WO2021130685A1

WO2021130685A1 - A system and process tool for assured returns distributed from allocated sums

Info

Publication number: WO2021130685A1
Application number: PCT/IB2020/062372
Authority: WO
Inventors: Dhwani Nirav Tarkas
Original assignee: Dhwani Nirav Tarkas
Priority date: 2019-12-25
Filing date: 2020-12-23
Publication date: 2021-07-01

Abstract

A system and process tool for assured returns distributed from allocated sums is a risk-based system tool which acts as an instrument for clients to invest at lower risk and gain higher returns. In this pool, units are issued as per risk variant of the pool chosen by clients through the purchase made. Returns on purchase made are obtained by issuing units to clients and assigning pre-determined random numbers to those units; wherein allotment is done by selection of such random numbers through single or multiple random number/hash generation methods, processes or techniques; here units are assigned series of random numbers or converted into series of random numbers/hashes which are then selected and allotted. The units selected are then allocated back to their clients and distributed returns. Units bought by a client are linked to their Unique Identification Number at the time of purchasing units.

Description

A system and process tool for assured returns distributed from allocated sums.

FIELD OF INVENTION

The present invention relates to a system tool for assured returns distributed from allocated sums. More particularly, this the present invention relates to Fin-Tech system that enables and facilitates alternative options of investing to clients where they can earn high and assured returns.

BACKGROUND

[0001] In the current global market scenario, clients are searching for a system of investment that is more secure as well as a short term, which gives quick profits and assured returns after considering limited risks. A system in which there is minimal risk of returns and maximum assured absolute returns. The non-existence of any such system which lets its clients decide and choose the risk embedded in earning specified returns has led to this invention. Due to the High- risk factor in equity markets, clients tend to lose money easily and have a direct hit as a result of global market uncertainties. On the other end, investment in Government units, corporate bonds, and other debt units fail to get high yielding returns because of low risk. Besides, the bullion market gives good returns but only at a high cost and over a longer period. Hence the necessity for a modern-day system tool which gives on hourly, daily, weekly, fortnightly, monthly & quarterly basis high and assured returns containing low risk is needed. Moreover, there is no such system that has a combination of high and assured pool returns prevailing in the market. It is a system tool wherein clients can invest the amount to purchase units having pre -determined risk to earn returns more than such risk, which is guaranteed to all such system clients as a whole.

[0002] Even During the different economic cycles prevailing in one’s country, the investment made has to nullify the effects of recession, recovery, depression, and other inflationary factors in achieving good returns. Most of the system tools fail to achieve returns to clients due to the high inflation factor as a result of which returns are as good as a drop-in bucket full of water. Moreover, the rigid and strict policies for investing in different countries are different; hence it is difficult to invest globally in the highest return paying investment. In this system, cash, cash equivalents, monetary receipts are invited for investment from system clients to create a pool of limited value, thereby giving returns after consideration of pre -determined risk.

[0003] The principal object of this invention is to introduce a system tool that uses random numbers/hashes to provide high and assured returns to its system clients with lower risk. Another object of this invention is to introduce a system tool where all sections of societies can invest with comparatively lower risk and higher assured returns. Other objects of this system tool are to stabilize the market of a country, enable small and medium system users to invest and obtain good as well as regular returns, remove biases from the prevailing investing options available in the market, enable clients to get a good rate of return within the shortest duration and at the lowest risk, enable lower sections of society to take benefit of the system tool, bring undisclosed or black money to books in one’s own country, make regular habits among system clients and emphasize on the compounding of returns, boost client’s confidence among all other investment options and tools and to increase and infuse liquidity in the market and to help the government to earn taxes through this system tool.

SUMMARY

[0004] System tool for assured returns distributed from allocated sums includes a system tool having modules and its variants, which determines assured returns to clients by the risk and return breakoff chosen by them. This is done by the processing of units into random series, which are distributed randomly among methods generated and thereafter by generating and allocating random hashes or numbers back to clients in the system. This determines and allocates assured returns to its client. The system has in its fixed memory modules stored depending upon the functions of each module in the system. Each function helps in processing and generating overall output and determining returns earned by system clients. This memory is linked to the processor to perform processing function based on risk and returns input in a particular variant of a module and client’s preference in the module variant. The processor collects the instructions from each of the program modules in the memory, and depending on input, criteria’s and rules process the allocation and selection of returns in a randomly and in an unbiased manner. This processing for module variants may or may not be performed individually or simultaneously. The processor collects the data of clients from the cloud or server, which is connected with the system through a wireless or wired network and processes the same in each of the modules. The processor is able to generate, convert, and process random hashes or numbers in a manner such that returns are allotted randomly among clients in an unbiased and unpredictable manner.

[0005] The Summary is provided to introduce a selection of concepts in a simplified form that is further described below in detailed description. The summary does not identify key ingredients or essential features of the system, nor is it intended to be used as an aid in determining the scope of the claimed subject matter.

BRIEF DESCRIPTION OF DRAWINGS.

In the following detailed portion of the present description, the teachings of the present application will be explained in more detail with reference to the example embodiments shown in the drawings, in which:

[0006] Figure 1 illustrates the block diagram of the system tool for assured returns distributed from allocated sums according to the present invention.

[0007] Figure 2 illustrates the different variants in module 1 RNHP (random number/hash processor) according to the present invention.

[0008] Figure 3 illustrates a process diagram of the processes in different variants of module 1 according to the present invention.

[0009] Figure 4 shows a flow diagram of the overall working of RNHP (random number/hash processor) according to the present invention.

