicators of a company. The term 'company' as described herein may refer to a public limited company (i.e., stock exchange listed company). However, such definition of the term 'company' should not be construed as a limitation to the present disclosure. Accordingly, the method and the system of the present disclosure may also be applicable for other entities, such as private limited companies and limited liability partnership firms. The method and the system of the present disclosure will now be exDlained with reference to FIGS. 1-3.

[0030] As shown in FIG 1, a method 100 for providing financial forecasting of a listed company includes receiving name of a company from a user, at block 10. The user as mentioned herein niay be a person interested in accessing financials of the company. Accordingly, a list of companies made available to the user, and the user may prompt the name of the company for which he desires the financials, at block 10. More specifically, the user may enter the name of the company by inputting the name of the company through an input device (not shown), such as a keyboard, a touchpad, or other similar inputting devices.

[0031] Thereafter, the method 100 includes locating a financial forecast model corresponding to the company, at block 20. It will be apparent to a person skilled in the art that the term 'financial forecast model' as mentioned herein refers to a set of relational parameters, which may be used to forecast key financial indicators of a company. Further, it will be apparent to a person skilled in the art that the financial forecast model may be based on a plurality of assumptions. Exemplary set of financial parameters of the financial models of the present disclosure, may include, but not limited to, 1. EBIT Margin = EBIT/ Total Revenue

2. Gross Debt to Assets = (Long Term Debt +,Short Term Debt)/ Total Assets

3. RoCE (%) = EBIT/ Avg, Capital Employed

4. Debt Service Cover = EBITDA/ (Interest +Debt Repayment) However, it should be clearly understood that the set of financial parameters as enlisted above should not be construed as a limitation to the present disclosure. Accordingly, the financial forecast model may include additional set of parameters and variables. [0032] More specifically, the method 100 may include retrieving the financial forecast model corresponding to the company from a plurality of financial forecast models stored in a database, and more particularly, uploaded in a database. [0033] In one embodiment of the present disclosure, the method 100 may include generating the financial forecast model, uploading the financial forecast model in the database, and then retrieving the generated financial forecast model, at block 20. The generation of the financial forecast model may now be explained with reference to FIG 2. [0034] As shown in FIG 2, the generation of the financial forecast model may include collecting data corresponding to the company, at block 32. The data may be collected from primary sources or secondary sources. Suitable examples of the primary sources may include interaction of an analyst from officials of the company Suitable examples of the secondary sources include collection of the data from sources, such as company databases, annual reports of the companies, websites, and other similar sources. Further, the collecting of the data corresponding to the company may include collecting as reported data of the company. In one embodiment, the collecting data corresponding to the company comprises collecting analyst derived data.

. [0035] After the collection of the data corresponding to the company, the method of generating the financial forecast model includes verifying the data, at block 34. The verification of the data may involve corroborating the collected data to locate inconsistencies and errors. The step of verification of the data, at block 34, may be performed by the analyst or may also be computer implemented. For example, a computer implemented code may ,be initiated on the collected data to determine the inconsistencies and the errors.

[0036] After the verification of the collected data, the method of generating financial forecast model includes analyzing the collected data to derive key pointers, at block 36. The term analyzing the data as mentioned herein may refer to deriving insights from the collected data about the company and the inter-relationship of these data points and structuring these insights in form of key pointers and forecasting formulae. Again, the analysis may be done by the analyst or may be computer [0032] More specifically, the method 100 may include retrieving the financial forecast model corresponding to the company from a plurality of financial forecast models stored in a database, and more particularly, uploaded in a database. [0033] In one embodiment of the present disclosure, the method 100 may include generating the financial forecast model, uploading the financial forecast model in the database, and then retrieving the generated financial forecast model, at block 20. The generation of the financial forecast model may now be explained with reference to FIG. 2. [0034] As shown in FIG 2, the generation of the financial forecast model may include collecting data corresponding to the company, at block 32. The data may be collected from primary sources or secondary sources. Suitable examples of the primary sources may include interaction of an analyst from officials of the company. Suitable examples of the secondary sources include collection of the data from sources, such as company databases, annual reports of the companies, websites, and other similar sources. Further, the collecting of the data corresponding to the company may include collecting as reported data of the company. In one embodiment, the collecting data corresponding to the company comprises collecting analyst derived data. [Please provide input on analyst derived data.]

