FIELD OF INVENTION [0001] The embodiments of the present disclosure generally relate to assessment of errors of inclusion and exclusion in social protection schemes/programs globally. BACKGROUND OF THE INVENTION [0002] The following description of related art is intended to provide background information pertaining to the field of the disclosure. This section may include certain aspects of the art that may be related to various features of the present disclosure. However, it should be appreciated that this section be used only to enhance the understanding of the reader with respect to the present disclosure, and not as admissions of prior art. [0003] Social protection has a significant share in Government’s budget. The efficient utilization of budget and effectiveness of social protection model is key to ensure that the citizens can grow socio-economically. Errors of inclusion and exclusion are a major challenge for Governments. On one hand, they are not able to utilize the budget efficiently. On the other hand, the funds disbursed not necessarily result in desired socio-economic progression of citizens. Current invention supports the Government in finding the probable cases falling under errors of inclusion and exclusion from multiple dimensions. With such insights, Government can improve the implementation methods, has opportunities to do policy level changes and create a social protection model on the unique needs of each citizen/family in the country. [0004] There is therefore a need in the art to provide a system and a method that can facilitate mitigating the problems associated with the prior art. OBJECTS OF THE PRESENT DISCLOSURE [0005] Some of the objects of the present disclosure, which at least one embodiment herein satisfies are as listed herein below. [0006] It is an object of the present disclosure to ensure effective utilization of social protection funds, and minimize the errors of inclusion (EoI) and exclusion (EoE). . [0007] It is an object of the present disclosure to reduce ultimate repercussions of errors on policy and policy-level changes, and using only the verified and latest data thus enrolled or terminated citizens with a time validity. [0008] It is an object of the present disclosure to use only shareable data. [0009] It is an object of the present disclosure to solve many data issues by the implementation as only citizens that are being enrolled/terminated for at least one scheme are picked. [0010] It is an object of the present disclosure to provide a refined survey/new service. [0011] It is an object of the present disclosure to calculate the score to be anonymised for score calculation. SUMMARY [0012] This section is provided to introduce certain objects and aspects of the present disclosure in a simplified form that are further described below in the detailed description. This summary is not intended to identify the key features or the scope of the claimed subject matter. [0013] In an aspect, the present disclosure provides for a system for assessment of errors of inclusion and exclusion in one or more welfare schemes for a plurality of users. The system may include one or more processors operatively coupled to a plurality of first computing devices, the one or more processors coupled with a memory that stores instructions which when executed by the one or more processors causes the system to receive a first set of data packets from a plurality of first computing devices, the first set of data packets pertaining to information on the one or more welfare-based schemes availed by the plurality of users operating the plurality of first computing devices and further receive a second set of data packets from the plurality of first computing devices, the second set of data packets pertaining to a set of welfare based scores pertaining to each user. The system may then be configured to extract a first set of attributes from the first set of data packets, the first set of attributes pertaining to error of inclusion (EOI), the error of inclusion referring to an inclusion of a user who should not avail the one or more welfare schemes and then extract a second set of attributes from the first set of data packets, the second set of attributes pertaining to error of exclusion (EOE), the error of exclusion referring to an error due to an exclusion of a user who should avail the one or more welfare schemes. The system may be further configured to extract a third set of attributes from the of second set of data packets, the third set of attributes pertaining to a first and a second limit of a score range associated with the set of welfare-based scores. Based on the extracted first, second and third set of attributes, the system may be configured to identify, by using an artificial intelligence (AI) engine, a set of errors pertaining to any or the combination of error of inclusion and error of exclusion and then determine, using the AI engine, a deprivation index for each user based on the identification of the set of errors. [0014] In an embodiment, the system may be further configured to compare the deprivation index of each user with the respective scores of the plurality of users and based on the comparison, determine a set of active users in descending order of the deprivation index, the deprivation index being within a predefined range with the first limit and the second limit of the score range. [0015] In an embodiment, the system may be further configured to use at least three types of scores such as a Socio-Economic Need Score, a Welfare-type Based Score, and a Scheme Specific Need-Score to calculate the EOE and the EOI and further determine the deprivation index of each user. [0016] In an embodiment, the deprivation index may provide information about an overall performance of the one or more