USING A FINANCIAL PROFILE”

TECHNICAL FIELD

[001 ] The present disclosure relates to a financial profile analysis of a target entity. More particularly, the present disclosure relates to a method and a system for analyzing the target entity by the financial entity to provide one or more financial sendees using a financial profile of the target entity.

BACKGROUND

[002] Financial entities such as banks provide financial services to various entities. The entities may be merchants, businesses, vendors, and the like. The entities are referred herein as target entities. Typically, the financial entities provide one or more financial services to the target entities. The one or more financial services may include lending loan, provisioning cash at Point of Sale (PoS) service and so on. However, to provide such financial sendees, it may be required to analyze finances of the target entity. By such analysis, the financial entity' may determine whether the target entities are eligible for the one or more financial sendees. For example, the banks determine whether the target entities are likely to repay the loans. For such determination, the banks may consider payment history of the target merchants. Further, growth of Automated Teller Machines (ATMs) has been saturated. There is an increase in demand for cash at PoS service in the target entities. Usually, the banks provide the cash at PoS sendees by analyzing cash flow of the target entities.

[003] Conventional techniques use credit score of the target entities to determine provision of the financial services which alone may not be sufficient. Further, digital transaction history of tire target entities is analyzed to determine provision of the financial services. Conventional techniques restrict the analysis to digital transactions of the target entities. This may result in declining provision of the loans (for example) to the target entities, that might otherwise have a relatively high chance of repaying the loans. Hence, there is a requirement of a system that analyzes the target entities accurately, to provide the financial services to the target entities.

[004] The information disclosed in this background of the disclosure section is only for enhancement of understanding of the general background of the invention and should not be taken as an acknowledgement or any form of suggestion that this information forms the prior art already known to a person skilled in the art.

SUMMARY

[005] In an embodiment, the present disclosure discloses a method for analyzing a target entity using a financial profde. Tire method comprises receiving financial information related to a target entity. The financial information comprises at least one of transaction information of the target entity, details of a transaction account associated with the target entity, a plurality of transactions of the target entity comprising digital transactions and cash transactions, a location of the target entity, Automated Teller Machine (ATM) data related to the target entity and a financial entity, Current Account and Savings Account (CASA) data, and business data of the target entity. Further, the method comprises generating a financial profile for the target entity based on the financial information, indicating a number of digital transactions and a number of cash transactions performed for a pre-determined period of time. Furthermore, the method comprises analyzing the target entity using the financial profile. The analysis is used to provide one or more financial sendees to the target entity.

[006] In an embodiment, the present disclosure discloses an analysis system for analyzing a target entity using a financial profile. The analysis system comprises one or more processors and a memory. The one or more processors are configured to receive financial information related to the target entity. The financial information comprises at least one of transaction information of the target entity, details of a transaction account associated with the target entity, a plurality of transactions of the target entity comprising digital transactions and cash transactions, a location of the target entity. Automated Teller Machine (ATM) data related to the target entity and a financial entity, Current Account and Savings Account (CASA) data, and business data of the target entity. Further, the one or more processors are configured to generate a financial profile for the target entity based on the financial information. The financial profile indica tes a number of digital transactions and a number of cash transactions performed for a pre-determined period of time. Furthermore, the one or more processors are configured to analyze the target entity using the financial profile. The analysis is used to provide one or more financial services to the target entity'.

[007] The foregoing summary is illustrative only and is not intended to he in any way limiting. In addition to the illustrative aspects, embodiments, and features described above, further aspects, embodiments, and features will become apparent by reference to the drawings and the following detailed description.

BRIEF DESCRIPTION OF THE ACCOMPANYING DRAWINGS [008] The novel features and characteristics of the disclosure are set forth in the appended claims. The disclosure itself, however, as well as a preferred mode of use, further objectives, and advantages thereof, will best be understood by reference to the following detailed description of an illustrative embodiment when read in conjunction with the accompanying figures. One or more embodiments are now described, by way of example only, with reference to the accompanying figures wherein like reference numerals represent like elements and in which:

[009] 0igure 1 shows exemplary environment for analyzing a target entity using a financial profile, in accordance with some embodiments of the present disclosure;

[0010] Figure 2 illustrates an internal architecture of an analysis system for analyzing a target entity using a financial profile, in accordance with some embodiments of the present disclosure;

[0011] Figure 3 shows an exemplary flow chart illustrating method steps for analyzing a target entity using a financial profile, in accordance with some embodiments of the present disclosure ;

[0012] Figures 4A - 4C show exemplary- illustrations for generating financial profile for a target entity and one or more entities, in accordance with some embodiments of the present disclosure; and

[0013] Figures 4D and 4E show exemplary illustrations for generating optimal profile for analyzing a target entity, in accordance with some embodiments of the present disclosure;

[0014] Figure 5A shows exemplary illustration for determining feasibility of installation of cash at Point of Sale (PoS) service, in accordance with some embodiments of the present disclosure;

[0015] Figure 5B shows exemplary illustration for provisioning banking channel optimization service, in accordance with some embodiments of the present disclosure; and [0016] Figure 6 shows a block diagram of a general-purpose computing system for analyzing a target entity' using a financial profile, in accordance with embodiments of the present disclosure.

[0017] It should be appreciated by those skilled in the art that any block diagram herein represents conceptual views of illustrative systems embodying the principles of the present subject matter. Similarly, it will be appreciated that any flow' charts, flow diagrams, state transition diagrams, pseudo code, and the like represent various processes which may be substantially represented in computer readable medium and executed by a computer or processor, whether or not such computer or processor is explicitly shown.