[0010] Figure 5 depict conversion of random series to hashes according to the present invention

[0011] Figure 6 depicts the conversion of series to random numbers/hashes and reconversion after the selection of random numbers/hashes to series according to the present invention.

[0012] Figure 7 shows the network layers and communication between interfaces according to the present invention.

[0013] Figure 8 illustrates the synopsis diagram of the present invention

DETAILED DESCRIPTION OF INVENTION.

The following specification particularly describes the invention and the manner in which it is to be performed.

[0014] Figure 1 describes a block diagram of the present invention on a system 500 and its network connection with external devices. The system 500 has a fixed Memory system 510 containing different modules for its processing numbered 511 as module 1 RNHP (Random number/Hash processor) 512 as module 2 database and 513 as module 3 security. The system 500 is capable of processing information through processor 520 with the help of random memory 530 present in the system. The system 500 is connected to cloud 550, which has multiple and sufficient storage capacities to accommodate data of clients and can expand as per the requirements of User 499. This cloud 550 through a network 545 is connected with the communications interface of System 500. These clouds containing servers are expandable and reveal a storage facility where data is stored after getting collected and processed from the client, and its functioning may be assigned to any third-party cloud service provider. Clients are able to connect to the system through the device interface 577 of their devices 565 and provide their information, which is stored on cloud 550 through system 500 through wireless or wired networks 545. All the data being received from the client is analyzed and filtered through a firewall 542. The data received from client device 545 is processed, and this information is systematically stored on the cloud. The cloud contains several servers, as shown in the diagram for illustrious purposes only. , The number of servers may exceed or may fall short and remains elastic depending on the volume of data received from clients. The data received from the User device interface 577 of the client, stored on the cloud 550, is retrieved and processed in different modules of fixed memory 510 located in the system 500. These include module 1 RNHP (Random number/Hash processor) 511, module 2, Database 512, and module 3 Security 513.

[0015] The communication device interface 577 of a client device 565 is capable of providing data such as UIN (Unique identification number), variants, tenure, unit no, face value, and number of units, etc. to the system 500 which is processed by system 500 and stored on the cloud 550. This data is then retrieved as required and processed in each module so as to give the user 499 details required from client device 565. The system 500 can sort, gather, accumulate, process and report data from cloud 550 through module 1 RNHP 511; module 2 Database 512, and module 3 Security 513. Embodiments of the system contain the ability of data to be processed in modules 511, 512, 513 and generate reports, lists, and results to the systems, thereby providing assured returns to clients. Initially, the data obtained from cloud 550 which is stored from the input provided by the client through the client’s device 565, is processed by module 1 RNHP (Random Number/Hash Processor) 511. The process includes the client being assigned units and the same being selected and allotted to clients through Module 1 RNHP 511 (Random Number/Hash Processor) by the risk and return mix given as input by User 499. An embodiment of this system tool also includes processing, which can be performed by any other methods or processes having the ability to generate and assign a random number or hashes for generating returns for the clients on a given risk-return mix. For the convenience of readers, RNHP (Random Number/Hash Processor), which is also an embodiment and novel method of this invention, is chosen as the best method. Information obtained after the said process is capable of being arranged as per the database fields required in module 2 Database 512. The process of receiving data from Client’s devices 565, sending the same to the cloud 550, its retrieval, and the processing of data in modules 1 511 RNHP and module 2 512 Database is secured by module 3 Security 513. The Client devices 565 connected through the client’s Device interface 577 are connected to the network, which may be wired or wireless as provided by the client’s internet service providers, which form a larger part of networks 545. The data transmission from Client’s device 565 up to System 500, from System 500 to Cloud 550 and during retrieval of data from cloud 550 to System 500 for data processing, may be secured by the Security module 513 located in the fixed memory 510.

[0016] A client device 565 shall be a device capable of data analyzing, capturing, transmitting and handling device which may be a mobile or cellular phone, a desktop computer, a personal computer, a notebook or a laptop, a personal digital assistant, a smartphone, a tablet, a smart TV, an electronic kiosk, kindle or e-book reader, multimedia or any electronic or mechanical device which has a basic processing and functioning capability and has an inbuilt memory. The devices mentioned above are exhaustive and may include other devices by any name capable of satisfying the above purpose.

[0017] Figure 2 depicts a general view of the different variants in module 1 RNHP (Random Number/Hash Processor) used for processing the data obtained from Client devices 565 through Network 545 and stored in Cloud 550. The process and working of the RNHP (Random number/Hash processor) remain the same in all variants, but the risk, returns, pool value, total number of units, and other input details differ from variant to variant. This information is obtained from the Client device 565 to System 500.

[0018] The Risk and the return data opted by the client received from the client for each variant of the module differs. However, the Risk and Return percentage within which risk and return mix may be determined are in different variants of the module RNHP 511 are:

Variant A 600 includes 5% risk and returns of more than 5% with allocation between 95%-100% to the total pool of clients.

Variant B 700 includes 10% risk and returns of more than 10% with allocation between 90%- 100% to the total pool of clients.

Variant C 800 includes 20% risk and returns of more than 20%, with allocation between 80%- 90% to the total pool of clients.

Variant D 900 includes 30% risk and returns of more than 30%, with allocation between 70%- 80% to the total pool of clients.

Variant E 1000 includes 40% risk and returns of more than 40% with an allocation of 60%-70% to the total pool of clients.

Variant F 1100 includes 50% risk and returns of more than 50% with an allocation of 50%-60% to the total pool of clients.