welfare schemes, and how much each user is in need of the one or more welfare schemes. [0017] In an embodiment, based on the deprivation index, the system may be configured to assess an overall effectiveness of the one or more welfare schemes, a plurality of possibilities to explore, and related one or more policy decisions. [0018] In an embodiment, each welfare scheme may be associated with one or more welfare types, and the system may be configured to map each welfare scheme with the respective one or more welfare types. [0019] In an embodiment, the system may be further configured to determine a welfare based score for each respective welfare scheme type. [0020] In an embodiment, the welfare based score may include at least five major welfare-type based scores such as Housing Need Score, Health Need Score, Education Need Score, Food Need Score, and Livelihood Need Score. [0021] In an embodiment, the system may be further configured to check if a user has already availed the one or more welfare-based schemes based on the extracted first and second set of attributes. [0022] In an embodiment, the system may be further configured to terminate a user that has exhausted all benefits associated with the one or more welfare schemes. [0023] In an aspect, the present disclosure provides for a user equipment (UE) for assessment of errors of inclusion and exclusion in one or more welfare schemes for a plurality of users. The UE may include a processor and a receiver operatively coupled to a plurality of first computing devices, the processor coupled with a memory that stores instructions which when executed by the processor causes the UE to receive a first set of data packets from a plurality of first computing devices, the first set of data packets pertaining to information on the one or more welfare-based schemes availed by the plurality of users operating the plurality of first computing devices and further receive a second set of data packets from the plurality of first computing devices, the second set of data packets pertaining to a set of welfare based scores pertaining to each user. The UE may then be configured to extract a first set of attributes from the first set of data packets, the first set of attributes pertaining to error of inclusion (EOI), the error of inclusion referring to an inclusion of a user who should not avail the one or more welfare schemes and then extract a second set of attributes from the first set of data packets, the second set of attributes pertaining to error of exclusion (EOE), the error of exclusion referring to an error due to an exclusion of a user who should avail the one or more welfare schemes. The UE may be further configured to extract a third set of attributes from the of second set of data packets, the third set of attributes pertaining to a first and a second limit of a score range associated with the set of welfare-based scores. Based on the extracted first, second and third set of attributes, the UE may be configured to identify, by using an artificial intelligence (AI) engine, a set of errors pertaining to any or the combination of error of inclusion and error of exclusion and then determine, using the AI engine, a deprivation index for each user based on the identification of the set of errors. [0024] In an aspect, the present disclosure provides for a method for assessment of errors of inclusion and exclusion in one or more welfare schemes for a plurality of users. The method may include the step of receiving, by one or more processors, receiving a first set of data packets from a plurality of user computing devices, the first set of data packets pertaining to information on the one or more welfare-based schemes availed by the plurality of users operating the plurality of first computing devices. The one or more processors may be operatively coupled to the plurality of first computing devices and may be coupled with a memory that stores instructions which may be executed by the one or more processors. The method may further include the step of receiving a second set of data packets from the plurality of computing devices, the second set of data packets pertaining to a set of welfare based scores pertaining to each user. The method may further include the steps of extracting a first set of attributes from the first set of data packets, the first set of attributes pertaining to error of inclusion (EOI). The error of inclusion may refer to an inclusion of a user who should not avail the one or more welfare schemes and the step of extracting a second set of attributes from the first set of data packets, the second set of attributes pertaining to error of exclusion (EOE). The error of exclusion may refer to an error due to an exclusion of a user who should avail the one or more welfare schemes. The method may also include the step of a third set of attributes from the of second set of data packets, the third set of attributes pertaining to a first and a second limit of a score range associated with the set of welfare-based scores. Furthermore, the method may include, the step of based on the extracted first, second and third set of attributes, identifying, by using an artificial intelligence (AI) engine, a set of errors pertaining to any or the combination of error of inclusion and error of exclusion. Furthermore, the method may include the step of determining a deprivation index for each user based on the identification of the set of errors. BRIEF DESCRIPTION OF DRAWINGS [0025] The accompanying drawings, which are incorporated herein, and constitute a part of this invention, illustrate exemplary embodiments of the disclosed methods and systems in which like reference numerals refer to the same parts throughout the different drawings. Components in the drawings are not necessarily to