DETAILED DESCRIPTION

[0018] In the present document, the word "exemplary'” is used herein to mean "serving as an example, instance, or illustration." Any embodiment or implementation of the present subject matter described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments.

[0019] While the disclosure is susceptible to various modifications and alternative forms, specific embodiment thereof has been shown by way of example in the drawings and will he described in detail below'. It should be understood, however that it is not intended to limit the disclosure to the particular forms disclosed, but on the contrary, the disclosure is to cover all modifications, equivalents, and alternatives falling within the scope of the disclosure.

[0020] The terms “comprises”, “comprising”, or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a setup, device or method that comprises a list of components or steps does not include only those components or steps but may include other components or steps not expressly listed or inherent to such setup or device or method. In other words, one or more elements in a system or apparatus proceeded by “comprises ... a” does not, without more constraints, preclude the existence of other elements or additional elements in the system or apparatus.

[0021] Embodiments of the present disclosure relates to a method for analyzing a target entity _' using a financial profile. Financial information related to the target entity is received. The financial information comprises at least one of transaction information of the target entity, details of a transaction account associated with the target entity, a plurality of transactions of the target entity comprising digital transactions and cash transactions, a location of the target entity, Automated Teller Machine (ATM) data related to the target entity and a financial entity, Current Account and Savings Account (CASA) data, and business data of the target entity. A financial profile is generated for the target entity based on the financial information. The financial information indicates a number of digital transactions and a number of cash transactions performed for a pre-determmed period of time. The target entity is analyzed using the financial profile. The analysis is used to provide one or more financial sendees to the target entity. Tire analysis comprises calculating a financial service score. For example, the one or more financial sendees may comprise providing a loan to the target entity based on the financial service score. Further, the analysis comprises determining feasibility of installation of cash at Point of Sale (PoS) sendee in the target entity. In the present disclosure, the cash transactions along with the digital transactions are considered to generate the financial profile. Further, different parameters such as CASA data and business data are considered to generate the financial profile. Hence, accurate analysis is ensured. Also, financial entities such as banks can take data driven decision using the analysis, to provide the financial sendees to the target entity.

[0022] Figure 1 shows exemplary environment 100 for analyzing a target entity using a financial profile, in accordance with some embodiments of the present disclosure. The environment 100 shown in Figure 1 comprises a target entity 101, a financial entity 102, a communication network 103, an analysis system 104, one or more entities 105, and one or more Automated Teller Machines (ATMs) 106. The target entity 101 maybe an entity requiring one or more financial sen/ices from the financial entity 102. The target entity 101 may be a merchant, a business, a vendor, an establishment, and the like. For example, the target entity 101 may be a merchant owning a shop. In another example, the target entity 101 may be a supermarket. The financial entity 102 may be an entity providing the one or more financial serv ices to the target entity 101. For example, the financial entity 102 may be a bank or any other financial institution. In an embodiment, the target entity 101 may be associated with the financial entity 102. For example, the target entity 101 may own a financial account in the financial entity 102. The one or more financial sen/ices provided by the financial entity 102 may be a loan, cash at Point of Sale (PoS) service, banking channel optimization sendee, and th e like. The one or more entities 105 may be entities in die location of the target entity 101. The one or more entities 105 may be a merchant, a business, a vendor, an establishment, and the like . The analysis system 104 is configured to analyze the target entity 101 using a financial profile. The analysis system 104 may provide the analysis to the financial entity 102. The financial entity 102 may provide the one or more financial services to the target entity 101 based on the analysis. In an embodiment, the analysis system 104 may be an integral part of the financial entity 102. In an embodiment, the analysis system 104 may be a dedicated server or a cloud-based server, in communication with the financial entity ⁷ 102. The analysis system 104 may receive required data from the target entity 101, the financial entity 102, the one or more entities 105, the one or more ATMs 106, and transmit the analysis to the financial entity 102. The analysis system 104 may communicate with the target entity 101, the financial entity 102, the one or more entities 105, and the one or more ATMs 106 via the communication network 103. The communication network 103 may include, without limitation, a direct interconnection, Local Area Network (LAN), Wide Area Network (WAN), wireless network (e.g., using Wireless Application Protocol), the Internet, and the like. In an embodiment, the analysis system 104 may communicate with the target entity 101, tire financial entity 102, the one or more entities 105, and the one or more ATMs 106 with a dedicated network.

[0023] The analysis system 104 may be configured to receive financial information related to the target entity 101. The financial information may comprise at least one of transaction information of the target entity 101, details of a transaction account associated with the target entity 101, a plurality of transactions of the target entity 101 comprising digital transactions and cash transactions, a location of the target entity 101, Automated Teller Machine (ATM) data related to the target entity 101 and the financial entity 102, Current Account and Savings Account (CASA) data, and business data of the target entity 101. In an embodiment, the financial information may be a pre-stored data. The analysis system 104 may receive the financial information from the financial entity 102. In an embodiment, the analysis system 104 may receive the financial information from the target entity 101.

[0024] Further, the analysis system 104 may be configured to generate the financial profile for the target entity 101 based on the financial information. The financial profile indicates a number of digital transactions and a number of cash transactions performed for a predetermined period of time. The number of digital transactions indicate number of transactions associated with the target entity 101 performed using a digital mode of payment. The digital transactions may comprise transactions performed using scan and pay mode, PoS, and the like. The number of cash transactions indicate number of transactions associated with the target entity 101 performed using a cash mode of payment. The cash transactions may comprise at least one of cash withdrawals, cash deposits by the target entity 101, and cash transactions related to business expenditures of the target entity 101. For example, the business expenditures may comprise infrastructure costs, equipment costs, maintenance costs, transport costs, and the like.