Variant Z 1200 includes risk between 50%-100% with returns ranging of more than 50%-100% with allocation between 0-50% to pool of clients.

[0019] The risk and return percentage for each variant of the RNHP (Random number/Hash processor) module is fixed at the time of inception of such pool. This risk and return may or may not be determined by formulae. If formulae are used in determining the risk and return mix, it may change after consideration of economic, financial, technological factors that are exhaustive in nature. These variants of RNHP (Random number/Hash processor) are designed to generate output in the form of units allocated to clients and send it to the User 499. The returns described here are the returns earned by the total pool after consideration of risk. The variants in module 1 511 help in ascertaining the distribution of assured returns from this pool of allocated sums.

[0020] Module 2 Database 512 has the ability to store, sort, arrange and present the information received from module 1 RNHP (Random number/Hash processor) 511 and can be used to generate various reports and spreadsheets as per the fields specified by the User 499. Fields such as client’s pool variants, pool type, pool risk, pool return, pool methods, number of methods, UIN (Unique identification number), unit number, K.Y.C (Know your customer) information of clients, payment details, bank details, tax details, profit/loss to clients, etc. which is an exhaustive list of some of the fields for which reports are generated.

[0021] Module 3 513 is the Security module that oversees the security aspect of the total process of the working of module 1 RNHP (Random number/Hash processor) 511 as well as module 2 Database 512. The Security Module 3 513 keeps all the information and data of Module 1 RNHP (Random number/Hash processor) 511 and module 2 Database 512 in encrypted form and decrypts the same when authenticated by the user. It includes security tools and encryption protocols to keep the database secured by applying protocols such as point-to- point tunneling protocol, layer two tunneling protocol, secure socket layer (SSL), and other encryption applications, which are some examples and exhaustive in nature.

[0022] Figure 3 illustrates the in-depth working of each of the Modules 1 RNHP (Random number/Hash processor) Variants. The module 1 RNHP (Random number/Hash processor) Variant A 600 shown in figure 2 can be referred to in figure 3 600 Variant A. 610 RNHP (Random number/Hash processor) A takes the input given by the user like risk, returns, pool value, the total number of units, etc. which is used for the purpose of determining the total allocation and selection of units after Random number/Hash generation process. After the input is given in 610 RNHP (Random number/Hash processor), A random series generation/Unit conversion is done in 610. 620 RMG refers to Random Method Generator, which helps in generating a number of random methods to be selected. The number of methods selected will be chosen randomly from a list of available methods which include hashes, functions, processes and are exhaustive and not limited to cyclic redundancy checks, checksums, universal hash function families, non-cryptographic hash functions, keyed cryptographic hash functions, un -keyed cryptographic hash functions, quadratic, algebraic, geometric, math and other functions. These also further include any subtype of each of the hashing functions or other mathematical models or methods which are exhaustive and which are described above. The methods & hashes are selected by selecting methods from Rand () function or any other similar methods, functions, commands, or algorithms which may or may not be used through a programming language for selecting random methods from a list of methods. The above methods are exhaustive and may include other methods for the generation of random methods. 630 Rmthds (random methods) shows the number of methods selected for the generation of random numbers/hashes. The methods selected are shown for illustration purposes, and in its practical application, it cannot be determined as to which method would be selected. These methods are selected in a random and unbiased manner. The methods selected by 630 Rmthds (random methods) are used to convert the unit numbers or their corresponding series to random numbers /hashes and assign units through the selection of such random numbers or hashes. To explain further, a reference to figure 5 shows series assignment/unit conversion and series classifications 620 after the series has been determined. Series may have been assigned by selecting from the list a series by applying random () function in figure 5, or Random methods are assigned random series starting from 421 to 440 are shown classified. Referring to figure 6, RNHP Generation shows in-depth Random Number/Hash Generation Module 630 on how the Random series are converted into hashes as per methods selected and unit assigned with series starting from 421 to 440 and.

[0023] In figure 3, the methods selected are method 1 640 being MD5 algorithm, 650 method 2 being SHA 1, 660 method 3 being Math, 670 method 4 being CRC 32, 680 method 5 being Binary. The random series generated from 421 to 440 are randomly classified among these methods. They are converted to random numbers/hashes depending on the method type. These Random Numbers/hashes are then selected at random so as to select quantum of numbers or hashes, which equals the percentage of allocation mentioned as input by User 499 in the beginning. Pool A 690 shows the allocation of assured returns distributed among 95% of the clients after considering the risk of 5%. Hence the quantum of Hashes/Random numbers selected is 95% of the total clients in the pool.

[0024] Similarly, variant B of RNHP (Random number/Hash processor) is shown in 700. RNHP (Random number/Hash processor) variant B 700 takes the input given by the user like risk, returns, pool value, the total number of units, etc. which is used for the purpose of determining the total allocation and selection of units after Random number/Hash generation process. Thereafter Random series generation or unit conversion is done in RNHP (Random number/Hash processor) B 710 and series so selected is classified randomly among methods that were selected in 720. The number of random methods generated (RMG) that is 1 is shown in 730. These quantum of methods selected are randomly generated out of the list of methods given as options. In variant B 730 shows that only one method was selected. 740 shows that the method selected was AES Hash. Thus ranges of series of numbers selected are converted into encryption hash method AES as shown in 740. Numbers/hashes generated are then selected at random to match quantum of numbers or hashes, which equals to the percentage of allocation mentioned as input by User 499 in the beginning. Pool B 750 shows the allocation of assured returns distributed among 90% of the clients after considering the risk of 10%. Hence the quantum of Hashes/random numbers selected is 90% of the total clients in the pool.