scale, emphasis instead being placed upon clearly illustrating the principles of the present invention. Some drawings may indicate the components using block diagrams and may not represent the internal circuitry of each component. It will be appreciated by those skilled in the art that invention of such drawings includes the invention of electrical components, electronic components or circuitry commonly used to implement such components. [0026] FIG. 1 illustrates an exemplary network architecture in which or with which the system of the present disclosure can be implemented, in accordance with an embodiment of the present disclosure. [0027] FIG. 2A illustrates an exemplary representation of system based on an artificial intelligence (AI) based architecture, in accordance with an embodiment of the present disclosure. [0028] FIG. 2B illustrates an exemplary representation of user equipment (UE) based on an artificial intelligence (AI) based architecture, in accordance with an embodiment of the present disclosure. [0029] FIG. 3 illustrates exemplary method flow diagram, in accordance with an embodiment of the present disclosure. [0030] FIG. 4 refers to the exemplary computer system in which or with which embodiments of the present invention can be utilized, in accordance with embodiments of the present disclosure. [0031] The foregoing shall be more apparent from the following more detailed description of the invention. DETAILED DESCRIPTION OF INVENTION [0032] In the following description, for the purposes of explanation, various specific details are set forth in order to provide a thorough understanding of embodiments of the present disclosure. It will be apparent, however, that embodiments of the present disclosure may be practiced without these specific details. Several features described hereafter can each be used independently of one another or with any combination of other features. An individual feature may not address all of the problems discussed above or might address only some of the problems discussed above. Some of the problems discussed above might not be fully addressed by any of the features described herein. [0033] The ensuing description provides exemplary embodiments only, and is not intended to limit the scope, applicability, or configuration of the disclosure. Rather, the ensuing description of the exemplary embodiments will provide those skilled in the art with an enabling description for implementing an exemplary embodiment. It should be understood that various changes may be made in the function and arrangement of elements without departing from the spirit and scope of the invention as set forth. [0034] Specific details are given in the following description to provide a thorough understanding of the embodiments. However, it will be understood by one of ordinary skill in the art that the embodiments may be practiced without these specific details. For example, circuits, systems, networks, processes, and other components may be shown as components in block diagram form in order not to obscure the embodiments in unnecessary detail. In other instances, well-known circuits, processes, algorithms, structures, and techniques may be shown without unnecessary detail in order to avoid obscuring the embodiments. [0035] The present invention provides a robust and effective solution to an entity or an organization by enabling the entity to implement a system for determining error inclusion and exclusion based on a deprivation index. Thus, the system and method of the present disclosure may be beneficial for both entities and users. The system can ensure effective utilization of social protection funds that is critical to minimize the errors of inclusion (EoI) and exclusion (EoE). The errors can be associated to specific scheme or can be at a higher level as well considering an individual or a family. An EoI, and an EoE model can consider a plurality of data sources, and a deprivation index to arrive at an insight. [0036] Referring to FIG. 1 that illustrates an exemplary network architecture (100) in which or with which system (110) of the present disclosure can be implemented, in accordance with an embodiment of the present disclosure. As illustrated in FIG. 1, by way of example and not by not limitation, the exemplary architecture (100) may include a plurality of users (102-1, 102-2…102-N) (collectively referred to as citizens (102) or users (102) and individually as citizen (102) or user (102)) associated with a plurality of first computing devices (104-1, 104-2,…104-N) (also referred to as user devices (104) or user computing devices (104) collectively and user device (104) individually), at least a network (106), at least a centralized server 112 and at least a second computing device (116) associated with an entity (114). More specifically, the exemplary architecture (100) includes a system (110) equipped with an artificial intelligence (AI) engine (214) (Ref. FIG. 2A) for facilitating determination of error inclusion and exclusion based on a deprivation index. The user device (104) may be communicably coupled to the centralized server (112) through the network (106) to facilitate communication therewith. As an example, and not by way of limitation, the user computing device (104) may be operatively coupled to the centralised server (112) through the network (106) and may be associated with the entity (114). Examples of the user computing devices (104) can include, but are not limited to, a computing device (104) associated with welfare-based assets, a smart phone, a portable computer, a personal digital assistant, a handheld phone and the like. [0037] The system (110) may be further operatively coupled to a second computing device (116) associated with the entity (114). The second computing device (116) may