[0025] In an embodiment of the present disclosure, the analysis comprises calculating a financial sendee score of the target entity 101. The analysis system 104 is configured to compare the financial profile of the target entity 101 with an optimal profile determined for the target entity 101 for calculating the financial service score. The optimal profile is determined by identifying the one or more entities 105 similar to the target entity 101. Th e identification is based on at least one of a merchant category code and a location, associated with each entity from the one or more entities 105 and the target entity 101.

[0026] In an embodiment of the present disclosure, the analysis comprises determining feasibility of installation of cash at PoS service in the target entity 101. The cash at PoS sendee is a facility through which a user may use a card issued by a financial entity associated with the user, to withdraw cash by swiping the card at PoS terminal at the location of the target entity 101. For example, a customer may use a debit card to withdraw the cash at the location of a merchant using the cash at PoS sendee. Tire analysis system 104 is configured to determine the feasibility of installation of the cash at PoS sendee in the target entity 101 based on the financial profile of the target entity 101 and the information related to at least one of one or more existing ATMs 106, a plurality of entities, and users in a location of the target entity 101.

[0027] The analysis system 104 may include Central Processing Units 107 (also referred as “CPUs" or “one or more processors 107" ), Input/ Output (I/O) interface 108, and a memory 109. In some embodiments, the memory 109 may be communicatively coupled to the processor 107. The memory 109 stores instructions executable by the one or more processors 107. The one or more processors 107 may comprise at least one data processor for executing program components for executing user or system-generated requests. The memory 109 may be communicatively coupled to the one or more processors 107. The memory 109 stores instructions, executable by the one or more processors 107, which, on execution, may cause the one or more processors 107 to analyze the target entity 101 using the financial profile. In an embodiment, the memory 109 may include one or more modules 111 and data 110. The one or more modules 111 may be configured to perform the steps of the present disclosure using the data 110, to analyze the target entity 101 using the financial profile. In an embodiment, each of the one or more modules 111 may be a hardware unit which may be outside the memory 109 and coupled with the analysis system 104. Further, the I/O interface 108 is coupled with the one or more processors 107 through which an input signal or/and an output signal is communicated. For example, the analysis system 104 may receive the financial information via the I/O interface 108. Also, the analysis system 104 may transmit output of the analysis via the I/O interface 108 to the financial entity 102. In an embodiment, the analysis system 104, for analyzing the target entity 101 using the financial profile, may be implemented in a variety of computing systems, such as a laptop computer, a desktop computer, a Personal Computer (PC), a notebook, a smartphone, a tablet, e-book readers, a server, a network server, a cloud- based server and the like.

[0028] Figure 2 illustrates an internal architecture 200 of the analysis system 104 in accordance with some embodiments of the present disclosure. The analysis system 104 may include the one or more processors 107, the memory 109 and the I/O interface 108. The memory 109 may include the modules 111 and the data 110.

[0029] In one implementation, the modules 111 may include, for example, a financial information input module 208, a financial profile generation module 209, an analysis module 210, and other modules 211. It will be appreciated that such aforementioned modules 111 may be represented as a single module or a combination of different modules. In one implementation, the data 110 may include, for example, entity data 201 , financial information 202, financial profile data 203, optimal profile data 204, analysis data 205, ATM data 206, and other data 207.

[0030] In an embodiment, the financial information input module 208 may be configured to receive the financial information from the financial entity 102. The financial information may be stored as the financial information 202 in the memory 109. The financial information 202 may comprise at least one of transaction information of the target entity 101, details of the transaction account associated with the target entity 101, the plurality of transactions of the target entity 101 comprising digital transactions and cash transactions, the location of the target entity 101, the ATM data related to the target entity 101 and the financial entity 102, the CASA data, and business data of the target entity 101. The digital transactions may comprise transactions performed using a digital mode of payment. For example, the digital transactions may comprise transactions performed using scan and pay mode, PoS, and the like. The cash transactions may comprise transactions performed using a cash mode of payment. The cash transactions may comprise at least one of cash withdrawals, cash deposits by the target entity 101, and cash transactions related to business expenditures of the target entity 101. For example, the cash transactions may be ATM withdrawals. The CASA data may have information of cash deposited in current account and savings account of the target entity 101. The business data of the target entity 101 may comprise data related to the business of the entity. For example, the business data may comprise operational expenditures, tax filings data and the like. In an embodiment, the financial information input module 2.08 may receive the financial information 202 from the target entity 101, For example, the location data of the target entity 101, the business data of the target entity 101, a merchant category code of the target entity 101 may be received from the target entity 101. The financial information received from the target entity 101 may be stored as the entity data 201 in the memory 109.

[0031] In an embodiment, the financial profile generation module 209 may be configured to generate the financial profile for the target entity 101 based on the financial information 202. The financial profile indicates a number of digital transactions and a number of cash transactions performed for a pre-determined period of time. The financial profile may be stored as the financial profile data 203 in the memory 109. The financial profile data 203 may indicate tire number of digital transactions and the number of cash transactions performed for the predetermined period of time in any data representation format. For exampl e, the financial profil e may be stored as a graph, table, and the like. A person skilled in the art will appreciate that the financial profile can be represented in any form to indicate the number of digital transactions and the number of cash transactions. The financial profile generation module 209 may generate the financial profile indicating the number of digital transactions based on the transaction information of the target entity 101, details of a transaction account associated with the target entity 101, the digital transactions performed by the target entity 101 and the like. The financial profile generation m odule 209 may generate the financial profile indicating the number of cash transactions based on the cash transactions, the ATM data related to the target entity 101 and the financial entity 102, the CASA data, business data of the target entity 101, and the like. A person skilled in the art will appreciate that any technique known in the art may be implemented to determine the financial profile using the financial information 202.