[0025] In the same manner, variant C of RNHP is shown in 800. RNHP (Random number/Hash processor) variant C 810 takes the input given by the user like risk, returns, pool value, the total number of units, etc. which is used for the purpose of determining the total allocation and selection of units after Random number/Hash generation process. Thereafter Random series generation/Unit conversion is done in 810, and series so selected is classified randomly among methods that were selected in 820. The number of random methods generated that is 4 is shown in 830. These quantum methods selected are randomly generated out of list of methods given as options. In variant B 830 shows that four methods were selected. Methods selected are shown in 840 being MD5 Hash, 850 being AES, 860 being CRC 32, 870 being Math. The ranges of series of numbers selected are converted into MD5 Hash 840, AES 850, CRC 32 860 and Math 870 randomly. Numbers/hashes generated are then selected at random to match quantum of numbers or hashes which equals to the percentage of allocation mentioned as input by User 499 in the beginning. Pool C 880 shows allocation of assured returns distributed among 80% of the clients after considering the risk of 20%. Hence the quantum of Hashes/random numbers selected is 80% of the total clients in pool.

[0026] Likewise, variant D of RNHP is shown in 900. RNHP (Random number/Hash processor) variant D 910 takes the input given by the user like risk, returns, pool value, total number of units etc. which is used for the purpose of determining the total allocation and selection of units after Random number/Hash generation process. Thereafter Random series generation/Unit conversion is done in 910 and series so selected is classified randomly among methods that were selected in 920. The number of random methods generated that is 6 is shown in 930. These quantum of methods selected are randomly generated out of list of methods given as options. In variant D 930 shows that six methods were selected. Methods selected are shown in 940 being Math, 950 being Binary, 960 being SHA 1, 970 being AES, 980 being CRC 32, 990 being Hex. The ranges of series of numbers selected are converted into Math 940, Binary 950, SHA 1 960, AES 970, CRC 32 980, and Hex 990 randomly. Numbers/hashes generated are then selected at random to match quantum of numbers or hashes which equals to the percentage of allocation mentioned as input by User 499 in the beginning. Pool D 999 shows allocation of assured returns distributed among 70% of the clients after considering the risk of 30%. Hence the quantum of Hashes/random numbers selected is 70% of the total clients in pool.

[0027] Similarly, variant E of RNHP is shown in 1000. RNHP (Random number/Hash processor) variant E 1010 takes the input given by the user like risk, returns, pool value, total number of units etc. which is used for the purpose of determining the total allocation and selection of units after Random number/Hash generation process. Thereafter Random series generation/Unit conversion is done in 1010 and series so selected is classified randomly among methods that were selected in 1020. The number of random methods generated that is 3 is shown in 1030. These quantum of methods selected are randomly generated out of list of methods given as options. In variant E 1030 shows that three methods were selected. Methods selected are shown in 1040 being AES, 1050 being CRC 32, 1060 being Math. The ranges of series of numbers selected are converted into AES 1040, CRC 32 1050, Math 1060 randomly. Numbers/hashes generated are then selected at random to match quantum of numbers or hashes which equals to the percentage of allocation mentioned as input by User 499 in the beginning. Pool E 1070 shows allocation of assured returns distributed among 60% of the clients after considering the risk of 40%. Hence the quantum of Hashes/random numbers selected is 60% of the total clients in pool.

[0028] Resembling the above variants, Variant F of RNHP (Random number/Hash processor) is shown in 1100. RNHP (Random number/Hash processor) variant F 1110 takes the input given by the user like risk, returns, pool value, total number of units etc. which is used for the purpose of determining the total allocation and selection of units after Random number/Hash generation process. Thereafter Random series generation/Unit conversion is done in 1110 and series so selected is classified randomly among methods that were selected in 1120. The number of random methods generated that is 5 is shown in 1130. These quantum of methods selected are randomly generated out of list of methods given as options. In variant F 1130 shows that six methods were selected. Methods selected are shown in 1140 being CRC 32, 1150 being AES, 1160 being Binary, 1170 being SHA 1, 1180 being Math. The ranges of series of numbers selected are converted into CRC 32 1140, AES 1150, Binary 1160, SHA 1 1170, math 1180 randomly. Numbers/hashes generated are then selected at random to match quantum of numbers or hashes which equals to the percentage of allocation mentioned as input by User 499 in the beginning. Pool F 1190 shows allocation of assured returns distributed among 50% of the clients after considering the risk of 50%. Hence the quantum of Hashes/random numbers selected is 50% of the total clients in pool.

[0029] Alike, Variant Z of RNHP is shown in 1200. RNHP (Random number/Hash processor) variant E 1210 takes the input given by the user like risk, returns, pool value, total number of units etc. which is used for the purpose of determining the total allocation and selection of units after Random number/Hash generation process. Thereafter Random series generation/Unit conversion is done in 1210 and series so selected are classified randomly among methods that were selected in 1220. The number of random methods generated that is 1 is shown in 1230. These quantum of methods selected are randomly generated out of list of methods given as options. In variant Z 1230 shows that only one method was selected. 1240 shows that the method selected was MD5 Hash. Thus ranges of series of numbers selected are converted into MD5 Hash as shown in 1240. Numbers/hashes generated are then selected at random to match quantum of numbers or hashes which equals to the percentage of allocation mentioned as input by User 499 in the beginning. Pool Z 1250 allocation shows the allocation of assured returns distributed among <50% of the clients after considering the risk of >50%. Hence the quantum of Hashes/random numbers selected are <50% and are equal to the number of clients to whom the return is distributed out of the total clients in the pool.