further be associated with a second user (118). The second user (118) can be anyone managing the system (110), a field inspector, an analyst, a system manager and the like. The system (110) may further be operatively coupled to a third computing device (108) (also referred to as the user computing device or user equipment (UE) hereinafter) associated with an entity (114). The entity (114) may include a company, a hospital, an organisation, a university, a lab facility, a business enterprise, or any other secured facility associated with welfare and social policy benefits. In some implementations, the system (110) may also be associated with the UE (108). The UE (108) can include a handheld device, a smart phone, a laptop, a palm top and the like. Further, the system (110) may also be communicatively coupled to the one or more first computing devices (104) via a communication network (106). [0038] The system (110) may receive a first set of data packets from the plurality of first computing devices (104), the first set of data packets pertaining to information on the one or more welfare-based schemes availed by the plurality of users (102) operating the plurality of first computing devices (104) and also receive a second set of data packets from the plurality of first computing devices, the second set of data packets pertaining to a set of welfare based scores pertaining to each user (102). The system may be further configured to extract by using the Ai engine (214), a first and a second set of attributes from the first set of data packets, the first set of attributes pertaining to error of inclusion (EOI) and the second set of attributes pertaining to error of exclusion (EOE). For example, the error of inclusion (EOI) may refer to an inclusion of a user who should not avail the one or more welfare schemes. It can be quantified as the proportion of a program’s beneficiaries who receive transfers despite not being in need of the program. It connotes the provision of aid to the non-needy. [0039] In an embodiment, the error of exclusion may refer to an error due to an exclusion of a user who should avail the one or more welfare schemes. It can be quantified as the proportion of people in need of the program/scheme but are omitted from the social transfer program. It implies failure to reach the needy. [0040] In an embodiment, the system may be further configured to extract, by using the AI engine (214), a third set of attributes from the of second set of data packets, the third set of attributes pertaining to a first and a second limit of a score range associated with the set of welfare-based scores. Based on the extracted first, second and third set of attributes, the system may further identify, by using the AI engine (214), a set of errors pertaining to any or the combination of error of inclusion and error of exclusion and then determine, using the AI engine (214), a deprivation index (also referred simply as the score herein) for each user based on the identification of the set of errors. [0041] In an embodiment, the AI engine may then compare the deprivation index of each user with the respective scores of the plurality of users and based on the comparison, determine a set of active users in descending order of the score, the deprivation index being within a predefined range with the first limit and the second limit of the deprivation index. For example, Suppose, X and Y are the first and the second limits for deprivation index respectively (for example, X= 80 and Y=20). Then, there are 3 brackets of scores: Score >=X Y< Score =X Y= X (category 1), there is no Error of Inclusion as the beneficiary is already included in the social program. [0069] In an exemplary embodiment, when the deprivation index is between X and Y (category 2), that is the deprivation index of the beneficiary is neither that high or nor that low, then there is no Error of Inclusion. However, this should be UI configurable and provided as a functionality for the client to decide. [0070] In an exemplary embodiment, when a deprivation index < = Y (category 3), If the deprivation index of an enrolled/ terminated beneficiary is very low, i.e. in the 3rd category, then this is a case of red alert. [0071] The beneficiary with a deprivation index =< Y should not have been eligible for the scheme. But we cannot make a judgement based upon some exceptional cases. Only if the number of such cases are greater than n for a particular social program, we need to make recommendations to the government for the policy changes. There may have been some eligibility criteria which is making non needy beneficiaries eligible. For example, in category 1, use cases of Socio-Economic Need Score may include calculations of socio-economic need score based errors of inclusion and exclusion, analytics based on time geography. For example, district with worst and best SEIC scores. Analytics on Progressive growth may include time-scale plotting of Socio-Economic Need Score, if this indicator trend is going in the right direction that means overall welfare is working fine. Will be used to find out the worst and best performers. The welfare-type based score must follow the lead of socio-economic need scores or should have a certain relationship with each other in some manners. TABLE 1 highlights the various categories Score Enrolled/Terminated For the scheme Score > = X Category 1 EOE: Not Applicable EOI: No Y< Score < X Category 2 EOE: Not Applicable EOI: No Score <= Y Category 3 EOE: Not applicable EOI: Yes [0072] The category 1 may further involve analytics by Combining with another Metric and may include socio-economic need score in isolation is not a good enough metric, but deprivation index combined with DBT given to the person/family is a very good measurement, Socio-Economic