[0032] Further, the financial profile generation module 209 may be configured to generate the optimal profile for the target entity 101. The optimal profile may comprise optimal value of digital transactions and cash transactions required for providing the one or more financial services. The optimal value may be value determined considering the financial information 202 of the one or more entities 105 in the location of the target entity 101. The financial profile generation module 209 may receive the location of the target entity 101 and the merchant category code of the target entity 101 from the entity data 201. The financial profile generation module 209 may be configured to identify the one or more entities 105 similar to the target entity 101 based on at least one of a merchant category code and a location, associated with each entity from the one or more entities 105 and the target entity 101. In an embodiment, the financial information 202 may be a pre-stored data. In an embodiment, the financial profile generation module 209 may receive the financial information 202 of the one or more entities 105, from one or more financial entities associated with the one or more entities 105. In an embodiment, the financial profile generation module 209 may receive the financial information 202 of the one or more entities 105, from the one or more entities 105. The merchant category code and the location of the one or more entities 105 may be stored as the entity data 201 in the memory 109. Further, the financial information of the one or m ore entities 105 may be stored as the financial information 202 in the memory' 109. The financial profile generation module 209 may be configured to determine the optimal profile for the target entity 101 by aggregating the financial information 202 of the one or more entities 105 and the target entity 101. One or more financial profiles may be generated from the financial information 202 of the one or more entities 105. The financial profile generation module 209 may perform time series analysis on the one or more financial profiles of the one or more entities 105 and the financial profile of the target entity 101 to determ ine the optimal profile. The time series analysis is defined as analysis of a series of data points indexed in time order. The number of digital transactions and the number of cash transactions of the one or more entities 105 and the target entity 101 may be the data points indexed over the pre-determined period of time. For example, the predetermined period may be a month. The number of digital transactions and the number of cash transactions may be analyzed to generate the optimal profile for die target entity 101. A person skilled in the art will appreciate that any known methods of performing the time series analysis may be used to determine the optimal profile for the target entity 101. The optimal profile may be stored as the optimal profile data 204 in the memory 109. The optimal profile may be stored in any of data representation formats in the memory 109. For example, the optimal profile may be stored as a graph, table, and the like. A person skilled in the art will appreciate that the optimal profile may be represented in any form such that the optimal profile can be compared with the financial profile determined for the target entity 101 . [0033] In an embodiment, the analysis module 210 may receive the financial profile data 203 and the optimal profile data 204. The analysis module 210 may be configured to analyze the target entity 101 using the financial profile. The analysis module 210 may analyze the target entity 101 to determine provisi on of the one or more fi nancial sendees to the target entity 101 by the financial entity 102. The one or more financial services may be lending loan, provisioning the cash at PoS service and so on. In an embodiment, the analysis module 210 may be configured to calculate the financial sendee score of the target entity 101. The analysis module 210 may compare the financial profile of the target entity 101 with the optimal profile determined for the target entity 101 to calculate the financial sendee score. The financial sendee score may be stored as tire analysis data 205 in the memory 109. Further, the financial entity 102 may provide the one or more financial sendees to the target entity 101 based on value of the financial sendee score. In an embodiment, the analysis module 210 may be configured to determine feasibility of installation of the cash at PoS sendee in the target entity' 101. The analysis module 210 may be configured to receive the information related to the one or more existing ATMs 106, the plurality of entities, and the users in a location of the target entity 101 , from the financial entity 102. For example, the plurality of entities may be merchants in the location of the target entity 101. The users may be associated with the plurality of entities. For example, the users may be customers to the merchants in the location of the target entity _' 101. The analysis module 210 may identify distribution of the plurality of entities around the one or more existing ATMs 106. The analysis module 210 may identify patterns in users visiting the plurality of entities and the one or more existing ATMs 106. The analysis module 210 may cluster the plurality of entities and the one or more existing ATMs 106 based on the patterns. In an embodiment, the analysis module 210 may be configured to receive the information related to the one or more existing ATMs 106 in a location of the target entity 101, from the one or more existing ATMs 106. In an embodiment, the analysis module 210 maybe configured to receive the information related to the plurality of entities and the users from a database. The information related to the one or more existing ATMs 106 may be stored as ATM data 206 in the memory 109. The ATM data 206 may comprise a number of the one or more existing ATMs 106 in the location of the target entity 101, a distance between the one or more existing ATMs 106, cash transaction data at the one or more existing ATMs 106, operational data related to the one or more existing ATMs 106, and cash demands in the one or more existing ATMs 106. The analysis module 210 may determine the feasibility of installation of the cash at PoS service in the target entity 101 based on the financial profile and the information related to the one or more existing ATMs 106. The analysis module 210 may determine a total amount associated with the cash transactions related to the target entity 101 to be greater than a threshold value derived using the information related to the one or more existing ATMs 106. In an embodiment, the analysis comprises identifying inaccessibility of cash to a user, at an ATM 106 in the location of the target entity 101. The cash may be inaccessible to the user due to a failed cash transaction, technical glitches, requested cash greater than ATM limit and the like. The target entity 101 may provide the cash at PoS service to one or more users. The analysis module 210 may identify the user to be related to the target entity 101 based on the financial information 202 of the target entity 101 and identification of the user, Tire digital transactions of the user with the target entity 101 may be identified from the financial information 202 of the target entity 101 and an identify of the user. The identification may determine a relation of the user with the target entity 101. Further, the analysis module 210 may generate a notification to provide to the user based on the identification. The notification comprises information associated with the target entity 101. In an embodiment, the analysis module 210 may notify locations of a plurality of entities, to the user for withdrawing the cash.