[0030] Figure 4 shows a flowchart of the working of RNHP (Random number/Hash processor) where 610 describes the assignment of series to unit numbers or conversion of unit numbers. In the figure, 610 shows series being allotted to units or units converted to series being classified randomly among methods that were selected in 620. In the figure, 630 shows that out of total methods being 10 only 5 methods have been selected to generate random hashes/numbers. Methods selected are shown in 640, 650, 660, 670 and 680 where methods are MD5, SHA 1, Math, CRC 32, and Binary, respectively. The numbers 422, 427, 429, 437 from the series of 421 to 440 have been allocated to MD5 in method 1. The numbers 424, 428, 434, 440 from the series of 421 to 440 have been allocated to method 2 is SHA1. The numbers 426, 432, 438 from the series of 421 to 440 have been allocated to Method 3 being Math. The numbers 421, 430, 435, 439 from the series of 421 to 440 have been allocated to Method 4 being CRC 32. The numbers 423, 425, 431, 433, 436 from the series of 421 to 440 have been allocated to Method 5 being Binary. Again this generation of series shown in 610 classifieds to these methods shown in 620 are on a random basis and cannot be ascertained as to which series number would be allocated to which method.

[0031] In figure 5, random series generation 610 shows the random series are either assigned corresponding to unit numbers or unit numbers are being converted to a random series. In 620, random series are being classified to different methods in 630 after the methods have been generated and thereafter be converted to random numbers/hashes in 631 through different methods generated in 630. These numbers in series are allocated and classified to methods using random () functions or any other function or method which can perform the function of assigning series to methods randomly. Various computer languages such as C, C++, Java, PhP, etc., and other methods, programming languages, can be used to classify the methods randomly. The allotment is made in such a way, which equals the percentage of allocation given as input by User 499 in the beginning after risk consideration. This way a system client is assured of his returns allocated from the pool.

[0032] Figure 6 shows the conversion of series to random numbers/hashes and reconversion after selection of random numbers/hashes to series. In the figure, series are converted into hashes/random number as per the method selected. The figure shows the Random number/Hash generation module, which starts with series being classified to random methods in column 1 and column 2. In diagram column, no 1 shows that the unit number series starting from 421 to 440 are assigned methods randomly generated on a random basis. These series of numbers are further converted into hashes/numbers according to methods assigned in column 2, and the output is shown in column 3. Column no 4 shows that out of all the 20 random numbers/hashes, 95% of them are selected randomly, and series no 430 in column 1 , which has been converted by CRC 32 method hash has not been selected. Here the total pool allocation of 95% has been made by the system, and all the units selected purchased by clients will be distributed assured returns. In System 500 the numbers selected have an equal chance of getting selected or not. The System 500 selection of numbers/hashes is made purely on a random and unbiased basis. After the selection of the numbers/hashes, they are converted back to their original series numbers linked to the original UIN (Unique identification number) of the client and are distributed returns back to the client’s bank account from where the purchase has been made.

[0033] Explaining the working of Module 1 RNHP 511 of system 500 through figure 6 further, the generation of random series corresponding to unit numbers, generation of random methods, allocation of such series assigned to random methods, and the generations of Random hashes/numbers are obtained from random methods which generate in the system by programming, acts, methods, tricks, different applications, formulas, plans, processes or any medium which involves generation of random numbers, random hashes, random alphabets, random signs, random simulations, random probabilities, random symbols, random drawings, random inscription, random visual or non-visual marks through any physical, mechanical, electronic, conventional or non-conventional ways which may be computerized or not; used to serve as a tool for selecting and allocating returns to the clients is also an embodiment and novelty of this application. On the selection of numbers/hashes drawn randomly, they are converted back to series and linked back to the client’s UIN (Unique identification number). RNHP (Random number/Hash processor) also has the capability to be linked or use a third-party application or system, which helps in generating random numbers/hashes. Hence the system tool includes generation of random series, generation of random methods, and allocation of series generated to random methods, and the generations of random hashes/numbers from those random methods, etc. are processing through Random number/Hash generator for allocation of assured returns. However, the performance of the RNHP (Random number/Hash generator) in the prescribed manner may change internally in any combination of steps mentioned above or even skipping any step for generation and selection of random number/hashes. [0034] The Random number/Hash processor, therefore, has the capability to generate random series, then allocate random series to random methods generated and then generate random numbers/hashes and select and allocate randomly from those Random numbers/hashes units to the client’s pool. The generation of random series, random methods, their allocation, and selection of Random Numbers/hashes are made in a manner so as not to prejudice any client in any manner and get returns in an unbiased manner. The probability of Non-predictability of selection, allocation, return and output by the module can be given by

1. Allocation of random series to units or conversion of units into random series.

2. Random selection of number of methods to be used by RNHP.

3. Random methods generated (RMG) and selected for RNHP Variants.

4. Conversion of random series by random methods selected into random numbers and hashes.

5. Selection of hashes/numbers randomly.

Hence the number of possibilities of results RNHP can give as output is:

RNHP = Series(R) X Mthd_Nos (R) X Method Type(R) X Hash selection (R)

Where,

Series(R) = Allocation of random series to unit or conversion of units into random series itself. Mthd_Nos (R) - Number of random methods selected.