need score + Analytics, Socio-Economic need score + welfare-type based score and the like. For example: the most needy for us will be whose Need Score is High + No monetary benefit is provided + They are not even enrolled in a program. Thus, a deprivation index with analytics will give us the required insights and not an isolated composite deprivation index. [0073] The category 1 may further involve Calibration of Scores that includes margin of errors to calibrate a user score so that there should not be drastic changes in the score progression for a user w.r.t time. In time “T” the score should not change by more than |x| (T,x being configurable). [0074] Category 2 may include use cases for Welfare-type Based Scores that may involve analytics based on Time and Geography, analytics on Progressive Growth and Calculation of Sectoral Error of Exclusion/Inclusion. Analytics that can be performed with welfare-type based scores generated EOE/EOI/ Reports, Geography and Time Based Analytics: Configurable, Departmental Analytics: All the schemes for a department would be considered under a single bracket and a welfare-type based EOE/EOI can be used to do department based analysis. For example, how many people are needy in the particular welfare-type based Department. Finance and expenditure related analysis and recommendations for a particular department. [0075] The category 2 may further involve Policy Recommendations. There can be 2 results for EOE Calculations such as no cases of EOE or a very few cases of EOE concluding there is no problem in eligibility rules. If there are many users who have a high welfare-type based score but are still not eligible concluding, there are some errors with policy and this case calls for policy recommendations. [0076] Category 3 may include use case for scheme specific scoring: that may involve recommendations to the government on policy. The beneficiary with a deprivation index =< Y should not have been eligible for the scheme. If the number of such cases are greater than n for a particular social program, we need to make recommendations to the government. The recommendations to be provided to the govt can be based on further deep analysis. For example: Calculation of Errors based on geography and time. Configurable, Rule specific analysis: Which rules are particularly contributing to errors. Demographic factors-based analysis. Example: Gender Inclusivity and the like. [0077] For finding defaulters, for example, if there is Error of Inclusion for a large number of users in a particular geography, then there may be some faults in that geography handling, there needs to be done a deep analysis in that geography. Hence, geography should also be configurable so that client can do a need-based analysis on what is wrong. Additionally, when Gram Panchayats verify and deliver welfare, there may be many beneficiaries who are getting the benefit by them (Favorable benefit delivery) even when they have a very low deprivation index (EOI). The recommendations, in that case, would be more from a faulty point of view. DM can ask for a query. Government can do a deep Analysis based on the report thus created. Table 2 highlights Score brackets for Socio-Economic Need Score: Socio-Economic Need Score Enrolled/Terminated (in at least a scheme) Score > = X EOE: If no. of schemes avail < D% of Total Schemes: EOE Yes If no. of schemes avail >= D% of Total Schemes: EOE No EOI: Not Applicable Y< Score < X EOE: Not Applicable (Configurable) EOI: Not Applicable (Configurable) Score <= Y EOE: Not applicable EOI: If no. of schemes avail > D% of Total Schemes: EOI Yes If no. of schemes avail <= D% of Total Schemes: EOI No [0078] In an exemplary embodiment, there is no error of Exclusion in category 2, 3(configurable in case 2), as the deprivation index for the user is already low. If a person whose score is falling in category 1 and is availing number of schemes is less than D%(Configurable) of schemes active in his/her geography, then that is a case of EOE. For Example: For Belakote District , suppose there are 30 schemes up and running, if D%=20% and Active Schemes= 30 , for citizen is high need score(category 1,score>=x) 20% of 30 = 6. If the number of schemes a person is availing for is less than 6, then that case is EOE. [0079] In an exemplary embodiment, for, category 2,1 there is no error of Inclusion (configurable in case 2). [0080] In an exemplary embodiment, for category 3, if a person whose score is falling in category 3(less than or equal to Y) and is availing a number of schemes that are greater than D%(Configurable) of schemes active in his/her geography, then that is a case of EOI. For Example: For Belakote District --- suppose there are 30 schemes up and running, score<=Y, if D%=10% and Active Schemes= 30, 10% of 30 = 3. If the number of schemes a person is availing for is more than 3, then that case is EOI. [0081] In an exemplary embodiment, an approach to track progression may include documenting w.r.t time to show progression of a family in welfare services for a citizen socio-economic need scores. This will be Configurable as per client’s requirements. Frequency of score updation to be set (weekly/monthly/biannual etc), progression of score to be shown on that basis. [0082] In an exemplary embodiment, a welfare-type-Based EOE/EOI may involve calculation of a need score for each welfare-type for a user. Thus, a user will have a need score for every welfare-type. Mapped to the welfare-types would be schemes, i.e, each scheme would be mapped to a single/multiple types. Schemes and Welfare-type will have a Many-to-Many Relationship. For example, there may be at least five major welfare-type based scores: • Housing Need Score • Health Need Score • Education Need Score • Food Need Score • Livelihood