[0035] After the collection of the data corresponding to the company, the method of generating the financial forecast model includes verifying the data, at block 34. The verification of the data may involve corroborating the collected data to locate inconsistencies and errors. The step of verification of the data, at block 34, may be · performed by the analyst or may also be computer implemented. For example, a computer implemented code may be initiated on the collected data to determine the inconsistencies and the errors. [0036] After the verification of the collected data, the method of generating financial forecast model includes analyzing the collected data to derive key pointers, at block 36. The term analyzing the data as mentioned herein may refer to deriving insights from the collected data about the company and the inter-relationship of these data points and structuring these insights in form of key pointers and forecasting

7 formulae. Again, the analysis may be done by the analyst or may be computer implemented. For example, the data may be interpreted to arrive at key pointers, such as income, expenses, depreciation, liabilities, and other such key pointers. [0037] After the analysis of the data, at block 36, the method of generating the financial forecast model may include deducing the financial forecast model based on the analyzed data, at block 38. More specifically, the method may include inputting the key pointers derived at block 36 in the relational parameters in a forecasting sense to deduce the financial forecast model, at block 38.

[0038] The method 100 of the present disclosure may additionally include validating the financial forecast model. The validation of the financial forecast model ensures that the financial forecast model may be free from inconsistencies and reconciliation problems. The validation of the financial forecast model may be based on a plurality of predetermined integrity checks. The validation ensures that in case any of the values is wrongly inputted, the method 100 may not accept the value, and may intimate the user of such inconsistencies and discrepancies.

[0039] The validation of the collected data ensures total accuracy from an accounting perspective. Further, if the user makes any changes that violate the internal control parameters, these are clearly notified to the level of identification of cells where the violation exists. This mav be better understood bv referring to FIG. 4.

[0040] As shown in FIG. 4, if a user inputs any number in the Income Statement sheet of the application, then on clicking model verification tab 252, the user would be prompted a error message 255, such as, "Net interest income for FY2011 F does not tally with the items that make up the "Net Interest Income" figure.

[0041] Moreover, FIG. 5 depicts a flow diagram 257 which explains how the validation of the collected data works with respect to method 100. As shown in FIG. 5,· if the method 100 during the validation of the collected data passes the first check, then the forecast items in the data input sheet may be checked so that it matches the predetermined calculations (accounting checks) that we have defined in the database. Any violation in the number may be highlighted as error. Alternatively, if the method 100

8 during the validation of the collected data passes the second check, then the user may be allowed to upload the numbers to the central server which may be used as estimates anywhere in the application to run the valuation comparisons. [0042] Now referring again to FIG. 1, after the locating of the financial forecast model, the method 100 may include providing the financial forecast of the company based on the forecasting capability of the financial forecast model, at block 27.

[0043] It should be understood that the financial forecast model as described herein may be manipulated by the user. More specifically, each financial forecast model combines historical financial information with forecasting methodologies for individual variables to determine the future expected financial performance of the company, based on a plurality of forecast assumptions. Also, the user may be capable of changing at least one of a plurality of forecasting assumptions, on which the financial forecast model may be based, for manipulating the financial forecast model. Such manipulation feature provides the user an option of customizing the forecasting assumption according to his/ her choice. This is shown with reference to FIG 6.

[0044] As shown in FIG 6, the user may change these assumptions by right clicking on a parameter 260. A manipulated assumption 265 may then accepted by the method 100.