[0034] The other data 207 may store data, including temporary' data and temporary' files, generated by the one or more modules 111 for performing tire various functions of the analysis system 104. The one or more modules 111 may also include the other modules 211 to perform various miscellaneous functionalities of the analysis system 104. For example, the other modules 211 may comprise a user interface. It will be appreciated that such modules may be represented as a single module or a combination of different modules.

[0035] Figure 3 shows an exemplary' flow chart illustrating method steps for analyzing the target entity 101 using the financial profile, in accordance with some embodiments of the present disclosure. As illustrated in Figure 3, the method 300 may comprise one or more steps. The method 300 may be described in the general context of computer executable instructions. Generally, computer executable instructions can include routines, programs, objects, components, data structures, procedures, modules, and functions, which perform particular functions or implement particular abstract data types.

[0036] The order in which the method 300 is described is not intended to be construed as a limitation, and any number of the described method blocks can be combined in any order to implement the method. Additionally, individual blocks may be deleted from the methods without departing from the scope of the subject matter described herein. Furthermore, the method can be implemented in any suitable hardware, software, firmware, or combination thereof.

[0037] At step 301, financial information 202 related to the target entity 101 is received by the analysis system 104. The analysis system 104 receives the financial information 202 from the financial entity 102. Tire financial information 202 may comprise at least one of the transaction information of the target entity 101, details of the transaction account associated with the target entity 101, the plurality of transactions of the target entity 101 comprising digital transactions and cash transactions, the location of the target entity 101, the ATM data related to the target entity 101 and the financial entity 102, the CASA data, and the business data of the target entity 101. The digital transactions may comprise transactions performed using a digital mode of payment. For example, the digital transactions may comprise transactions performed using scan and pay mode, PoS, and the like. The cash transactions may comprise transactions performed using a cash mode of payment. The cash transactions may comprise at least one of cash withdrawals, cash deposits by the target entity 101, and cash transactions related to business expenditures of the target entity 101. For example, the cash transactions may be ATM withdrawals. In an embodiment, analysis system 104 may receive the financial information 202 from the target entity 101. For example, the location data of the target entity 101, the business data of the target entity 101, a merchant category code of the target entity 101 may be received from the target entity 101. In another example, the merchant category code of the target entity 101 may be received from the financial entity 102.

[0038] At step 302, the financial profile for the target entity 101 is generated by tire analysis system 104 based on the financial information 202. The financial profile indicates a number of digital transactions and a number of cash transactions performed for the pre-detemiined period of time. For example, the pre -determined period may be a month, lire analysis system 104 may generate the financial profile based on the financial information 202 of a month The analysis system 104 may generate the financial profile indicating the number of digital transactions based on tire transaction information of the target entity 101, details of a transaction account associated with the target entity 101, the digital transactions performed by the target entity 101 and the like. The analysis system 104 may generate the financial profile indicating the number of cash transactions based on the cash transactions, the ATM data related to the target entity 101 and the financial entity 102, the CASA data, business data of the target entity 101, and the like. Referring to example shown in Figure 4A, 400 shows the financial profile generated for the target entity 101. 400 is a graph showing the number of digital transactions 401 and the number of cash transactions 402 over the predetermined period of time (shown as time in Figure 4A). Further, the analysis system 104 may be configured to identify the one or more entities 105 similar to the target entity 101 based on at least one of the merchant category code and the location, associated with each entity from the one or more entities 105 and the target entity 101. The analysis system 104 may receive the financial information 202 of the one or more entities 105. For example, target entity A may be a supermarket in location A with the merchant category code as 5000. Entity B and entity C may be supermarkets with the same merchant category code as 5000 in the same location A. The analysis system 104 may identify entity B and entity C as the one or more entities 105 similar to the target entity 101. The analysis system

104 may generate one or more financial profiles of the one or more entities 105 from the financial information 202. Referring to Figure 4B, 403 shows the aggregated financial profile of the one or more entities 105 similar to the target entity 101 based on the merchant category code. 403 is a graph showing aggregated digital transactions 404 and aggregated cash transactions 405 of the one or more entities 105 similar to the target entity 101 based on the merchant category code, over the predetermined period of time (shown as time in Figure 4B). Referring to Figure 4C, 406 shows the aggregated financial profile of the one or more entities