Need Score [0083] How to pick a score in case of a scheme mapped to multiple welfare-type is yet to be decided once we get the data. Some recommendations are: considering multiple Score, considering highest score and the like. [0084] In an exemplary embodiment, the exclusion error is present in the case when people who are in need of the program/scheme but are omitted from the social transfer program. As the Eligible beneficiaries are not omitted for the social program, the EOE is not applicable in case of Terminated +Enrolled beneficiaries. Thus, for all three brackets EOE is not applicable. Table 3 highlights combined table for score calculation: Score Socio-Economic Need Score Welfare-type Based Score Scheme-Specific Score Score > = X EOE: If no. of schemes avail < D% of Total Schemes: EOE Yes If no. of schemes avail >= D% of Total Schemes: EOE No EOI: Not Applicable EOE: If no. of schemes avail < D% of Total Departmental Schemes: EOE Yes If no. of schemes avail >= D% of Total Departmental Schemes: EOE No EOI: Not Applicable EOE: Not Applicable EOI: No Y< Score < X EOE: Not Applicable (Configurable) EOI: Not Applicable (Configurable) EOE: Not Applicable (Configurable) EOI: Not Applicable (Configurable) EOE: Not Applicable EOI: No Score <= Y EOE: Not applicable EOI: If no. of schemes avail > D% of Total Schemes: EOI Yes If no. of schemes avail <= D% of Total Schemes: EOI No EOE: Not applicable EOI: If no. of schemes avail > D% of Total Departmental Schemes: EOI Yes If no. of schemes avail <= D% of Total Departmental Schemes: EOI No EOE: Not applicable EOI: Yes [0085] In an exemplary embodiment, time validity for user data and score may include the encompassing the following: ? Data Newness to be considered while calculating EOE/EOI, considering only terminated/ enrolled is a way of limiting data wrt. time. ? Users Time Validity: Suppose a scheme is terminated 4 years old, we cannot pick up that old data or citizen. Thus it is encouraged to consider users: ? Who have been enrolled in the last one year or ? Currently enrolled ? However, this time validity is to be kept variable as per the business case and is to be defined by Client. Time limit to not be hard-cored. ? For a citizen: Progressive scores would be kept documented to show progression of a family in welfare services. To show how the family is progressing. ? Frequency of score updation to be set (weekly/monthly/biannual etc.), progression of score to be shown on that basis frequency and further analysis to be made on that. ? From a financial point of view Batch Mode (Weekly Basis) is encouraged, though it's an architectural call. [0086] FIG. 4 illustrates an exemplary computer system in which or with which embodiments of the present invention can be utilized in accordance with embodiments of the present disclosure. As shown in FIG. 4, computer system 400 can include an external storage device 410, a bus 420, a main memory 430, a read only memory 440, a mass storage device 450, communication port 460, and a processor 470. A person skilled in the art will appreciate that the computer system may include more than one processor and communication ports. Processor 440 may include various modules associated with embodiments of the present invention. Communication port 460 can be any of an RS-232 port for use with a modem based dialup connection, a 10/100 Ethernet port, a Gigabit or 10 Gigabit port using copper or fiber, a serial port, a parallel port, or other existing or future ports. Communication port 460 may be chosen depending on a network, or any network to which computer system connects. Memory 430 can be Random Access Memory (RAM), or any other dynamic storage device commonly known in the art. Read-only memory 440 can be any static storage device(s). Mass storage 450 may be any current or future mass storage solution, which can be used to store information and/or instructions. [0087] Bus 420 communicatively couples processor(s) 470 with the other memory, storage and communication blocks. Optionally, operator and administrative interfaces, e.g. a display, keyboard, and a cursor control device, may also be coupled to bus 420 to support direct operator interaction with a computer system. Other operator and administrative interfaces can be provided through network connections connected through communication port 460. Components described above are meant only to exemplify various possibilities. In no way should the aforementioned exemplary computer system limit the scope of the present disclosure. [0088] While considerable emphasis has been placed herein on the preferred embodiments, it will be appreciated that many embodiments can be made and that many changes can be made in the preferred embodiments without departing from the principles of the invention. These and other changes in the preferred embodiments of the invention will be apparent to those skilled in the art from the disclosure herein, whereby it is to be distinctly understood that the foregoing descriptive matter to be implemented merely as illustrative of the invention and not as limitation. [0089] A portion of the disclosure of this patent document contains material which is subject to intellectual property rights such as, but are not limited to, copyright, design, trademark, IC layout design, and/or trade dress protection, belonging to Jio Platforms Limited (JPL) or its affiliates (herein after referred as owner). The owner has no objection to the facsimile reproduction by anyone of the patent document or the patent disclosure, as it appears in the Patent and Trademark Office patent files or records, but otherwise reserves all rights whatsoever. All rights to such intellectual property are fully reserved by the owner. ADVANTAGES OF THE PRESENT DISCLOSURE [0090] The present disclosure provides for