[0045] In one embodiment of the present disclosure, the method 100 may include viewing source of the collected data. Accordingly, the user may drill down to documents from where the collected data is sourced. Also, the user may download such data if required. This gives the user an option of quickly verifying the authenticity and integrity of the collected data, in terms of its sourcirig, by electing to view the source documents. For example, if the user intends to drill down to source of a key indicator, such as operating profit, then the user may be able to view the as reported financial statements of the company with the operating profit indicator highlighted. This viewing source of the collected data is as shown in FIGS. 7 and 8.

[0046] As shown in FIG 7, a user may view the financial statements as released by the company by referring to associated files section 300 on right hand side of

9 the application. The section 300 includes all source documents like annual reports and corporate presentations.

[0047] As shown in FIG 7 and FIG 8, a user may also "right click" on a particular cell in the application to retrieve the source document corresponding to the collected data. If the user clicks on the collected data, and selects drill-down to source option 310, it brings the user to the source document 320 with the specific data highlighted in yellow. [0048] In one embodiment of the present disclosure, the method 100 may further include generating analytical charts based on the financials of the company. In one embodiment of the present disclosure, the method 100 may include generating analytical charts may include generating charts based on a user defined criteria. More specifically, the method 100 may include reorganizing data about the key indicators, and thereafter using the data to prepare the analytical charts.

[0049] In yet another embodiment, the present disclosure provides generating summary reports using generated forecasts of method 100. Exemplary summary report is as shown in FIG. 9. The method may generate four kinds of reports: , Company Profile, One Pager Report, Two Pager Report, and Company Report. However, the generation of the aforementioned reports should not be construed as a limitation to the present disclosure.

[0050] Further, the method 100 gives an option to the user to generate the summary reports based on his her estimates or predetermined estimates. As shown in FIG. 10, the application provides the user with two options for each type of summary report. First, the application provides the user with an option of summary reports based on predetermined estimates 330. Second, the application provides the user with an option of summary report based on his/her estimates 335. If the user chooses the predetermined estimates 330 option, a summary report similar to that shown in FIG. 9 is generated.

[0051 ] If the user chooses the option of generating summary report based on his/her estimates, then the user may be allowed to manipulate any assumption. For example, the user may manipulate the Total Revenue Figure 340 as shown in FIG. 1 1 by changing Average Revenue per Minute in the financial forecast model sheet

1 Q corresponding to the Total Revenue Figure 340 from a figure 345 of 0.7 to a figure 350 of 55 NTS per minute as shown in FIG 12. The change may reflect in the summary report as shown by figure 355 in FIG 13. [0052] In yet another embodiment of the present disclosure, the method

100 may also include creating scenarios and view the companies that fall into the scenario. More specifically, the user may have an option of creating new scenarios based on plurality of filters available. This allows the user to view some of the key financial parameters associated with companies.

[0053] The company screening may rely on fundamental and valuation data, and may deliver a focused list of companies for the subscriber. The company screening as described herein may be better understood in conjunction with reference to FIG 14.

[0054] As shown in FIG. 14, the company screening may include a screening criteria section 375 and a list of companies 380.

[0055] In one embodiment of the present disclosure, the method 100 may further include performing a peer group analysis of the company. The peer group analysis may include comparing financials of the company to the financials of competitor companies. Further, the peer group analysis may include presenting the result of the comparison to the user. The peer group analysis may be shown with reference to FIG 15. [0056] In yet another embodiment of the present disclosure, the method

100 may include analyzing impact of a change in an independent variable on a given dependent variable in a created scenario. This analysis may be as shown in FIG 16.

[0057] As shown in FIG 16, a sensitivity detail section 400 presents the user with an option to change the independent variable. The analysis of the sensitivity is shown in the output grid section 410.

[0058] In addition, the method 100 also enables the user to summarize comparison between companies in particular portfolios/sectors/iridices/regions, which are under coverage of the firm for various parameters. The user may select companies,

11 forecast items, forecast periods for summarizing the comparison. The summarizing may be depicted by FIG. 17. The summary may be shown in FIG 18.