105 similar to the target entity 101 based on the location. For example, entity D and entity E may be individual merchants in the location A. 406 is a graph showing aggregated digital transactions 407 and aggregated cash transactions 408 of the one or more entities 105 similar to the target entity 101 based on the location, over the predetermined period of time (shown as time in Figure 4C). Further, the analysis system 104 may be configured to determine the optimal profile for the target entity 101 by performing time series analysis on the one or more financial profiles of the one or more entities 105 and the financial profile of the target entity 101. For example, financial profile of the target entity 101 and the one or more financial profiles of the one or more entities 105 may be analyzed. The analysis may comprise determining correlations and variations the one or more financial profiles of the one or more entities 105 and the financial profile of the target entity 101. The correlations may be determined between the financial profile of the target entity 101 and the one or more financial profiles of the one or more entities 105 for generating the optimal profile for the target entity 101. The variations in the financial profile of the target entity 101 and the one or more financial profiles of the one or more entities 105 may he used to determine transaction growth or decline. A person skilled in the art will appreciate that any known methods of performing the time series analysis may be used to determine the optimal profile for the target entity 101. The optimal profile indicates optimal value of digital transactions and cash transactions required for providing the one or more financial services. The optimal value may be value determined considering the financial information 202 of the one or more entities 105 in the location of the target entity 101. Referring to Figure 4D, 409 shows the optimal profile generated for the target entity 101. 409 is a graph showing the optimal value of digital transactions 410 and cash transactions 411 over th e predetermined period of time (shown as time in Figure 4D). For example, the optimal value of digital transactions may be 0.65 and the optimal value of cash transactions may be 0.35 in a scale of 0 to 1. A person skilled in the art will appreciate that aggregation of data for generating the optimal profile can be performed using any known methods.

[0039] At step 303, the target entity 101 is analyzed by the analysis system 104 using the financial profile, to provide the one or more financial serv ices to the target entity 101. In an embodiment, the analysis system 104 may be configured to calculate the financial service score of the target entity 101. The analysis system 104 may compare the financial profile of the target entity 101 with the optimal profile determined for the target entity 101 to calculate the financial service score. Referring to example shown in Figure 4E, 412 shows the calculation of the financial service score. 401 and 402 are the number of digital and cash transactions of the target entity 101. For example, the number of digital transactions may be 0.75 and the number of cash transactions may be 0.25. 410 and 411 are the optimal value for digital transactions and cash transactions. For example, the optimal value of digital transactions may be 0.65 and the optimal value of cash transactions may be 0.35. The analysis system 104 may calculate the financial service score by comparing the financial profile of the target entity 101 and the optimal profile.

An exemplary _' equation for calculating the financial sendee score is provided as equation (1) below:

Financial service score = 1- ((optimal cash value-target entity cash value) + (optimal digital value -target entity digital value)) ......... (1)

[0040] The optimal value for digital transactions and cash transactions are referred as optimal digital value and optimal cash value, respectively. The number of digital transactions and the number of cash transactions of the target entity 101 are referred as target entity digital value and target entity cash value, respecti vely . Considering the example of Figure 4E in equation (1), the financial service score is 0.80. The financial entity' 102 may provide the one or more financial sendees to the target entity 101 based on value of the financial sendee score. When the value of the financial sendee score is more, probability to provision the one or more financial sendees to the target entity 101 by the financial entity 102 is high. A person skilled in the art will appreciate that any other methods such as learning algorithms may be used, to determine the probability to provision the one or more financial sendees to the target entity 101.

[0041] In another embodiment, the analysis system 104 may be configured to determine feasibility of installation of the cash at PoS service in the target entity 101. The analysis system 104 may be configured to receive the information related to the one or more existing ATMs 106, the plurality of entities, and the users in the location of the target entity 101. The information related to the one or more existing ATMs 106 may comprise a number of the one or more existing ATMs 106 in the location of the target entity 101, a distance between the one or more existing ATMs 106, cash transaction data at the one or more existing ATMs 106, operational data related to the one or more existing ATMs 106 and cash demands in the one or more existing ATMs 106. The cash transaction data may comprise cash withdrawals, cash deposits and the like. The operational data related to the one or more existing ATMs 106 may comprise data related to technical glitches at the one or more existing ATMs, cash availability at the one or more existing ATMs 106, and the like. The cash availability at the one or more existing ATMs 106 may comprise information such as a current cash available at the one or more existing ATMs 106, ATM limit on cash withdrawals, out-of-cash data related to the one or more existing ATMs 106, and the like. A requirement of the cash at PoS sendee in the target entity 101 may be determined from the information related to the one or more existing ATMs 106. The analysis system 104 may determine the feasibility of installation of the cash at PoS sendee in the target entity 101 based on the financial profile and the information related to the one or more existing ATMs 106, the plurality of entities and the users. The analysis system 104 may determine installation of the cash at PoS to be feasible when a cash flow of the target entity 101 is high. The analysis system 104 may determine a total amount associated with the cash transactions related to the target entity 101 to be greater than a threshold value derived using the information related to the one or more existing ATMs 106. For example, consider an ATM A at a location A. The cash demand may be high at the ATM A. Consider the total amount associated with the cash transactions related to a merchant A in the location A, are greater than the threshold value. The threshold value may be determined based on an average amount of cash withdrawal at the ATM A. Hence, installing of the cash at PoS service to the merchant A is determined to be feasible. Reference is now made to Figure 5A. In example 500 shown in Figure 5 A, the target entity 101 is merchant A. The one or more entities 105 similar to the target entity 101 based on the location 502 of the target entity 101, are merchant B and merchant C. 501 shows the financial profiles of the merchant A, merchant B and merchant C, indicating the number of cash transactions. 504 shows exemplary priorities for installing the cash at PoS service based on the financial profiles of the merchant A, merchant B and merchant C. As can be seen, the merchant A has higher priority, since the number of cash transactions is an increasing curve. Hence, the analysis system 104 may determine the installation of the cash at PoS service to the merchant A as feasible. 503 may he user interface showing the locations of the merchant A, merchant B and merchant C, and feasibility of installation of the cash at PoS sendee, to the financial entity 102. In another example, the analysis system 104 may analyze the cash demands at a bank branch. Hie analysis system 104 may determine the feasibility of installation of the cash at PoS service based on cash demands at the bank branch. In an embodiment, the analysis system 104 may be configured to determine the feasibility of installation of the cash at PoS service based on the information related to the one or more existing ATMs 106, the plurality of entities, and the users in a location of the target entity 101. For example, the plurality of entities may be merchants in the location of the target entity 101. The users may be associated with the plurality of entities. For example, the users may be customers to the merchants in tire location of the target entity 101. The analysis module 210 may identify distribution of the plurality of entities around the one or more existing ATMs 106. For example, consider two ATMs, ATM 1 and ATM 2. Merchant 1, merchant 2, merchant 3, and merchant 4 may be distributed around ATM 1. Merchant 5, merchant 6, merchant 7, and merchant 8 may be distributed around ATM 2. The analysis system 104 may identify that the cash demand is high at ATM 1. Hie analysis system 104 may determine feasibility of the cash at PoS sendee in the merchant 1, merchant 2, merchant 3, and merchant 4. Further, the analysis system 104 may identity paterns in users visiting the merchant 1, merchant 2, merchant 3, merchant 4 and the ATM i, for offloading the ATM i . Hie analysis system 104 may determine the feasibility based on the patterns.