a system and method that ensures effective utilization of social protection funds, and minimize the errors of inclusion (EoI) and exclusion (EoE). [0091] The present disclosure provides for a system and method that reduces ultimate repercussions of errors on policy and policy-level changes, and using only the verified and latest data thus enrolled or terminated citizens with a time validity. [0092] The present disclosure provides for a system and method that uses only shareable data. [0093] The present disclosure provides for a system and method that solves many data issues by the implementation as only citizens that are being enrolled/terminated for at least one scheme are picked. [0094] The present disclosure provides for a refined survey/new service. [0095] It is an object of the present disclosure to calculate the score to be anonymised for score calculation. WE CLAIMS: 1. A system (110) for assessment of errors of inclusion and exclusion in one or more welfare schemes for a plurality of users (102), said system (110) comprising; one or more processors (202) operatively coupled to a plurality of first computing devices (104), the one or more processors (202) coupled with a memory (204), wherein said memory (204) stores instructions which when executed by the one or more processors (202) causes said system (110) to: receive a first set of data packets from a plurality of first computing devices (104), the first set of data packets pertaining to information on the one or more welfare-based schemes availed by the plurality of users (102) operating the plurality of first computing devices (104); receive a second set of data packets from the plurality of first computing devices, the second set of data packets pertaining to a set of welfare based scores pertaining to each user (102); extract a first set of attributes from the first set of data packets, the first set of attributes pertaining to error of inclusion (EOI), wherein the error of inclusion refers to an inclusion of a user who should not avail the one or more welfare schemes; extract a second set of attributes from the first set of data packets, the second set of attributes pertaining to error of exclusion (EOE), wherein the error of exclusion refers to an error due to an exclusion of a user who should avail the one or more welfare schemes; extract a third set of attributes from the of second set of data packets, the third set of attributes pertaining to a first and a second limit of a score range associated with the set of welfare-based scores; based on the extracted first, second and third set of attributes, identify, by using an artificial intelligence (AI) engine (214), a set of errors pertaining to any or the combination of error of inclusion and error of exclusion; determine, using the AI engine (214), a deprivation index for each user based on the identification of the set of errors. 2. The system as claimed in claim 1, wherein the system is further configured to compare the deprivation index of each user with the respective scores of the plurality of users; and based on the comparison, determine a set of active users in descending order of the deprivation index, the deprivation index being within a predefined range with the first limit and the second limit of the score range. 3. The system as claimed in claim 1, wherein the system is further configured to use at least three types of scores such as a Socio-Economic Need Score, a Welfare-type Based Score, and a Scheme Specific Need-Score to calculate the EOE and the EOI and further determine the deprivation index of each user. 4. The system as claimed in claim 1, wherein the deprivation index provides information about an overall performance of the one or more welfare schemes, and how much each user is in need of the one or more welfare schemes. 5. The system as claimed in claim 4, wherein based on the deprivation index, the system is configured to assess an overall effectiveness of the one or more welfare schemes, a plurality of possibilities to explore, and related one or more policy decisions. 6. The system as claimed in claim 4, wherein each said welfare scheme is associated with one or more welfare types, wherein the system is configured to map each said welfare scheme with the respective one or more welfare types. 7. The system as claimed in claim 4, wherein the system is configured to determine a welfare based score for each respective welfare scheme type. 8. The system as claimed in claim 4, wherein the welfare based score includes at least five major welfare-type based scores such as Housing Need Score, Health Need Score, Education Need Score, Food Need Score, and Livelihood Need Score. 9. The system (110) as claimed in claim 1, wherein the system is further configured to check if a user has already availed the one or more welfare-based schemes based on the extracted first and second set of attributes. 10. The system as claimed in claim 9, the system is configured to terminate a user that has exhausted all benefits associated with the one or more welfare schemes. 