[0059] Further, the present disclosure provides a computer program product embodied within a computer readable medium. The computer program product encodes a computer program of instructions for executing a computer process to provide financial forecast of a listed company. The computer process includes receiving name of a company from a user from a list of companies made available to the user. Further, the computer process includes locating a financial forecast model corresponding to the company. The financial forecast model as described herein is similar to the financial forecast model described above. Accordingly, the financial forecast model is capable of being manipulated by the user, and wherein the financial forecast model is capable of being utilized for determining future expected financial performance of the company.-

[0060] · After, the location of the financial forecast model, the computer process includes providing the financials of the company based on the forecasting capability of the financial forecast model.

[0061] The computer process may further include generating the financial forecast model. The generating of the financial forecast model is similar to the generating of the financial forecast model as described above. Accordingly, the generating of the financial forecast model includes collecting data corresponding to the company. The collecting of the data corresponding to the company includes collecting as reported data of the company. In one embodiment of the present disclosure, the collecting data corresponding to the company comprises collecting analyst derived data. Thereafter, the computer process may include verifying the data, analyzing the collected data, and deducing the financial forecast model based on the analysis.

[0062] The computer process may further include validating the financial forecast model, the validating of the data based on a plurality of predetermined integrity checks, comprising of accounting and reconciliation checks. The validation may be similar to the validation described above with reference to FIG. 1. Further, the validation may include intimating the user based on the result of the validation.

12 [0063] Also, the computer process may include viewing source of a data element of the collected data-, wherein locating the financial forecast model comprising retrieving the model from a database of uploaded models.

[0064] In an embodiment of the present disclosure, the computer process may include screening companies based on investment criteria comprising one or more of sector, country, investment characteristics, and fundamental and valuation filters. Further, the computer process may include performing a peer group analysis comprising comparing financials of the company to the financials of competitor companies. The computer process may also include generating analytical charts based on the data of the company. The generation of analytical charts may include generating charts based on a user defined criteria.

[0065] In another aspect, the present disclosure provides a system for providing financial forecasting of a listed company. The system will be explained in details with reference to FIG .3. As shown in FIG. 3, the system 200 includes a receiving module 210 configured to receive name of a company from a user from a list of companies made available to the user. Further, the system 200 includes a locating module 230 coupled to the receiving module 210. The locating module 230 may be configured to locate a financial forecast model corresponding to the company in a database 235 having a plurality of uploaded financial forecast models. It should be understood that the financial forecast model may be capable of being manipulated by the user. Further, the financial forecast model is capable of being utilized for determining future expected financial performance of the company.

[0066] In one embodiment, the locating module 230 may also include a generating module 237 configured to generate the financial forecast model. More specifically, the generating module 237 may be configure to collect data corresponding to the company from primary and secondary sources using a collecting module 239, verify the data, analyze the collected data, and deduce the financial forecast model based on the analysis.

13 [0067] In addition, the system 200 includes an application module 240 coupled to the locating module 230. The application module 240 may be configured to provide the financials of the company based on the financial forecast model. [0068] The system 200 may further include a storage module (not shown in FIG 3), which may fulfill the storage requirement of the system 200. For example, the storage module may be configured to store the financial forecast model generated by the locating module 230. [0069] The system 200 may include a manipulating module (not shown) adapted to allow a user to change at least one of a plurality of forecasting assumptions for manipulating the financial forecast model.

[0070] The system 200 may furthermore include a validating module configured to validate the financial forecast model, wherein the validating of the financial forecast model is based on a plurality of predetermined integrity checks. The plurality of predetermined integrity checks are similar to the integrity checks described above.

[0071] The system 200 may additionally include a screening module (not shown) configured to screen companies based on investment criteria, such as, sector, country, investment characteristic and fundamental and valuation filters. Further, the system 200 may include a peer group analysis (not shown) module configured to perform a peer group analysis of the company. The peer group analysis module comprises a comparison module configured to compare financials of the company to financials of competitor companies. Further, the system 200 includes a chart generation module configured to generate charts based on the financials of the company. In one embodiment, the chart generating module is configured to generate charts based on a user defined criteria. [0072] The system 200 may be better understood by considering the logical diagram of the system 200 as shown in FIG. 19, and the architecture diagram of the svstem 200 as shown in FIG 20.