[0042] Reference is now made to Figure 5 B. In example 505, consider the cash at PoS service is provided to the merchant A, merchant B and merchant C. 506 shows exemplary indications of the number of cash transactions of the merchant A, merchant B and merchant C. The priorities may be determined based on the number of cash transactions. A user may visit an ATM in the location 502 to withdraw cash. The ATM may not have cash or there may be a maintenance issue at the ATM. The ATM may recommend the locations of the merchant A, merchant B and merchant C according to the priorities on the user interface 503, so that the user may withdraw the cash using the cash at PoS sendee in the merchant A, merchant B and merchant C. In another example, the bank associated with the user may be in the location 502. The analysis system 104 may recommend the user to withdraw the cash at bank branch.

[0043] In an embodiment, the analysis compri ses identifying inaccessibility' of cash to a user, at an ATM 106 in the location of the target entity 101. Tire cash may be inaccessible to the user due to a failed cash transaction, technical glitches, requested cash greater than ATM limit and the like. The target entity 101 may provide the cash at PoS service to one or more users. The analysis system 104 may identify the user to be related to the target entity 101 based on the financial information 202 of the target entity 101 and identification of the user. The digital transactions of the user with the target entity 101 may be identified from the financial information 202 of the target entity 101 and an identity of the user. The identification may determine a relation of the user with the target entity 101. For example, the user may be a customer. A customer identification in the financial information of the target entity 101 may be performed to determine that the user is a customer of the target entity 101. Further, the analysis system 104 may generate a notification to provide to the user based on the identification. The notification comprises information associated with the target entity 101. In an embodiment, the analysis system 104 may notify locations of a plurality of entities, to the user for withdrawing the cash. For example, the information associated with the target entity 101 may be a location of the target entity 101. For example, user A may be a customer to the target entity 101. The target entity 101 may be merchant A. The user A may visit the ATM A to withdraw the cash. The cash transaction may fail because there may be no cash at the ATM A. The analysis system 104 may notify the user A to visit the merchant A to avail the cash at PoS service, on a user interface. The user A may visit the merchant A to withdraw' the cash and may make a purchase at the merchant A. In an embodiment, the analysis system 104 may notify locations of a plurality of entities, to the user for withdrawing the cash. For example, the ATM A m ay be having a high cash demand. Hie cash may not be available at the ATM A when the user A initiates cash withdrawal. The analysis system 104 may notify the location of the merchant A as a first preference. Further, the analysis system 104 may notify locations of merchant B and merchant C with second preference and a third preference, respectively, based on the financial profiles of the merchant B and merchant C. Hence, it is convenient for the user to withdraw' the cash and avail services at the target entities at a same time. Service defined in the embodiment is termed as the banking channel optimization service in the present description. The ATM may be a banking channel. The banking channel may be optimized by providing the notification to the user, when the cash is inaccessible to the user.

COMPUTER SYSTEM

[0044] Figure 6 illustrates a block diagram of an exemplary computer system 600 for implementing embodiments consistent with the present disclosure. In an embodiment, the computer system 600 may be used to implement the analysis system 104. Tims, the computer system 600 may be used to receive the financial information of the target entity 612, the financial entity 613, the one or more entities 614 and generate the financial profile to analyze the target entity 612 using the financial profile. Also, the computer system 600 may be used to receive the information related to the one or more existing ATMs 615 (ATMs in Figure 6) to analyze the target entity' 612. The computer system 600 may comprise a Central Processing Unit 602 (also referred as “CPU” or “processor”). The processor 602 may comprise at least one data processor. The processor 602 may include specialized processing units such as integrated system (bus) controllers, memory management control units, floating point units, graphics processing units, digital signal processing units, etc.

[0045] The processor 602 may be disposed in communication with one or more input/output (I/O) devices (not shown) via I/O interface 601. The I/O interface 601 may employ communication protocols/methods such as, without limitation, audio, analog, digital, monoaural, RCA, stereo, IEEE (Institute of Electrical and Electronics Engineers) -1394, serial bus, universal serial bus (USB), infrared, PS/2, BNC, coaxial, component, composite, digital visual interface (DVI), high-definition multimedia interface (HDMI), Radio Frequency (RF) antennas, S- Video, VGA, IEEE 802.n /b/g/n/x, Bluetooth, cellular (e.g,, code-division multiple access (CDMA), high-speed packet access (HSPA+), global system for mobile communications (GSM), long-term evolution (LTE), WiMax, or the like), etc.