Method_Type(R)- Random methods selected in the number of methods selected.

Hash_selection (R) - Conversion to hash/number and selection of the same randomly.

There numerous outcomes and probabilities as to results of RNHP (Random number/Hash processor) make it very difficult to predict and ascertain the selection and allocation process that RNHP (Random number/Hash processor) performs which would take reasonable and sufficient time to be cracked or decrypted which makes RNHP (Random number/Hash processor) a unique proposition of it being unbiased, uncertain and fair to all users.

[0035] Once the allocation and selection of hashes are completed, the information and selection of units are conveyed to the Client device 565 using another application protocol. It can also use a third-party tool provider not maintained or processed by the system 500 and can include content from the system embedded in a webpage provided by a third-party tool provider. This thin client configuration for the client device 565 is provided by way of example only and is not meant to limit the present disclosure.

[0036] Further, referring to figure 1, a system 500, including some or all of its components, can operate under computer control. For example, a processor 520 can be included with or in a system 500 to control the components and functions of systems 500 and modules contained therein described herein using software, firmware, hardware (e.g., fixed logic circuitry), manual processing, or a combination thereof. The terms “functionality,” “process,” “logic” is used herein generally represent software, firmware, hardware, or a combination of software, firmware, or hardware in conjunction with controlling the systems 500. In the case of a software implementation, the module functionality, or logic represents program code that performs specified tasks when executed on a processor (e.g., Central processing Unit). The program code can be stored in one or more computer-readable memory devices (e.g., internal memory and/or one or more tangible media), and so on. The structures, functions, approaches, and techniques described herein can be implemented on a variety of commercial computing platforms having a variety of processors.

[0037] A processor 520 provides processing functionality for the system 500 and can include any number of processors, micro-controllers, or other processing systems and resident or external memory for storing data and other information accessed or generated by the system 500. The processor 520 can execute one or more software programs or modules that implement techniques described therein. The processor 520 is not limited by the materials from which it is formed or the processing mechanisms employed therein and, as such, can be implemented via semiconductor(s) and/or transistors (e.g., using electronic circuit(IC) components), and so forth.

[0038] The system 500 includes a communications interface 540. The communications interface 540 is operatively configured to communicate with components of the system 500. For example, the communications interface 540 can be configured to transmit data for storage in the system 500, retrieve data from storage in the system 500, and so forth. The communications interface 540 is also communicatively coupled with the processor 520 to facilitate data transfer between components of the system 500 and the processor 520 (e.g., for communicating inputs to the processor 520 received from a device communicatively coupled with the system 500). It should be noted that while the communication interface 520 is described as a component of a system 500, one or more components of the communications interface 540 can be implemented as external components communicatively coupled to the system 500 via a wired and/or wireless connection. The system 500 can also comprise and/or connect to one or more input/output (I/O) devices (e.g., via the communications interface 540), including, but not necessarily limited to a display, a mouse, a touchpad, a keyboard, and so on.

[0039] The communications interface 540 and/or the processor 520 can be configured to communicate with a variety of different networks including, but not necessarily limited to a wide-area cellular telephone network, such as a 3G cellular network, a 4G cellular network, or a global system for mobile communications (GSM) network; a wireless computer communications network, such as a Wifi network (e.g., a wireless local area network(WLAN) operated using IEEE 802 network standards); an internet; the Internet; a wide area network (WAN); a local area network (LAN); a personal area network (PAN) (e.g., a wireless personal area network (WPAN) operated using IEEE 802.15 network standards); a public telephone network; an extranet; an intranet; and so on. However, this list is provided by way of example only and is not meant to be restrictive of the present disclosure. Further, the communications interface 540 can be configured to communicate with a single network or multiple networks across different access points.

[0040] The system 500 also includes a memory 530. The memory 530 is an example of tangible, computer-readable storage medium that provides storage functionality to store and process various data associated with the operation of the system 500, such as software programs and/or code segments, or other data to instruct the processor 520, and possibly other components of the system 500, to perform the functionality described herein. Thus, the memory 530 can store data, such as a program of instructions for operating the system 500 (including its components), and so forth. It should be noted that while a single memory 530 is described, a wide variety of types and combinations of memory (e.g., tangible, non-transitory memory) can be employed. The memory 530 can be integral with the processor 520, can comprise stand-alone memory, or can be a combination of both. The memory 530 can include but is not necessarily limited to removable and non-removable memory components, such as random-access memory (RAM), read-only memory (ROM), flash memory (e.g., a secure digital (SD) memory card, a mini-SD memory card, and/or a micro-SD memory card), magnetic memory, optical memory, universal serial bus (USB) memory device, hard disk memory, external memory, and so forth. In implementations, the system 500 and/or the memory 530 can include removable integrated circuit card (ICC) memory, such as memory provided by a subscriber identity module (SIM) card, a universal subscriber identity module (USIM) card, a universal integrated circuit card (UICC), and so on.