[0073] As shown in FIG. 19, the system 200 may include multiple servers 500 (Web servers and database servers), and multiple users 502 connected to the multiple

14 servers 500 for data retrieval via internet. The input message, inquiry or request by One of the multiple users 502 is transferred via standard transport protocol, such as PORT 80 using SOAP technology, to the network hardware and then finally to web servers 502. The network hardware also checks the load between multiple web servers. It will be apparent to a person skilled in the art that SOAP is the simple Object Access Protocol, a way to create widely distributed, complex computing environments that run over the Internet using the existing Internet infrastructure. It is about applications communicating directly with each other over the Internet in a very rich way. Further, SOAP mandates the small number of HTTP headers that facilitates firewall/proxy settings.

[0074] The web servers sends the query to the database servers which then sends the output back to web servers to transfer via network switch to the particular user 500. [0075] The architecture of the system 200 may be Windows based three tiers WPF (Windows Presentation Foundation), as depicted in FIG 19. As shown in FIG. 19, the first layer is the user interface and the business access layer, wherein the user accesses the system through their workstations. The signal from user interface travels to web server where web service are installed at port 80/443. The signal travelling to web- server via internet may be encrypted. The users are then authenticated with username and password check, and after this the signal goes to core libraries where there is security enabled for access rights of users. This layer may have database access where the data is encrypted for communication with database. The database used is MS SQL Server 2005. The encrypted signal goes to the database which contains primary and audit databases. The database has the stored procedures and the data for the system 200. The signal travels back to the user interface with the required information from the database.

[0076] The present disclosure therefore provides a method, such as method 100, and a system, such as system 200, for providing financial forecasting of a listed company. The method includes receiving name of a company from a user, and locating a financial forecast model corresponding to the company. The financial forecast model is capable of being manipulated by the user. Further, the method includes providing the financials of the company based on the forecasting capability of the

15 financial forecast model. The system includes a receiving module configured to receive name of a company from a user, and a locating module coupled to the receiving module. The locating module is configured to locate a financial forecast model corresponding to. the company. Further, the system includes an application module coupled to the locating module and the collection module. The application module configured to provide the financials of the company based on the historical data and the financial forecast model. Further, the present disclosure provides a computer process for providing financial forecasting of a listed company. The system, the method and the computer process give significant value to the customer iri terms of reduced analysis, conversion and testing timeframe to forecast the future financial performance of a business entity or a company or a company listed in any stock exchange. Further, the system, the method and the computer process lowers the total cost of ownership of the financial platform for the client. Also, the system, the method and the computer process empowers a user of the information to form a fundamental view on a company within hours, delivering significant speed of decision-making. The method, system, and the computer process also allows quick generation of reports corresponding to companies, macro screening of companies, and peer group comparisons between companies.

[0077] In addition, the financial forecast models as described in the present disclosure are industry and company specific, keeping in mind in mind the specifics of each industry group and, in particular, each company's dynamics. Also, the financial forecast models are completely transparent in terms of methodology and information sourcing. Moreover, the financial forecast models are based on clear methodologies, provides complete transparency on the various formulae that drive forecasting as well as the underlying assumptions being used and the rationale for their use.

[0078] The foregoing descriptions of specific embodiments of the present disclosure have been presented for purposes of illustration and description. They are not intended to be exhaustive or to limit the present disclosure to the precise forms disclosed, and obviously many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the present disclosure and its practical application, to thereby enable others skilled in the art to best utilize the present disclosure and various embodiments with

16 various modifications as are suited to the particular use contemplated. (It is understood that various omission and substitutions of equivalents are contemplated as circumstance may suggest or render expedient, but such are intended to cover the application or implementation without departing from the spirit or scope of the claims of the present disclosure).

17