11. A user equipment (UE) (108) for assessment of errors of inclusion and exclusion in one or more welfare schemes for a plurality of users (102), said UE (108) comprising; an edge processor (222) and a receiver operatively coupled to a plurality of first computing devices (104), the processor (222) coupled with a memory (224), wherein said memory (224) stores instructions which when executed by the processor (222) causes said UE (108) to: receive a first set of data packets from a plurality of first computing devices (104), the first set of data packets pertaining to information on the one or more welfare-based schemes availed by the plurality of users (102) operating the plurality of first computing devices (104); receive a second set of data packets from the plurality of first computing devices, the second set of data packets pertaining to a set of welfare based scores pertaining to each user (102); extract a first set of attributes from the first set of data packets, the first set of attributes pertaining to error of inclusion (EOI), wherein the error of inclusion refers to an inclusion of a user who should not avail the one or more welfare schemes; extract a second set of attributes from the first set of data packets, the second set of attributes pertaining to error of exclusion (EOE), wherein the error of exclusion refers to an error due to an exclusion of a user who should avail the one or more welfare schemes; extract a third set of attributes from the of second set of data packets, the third set of attributes pertaining to a first and a second limit of a score range associated with the set of welfare-based scores; based on the extracted first, second and third set of attributes, identify, by using an artificial intelligence (AI) engine (234), a set of errors pertaining to any or the combination of error of inclusion and error of exclusion; determine, using the AI engine (234), a deprivation index for each user based on the identification of the set of errors. 12. A method for assessment of errors of inclusion and exclusion in one or more welfare schemes for a plurality of users (102), said method comprising; receiving, by one or more processors (202), a first set of data packets from a plurality of first computing devices (104), the first set of data packets pertaining to information on the one or more welfare-based schemes availed by the plurality of users (102) operating the plurality of first computing devices (104), wherein the one or more processors (202) are operatively coupled to the plurality of first computing devices (104), the one or more processors (202) coupled with a memory (204), wherein said memory (204) stores instructions which are executed by the one or more processors (202); receiving, by the one or more processors (202), a second set of data packets from the plurality of first computing devices, the second set of data packets pertaining to a set of welfare based scores pertaining to each user (102); extracting, by the one or more processors (202), a first set of attributes from the first set of data packets, the first set of attributes pertaining to error of inclusion (EOI), wherein the error of inclusion refers to an inclusion of a user who should not avail the one or more welfare schemes; extracting, by the one or more processors (202), a second set of attributes from the first set of data packets, the second set of attributes pertaining to error of exclusion (EOE), wherein the error of exclusion refers to an error due to an exclusion of a user who should avail the one or more welfare schemes; extracting, by the one or more processors (202), a third set of attributes from the of second set of data packets, the third set of attributes pertaining to a first and a second limit of a score range associated with the set of welfare-based scores; based on the extracted first, second and third set of attributes, identifying, by using an artificial intelligence (AI) engine (214), a set of errors pertaining to any or the combination of error of inclusion and error of exclusion; determining, using the AI engine (214), a deprivation index for each user based on the identification of the set of errors. 13. The method as claimed in claim 12, wherein the method further comprises the step of: comparing, by the AI engine (214), the deprivation index of each user with the respective scores of the plurality of users; and based on the comparison, determining, by the AI engine (214), a set of active users in descending order of the deprivation index, the deprivation index being within a predefined range with the first limit and the second limit of the score range. 14. The method as claimed in claim 12, wherein the method further comprises the step of: using, by the one or more processors (202), at least three types of scores such as a Socio-Economic Need Score, a Welfare-type Based Score, and a Scheme Specific Need-Score to calculate the EOE and the EOI and further determine the deprivation index of each user. 15. The method as claimed in claim 12, wherein the deprivation index provides information about an overall performance of the one or more welfare schemes, and how much each user is in need of the one or more welfare schemes. 16. The method as claimed in claim 14, wherein based on the deprivation index, the method further comprises the step of: assessing an overall effectiveness of the one or more welfare schemes, a plurality of possibilities to explore, and related one or more policy decisions. 17. The method as claimed in claim 14, wherein each said welfare scheme is associated with one or more welfare types, wherein the method further comprises the step of: mapping each said welfare scheme with the respective one or more welfare types. 18. The method as claimed in claim 14, wherein the method further comprises the step of: determining a welfare based score for each respective welfare scheme type. 19. The method as claimed in claim 14, wherein the welfare based score includes at least five major welfare-type based scores such as Housing Need Score, Health Need Score, Education Need Score, Food Need Score, and Livelihood Need Score. 20. The method as claimed in claim 12, wherein the method further comprises the step of: checking if a user has already availed the one or more welfare-based schemes based on the extracted first and second set of attributes. 21. The method as claimed in claim 12, wherein the method further comprises the step of: terminating a user that has exhausted all benefits associated with the one or more welfare schemes.