[0041] Figure 7 also reveals a system 500, which has different layers which enable information handling, processing and storage and use of Artificial Intelligence to convert data into user- readable information. Such data received from Clients 565 may be facilitated directly or through a third-party tool provider 555 that help in information handling, arranging, sorting, processing functions as well as storage on Cloud 550. This processing of data into information and its response to the client is processed through different layers included in Communications interface 540. These layers include the Application layer, Presentation Layer, Sessions Layer, Transport Layer, Network Layer, Data Link Layer, and Physical Layer, as shown in Figure 7. These layers are based on the established principles of the OSI model and a more recent TCP Model for inter networking between themselves. These layers together help in overall information handling and synchronize the transfer of information. These Layers help in the communication process between system 500, Users 499, and Clients 565. Further, a Module 1 RNHP is described in an example implementation in which the system 500 processes selection and allotment of unit . One or more of the information handling layers is implemented as a computing device that responds to requests across a computer network. For example, the Information handling device 541 receives a request from a client device 565 and/or a third-party tool provider 555 in response to the request. The information handling devices 541 can also communicate with one another to serve the request. In some embodiments, the information handling devices 541 are arranged in clusters, where each cluster provides the functionality of the system 500. In embodiments of the disclosure, the system 500 provides functionality to balance the loads on the various clusters.

[0042] In some embodiments, the first cluster of information handling devices is configured as a user interface layer 535, the second cluster of information handling devices 541 is configured as a data layer 536, and the third cluster of information handling devices 541 is configured as a calculation layer 537. The user interfaces layer 535 can be configured as a web layer that provides client-side script (e.g., JavaScript (JS)) configured to allow a user 499 to interact with content provided by the system 500 (e.g., in the form of a webpage 112). For example, a web browser 585 is configured to receive input from a user 499 to interact with content provided by the system 500 (e.g., in the form of a web page 585) and a web browser 585 is also configured to receive input from a Client 565 identifying a variant (e.g., a variant present in module 1 RNHP having different variants like variant A 600 in Fig 2). The results of Processed information from different variant to and from the client devices 565 to and from the user interface layer 535, and then to and from the data layer 536. The data layer 536 is configured to authenticate the user 499, verify the input and security information contained in Module 3 Security 513. However, this example is not meant to limit the present disclosure. In other embodiments, the data layer 536 communicates directly with a third-party tool provider 555 - (e.g., using an application programming interface (API) or the like). The information is then transferred from the data layer 536 to the calculation layer 537.

[0043] The calculation layer 537 is configured to implement one or more Module 1 RNHP Variant 511, the Database module 512, the Security Module 513, and all their variants. For example, the calculation layer 537 includes a database stored in Cloud 550 on any of its servers or memory (e.g., an in-memory database, a relational database (e.g., a structured query language (SQL) server), and so forth). The calculation layer 537 accesses the database to obtain information associated with one or more financial characteristics of the RNHP (Random number/Hash processor) 511 of systems tool 500. In embodiments of the disclosure, the database Module 2 512 stores client information, including but not necessarily limited to client pool variants, pool type, pool risk, pool return, pool methods, pool number of methods, UIN, unit no, K.Y.C Information of clients and so forth. In some embodiments, the calculation layer 537 receives processing input from Module 1 RNHP 511 or other sources (e.g., a third-party) and produces output information to be stored in the database 550 (e.g., by batch processing and/or real-time processing of 511 Module 1 RNHP at the end of a day, throughout a day, and so forth). As described, the calculation layer 537 determines one or more selected Random hashes, Unit, and its corresponding UIN, and so forth. The calculation layer 537 then transfers this information to the data layer 536, which in turn, transfers the information to the client device 565 (e.g., via the user interface layer 535) and/or to the third-party tool provider 555. Also, the information may be stored in the Cloud 550 through system 500. [0044] Figure 8 illustrates a synopsis for better understanding of the present invention. Step 1 of client process flow in system 500 starts with multiple Clients 565 opting to purchase in a particular variant of the pool. Limited number of clients can participate in the pool variant they have chosen in Module 1 RNHP depending on the risk and return mix. Limited number of clients 565 can purchase depending on the units available in the pool for a limited period. As shown in step 2 multiple clients through their Client’s device 565 are supposed to register themselves on the Webpage 585 through their web browser 580 and complete all the registration formalities required. Step 3 shows that a confirmation is provided to a Client’s device 565 once Client 565 successfully registers himself on the Webpage 585 through their web browser 580. The system 500 is capable of sending an acknowledgement and status to Client 565 through network 545. Step 4 indicates the Terms & Conditions for purchasing in the pool. A client through Client’s device 565 is able to choose the variant and agree or disagree to the terms & conditions for purchasing units in the pool variant depending on the risk-return tradeoff he chooses. Thereafter step 5 shows Unique Identification Number being allotted on confirmation of the terms and conditions above. Clients are allocated a Unique Identification Number (UIN) after they are duly registered and permitted for purchase of units in a pool variant. A UIN allotted to a client can hold single or multiple units assigned to different risk variants of pools i.e. A, B, C, D, E, F and Z. A client assigned a UIN is able to hold multiple units of same pool variant. UIN is a Unique Identification Number provided for identification of a client. Step 6 shows how a client’s device 565 can make purchases. A client through Client’s device 565 is able to purchase units in the pool after the following the above mentioned steps in a particular pool variant depending on the risk-return tradeoff he chooses. Step 7 shows Units being allotted to clients. Client’s device 565 purchasing units in a particular variant of the pool are assigned units against their purchases made. These multiple units are linked to the UIN (Unique Identification Number) of client 565. Step 8 shows risk variants of pools. These describe the categories of pool variants with different risk and return tradeoffs whose details can be referred in Para [0018]. Step 9 shows Module 1 RNHP 511 Module 1 RNHP 511 (Random Number Hash Processor) being used as best method in system 500 to select units and allocate returns to Client’s 565. The process of RNHP helps in selection and allotment of random numbers and hashes in a manner which is uncertain and un bias. Step 10 reveals assignment of units to clients. All the Random number/hashes selected in Module 1 RNHP 511 are used for assigning units to UIN of Client 565. Step 11 shows Tax & Governmental Levies being deducted from the returns. The returns earned by client on purchasing in pool are deducted as per a country’s taxation policies and governmental levies before being transferred back to client’s account. Step 12 depicts Client’s Bank where all the Returns obtained by Client’s 565 after processing of Module 1 RNHP 511 are returned to clients of the pool and the same is credited in Bank Account of client registered by the pool.

[0045] Generally, any of the functions described herein can be implemented using hardware (e.g., fixed logic circuitry such as integrated circuits), software, firmware, manual processing, or a combination thereof. Thus, the Modules and its variants, as discussed in the above disclosure, generally represent hardware (e.g., fixed logic circuitry such as integrated circuits), software, firmware, or a combination thereof. In the instance of a hardware configuration, the various Modules discussed in the above disclosure may be implemented as integrated circuits along with other functionality. Such integrated circuits may include all of the functions of a given module system, or circuit, or a portion of the functions of the module, system or circuit. Further, elements of the modules, systems or circuits may be implemented across multiple integrated circuits. Such integrated circuits may comprise various integrated circuits including, but not necessarily limited to a monolithic integrated circuit, and a flip flop integrated circuit, a multichip module integrated circuit, and/ or a mixed-signal integrated circuit. In the above instance of a software implementation, the various modules discussed in the above disclosure represent executable instructions (e.g. program code) that perform specified tasks when executed on a processor. These executable instructions can be stored in one or more tangible computer- readable media. In some such instances, the entire system, module or circuit may be implemented using its software or firmware equivalent. In other instances, one part of a given system, module, or circuit may be implemented in software or firmware, while other parts are implemented in hardware.

[0046] Although the subject matter has been described in language specific to structural features and/or process operations, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather the specific features, codes, acts, and design as described above are disclosed as example forms of implementing the claims and could be altered to make it more efficient, avoid redundancy, and as per the need.

Claims

CLAIMS: I Claim:

1. A process tool for assured returns distributed from allocated sums for clients comprising the steps of: a. registering in a database for a variant of an investment plan; b. agreeing to the terms and conditions for said investment plan; c. purchasing units of a particular variant of said investment plan in a pool of investment; d. generation of output from a random number hash processor module(RNHP) based on a said variant of investment plan; e. issuing a Unique Identification Number (UIN) being allotted on said registration of said variant of investment plan; f. issuing an investment return based on the said variant of the investment plan and output of said RNHP processing.

2. The process tool for assured returns distributed from allocated sums as claimed in claim 1, wherein a confirmation is provided to the clients on said registration, post which the said client is enabled to make a purchase in the said investment plan.

3. The process tool for assured returns distributed from allocated sums as claimed in claim 1, wherein the returns to said client on said investment plan varies on the output of said RNHP and is limited to a risk profile in the said investment plan.

4. The process tool for assured returns distributed from allocated sums as claimed in claim 1, wherein said RNHP module is designed to generate output in the form of units allocated to clients.

5. A system for assured returns distributed from allocated sums for clients comprising: a. memory system having a fixed memory with at least one a random number hash processor generating module (RNHP), a database module, anda security module; b. a networking cloud system; c. a random memory system; d. a processor e. a communication device interface of the said memory system, said interface being connected to said cloud system through networks; wherein data received from said communication interface of said client, is stored in the cloud, and retrieved and processed in said RNHP modules, said database modules and said security module.

6. The system for assured returns distributed from allocated sums for clients as claimed in claim 5, wherein said communication device interface of the said client device is capable of providing data including a UIN (Unique identification number), variants, tenure, unit no, face value, and the number of units in said memory system which is processed by said RNHP module and stored on the said cloud system.

7. The system for assured returns distributed from allocated sums for clients as claimed in claim 5, wherein said system assigns units for returns through said methods including RNHP module depending on risk profile selected by said client.

8. The system for assured returns distributed from allocated sums for clients as claimed in claim 5, wherein said database module receives the information from said RNHP module and is shared with said communication device interface of the said memory system.

9. The system for assured returns distributed from allocated sums for clients as claimed in claim 5, wherein said security module of said memory system secures the data from said memory system and its interaction with said communication device interface including the retrieval of said data from the said networking cloud system.

10. The system for assured returns distributed from allocated sums for clients as claimed in claim 5, the memory subsystem has the ability to store and present the data in a format of spreadsheets, and visual reports having fields specified by system user of said client’s pool variants, pool type, pool risk, pool return, pool methods, number of methods and UIN.

11. The system for assured returns distributed from allocated sums for clients as claimed in claim 5, wherein said security module keeps all the information and data of RNHP module and database module in encrypted form and decrypts the same when authenticated by the system user and the client.

12. The system for assured returns distributed from allocated sums for clients as claimed in claim 5, wherein said RNHP module allocates and selects random units to said clients on basis of a risk-return mix input by client or user in order to give them assured returns from allocated sums.

13. The system for assured returns distributed from allocated sums for clients as claimed in claim 5, wherein said RNHP module generates random numbers and hashes involving the steps of: a. allocation of a random series to unit numbers or conversion of unit numbers to random series; b. generating and selecting methods by a random method generator (RMG)from a list of available methods wherein the said methods convert series or unit numbers into random numbers or hashes; c. using the methods so generated in b above to convert series or unit numbers in a. above into random numbers or hashes; d. selection of said random numbers or hashes and forwarding the same to said database module.