[0046] Using the I/O interface 601, the computer system 600 may communicate with one or more I/O devices. For example, the input device 610 may be an antenna, keyboard, mouse, joystick, (infrared) remote control, camera, card reader, fax machine, dongle, biometric reader, microphone, touch screen, touchpad, trackball, stylus, scanner, storage device, transceiver, video device/source, etc. The output device 611 may be a printer, fax machine, video display (e.g., cathode ray tube (CRT), liquid crystal display (LCD), light-emitting diode (LED), plasma, Plasma display panel (PDP), Organic light-emitting diode display (OLED) or the like), audio speaker, etc. [0047] The computer system 600 is connected to the laser integrated system 612 through a communication network 609. The laser integrated system 612 is used to provide the detected energy levels to the computer system 600. The processor 602 may be disposed in communication with the communication network 609 via a network interface 603. The network interface 603 may communicate with the communication network 609. The network interface 603 may employ connection protocols including, without limitation, direct connect, Ethernet (e.g., twisted pair 10/100/1000 Base T), transmission control protocol/internet protocol (TCP/IP), token ring, IEEE 802.1 la/b/g/n/x, etc. The communication network 609 may include, without limitation, a direct interconnection, local area network (LAN), wide area network (WAN), wireless network (e.g., using Wireless Application Protocol), the Internet, etc. The network interface 603 may employ connection protocols include, but not limited to, direct connect, Ethernet (e.g., twisted pair 10/100/1000 Base T), transmission control protocol/internet protocol (TCP/IP), token ring, IEEE 802.1 la/b/g/n/x, etc.

[0048] The communication network 609 includes, but is not limited to, a direct interconnection, an e-commerce network, a peer to peer (P2P) network, local area network (LAN), wide area network (WAN), wireless network (e.g., using Wireless Application Protocol), the Internet, Wi- Fi, and such. The first network and the second network may either be a dedicated network or a shared network, which represents an association of the different types of networks that use a variety of protocols, for example, Hypertext Transfer Protocol (HTTP), Transmission Control Protocol/internet Protocol (TCP/IP), Wireless Application Protocol (WAP), etc., to communicate with each other. Further, the first network and the second network may include a variety of network devices, including routers, bridges, servers, computing devices, storage devices, etc,

[0049] In some embodiments, the processor 602 may be disposed in communication with a memory 605 (e.g., RAM, ROM, etc. not shown in Figure 6) via a storage interface 604. The storage interface 604 may connect to memory' 605 including, without limitation, memory drives, removable disc drives, etc., employing connection protocols such as serial advanced technology atachment (SATA), Integrated Drive Electronics (IDE), IEEE- 1394, Universal Serial Bus (USB), fiber channel, Small Computer Systems Interface (SCSI), etc. The memory drives may further include a drum, magnetic disc drive, magneto-optical drive, optical drive, Redundant Array of Independent Discs (RAID), solid-state memory devices, solid-state drives, etc. [0050] The memory 605 may store a collection of program or database components, including, without limitation, user interface 606, an operating system 607, web browser 608 etc. In some embodiments, computer system 600 may store user/application data, such as, the data, variables, records, etc., as described in this disclosure. Such databases may be implemented as fault-tolerant, relational, scalable, secure databases such as Oracle © or Sybase®.

[0051 ] The operating system 607 may facilitate resource management and operation of the computer system 600. Examples of operating systems include, without limitation, APPLE MACINTOSH ^R OS X, UNIX ^R , UNIX-like system distributions (E.G., BERKELEY SOFTWARE DISTRIBUTION™ (BSD), FREEBSD™, NETBSD™, OPENBSD™, etc.), LINUX DISTRIBUTIONS™ (E.G., RED HAT™, UBUNTU™, KUBUNTU™, etc.), IBM™ OS/2, MICROSOFT™ WINDOWS™ (XP™, VISTA™/7/8, 10 etc.), APPLET IOS™, GOOGLE* ANDROID™, BLACKBERRY ^R OS, or the like.

[0052] In some embodiments, the computer system 600 may implement the web browser 608 stored program component. The web browser 608 may be a hypertext viewing application, for example MICROSOFT* INTERNET EXPLORER™, GOOGLE* CHROME™ ⁰ , MQZILLA* FIREFOX™, APPLE* SAFARI ¹ * ¹ , etc. Secure web browsing may be provided using Secure Hypertext Transport Protocol (HTTPS), Secure Sockets Layer (SSL), Transport Layer Security (TLS), etc. Web browsers 608 may utilize facilities such as AJAX™, DHTML™, ADOBE* FLASH™, JAVASCRIPT™, JAVA™, Application Programming Interfaces (APIs), etc. In some embodiments, the computer system 600 may implement a mail server (not shown in Figure) stored program component. Hie mail server may be an Internet mail server such as Microsoft Exchange, or the like. The mail server may utilize facilities such as ASP ¹ * ¹ , ACTIVEX™, ANSI™ C++/C#, MICROSOFT*, .NET™, CGI SCRIPTS™, JAVA™, JAVASCRIPT™, PERL™, PHP™, PYTHON™, WEBQBJECTS™, etc. The mail server may utilize communication protocols such as Internet Message Access Protocol (IMAP), Messaging Application Programming Interface (MAPI), MICROSOFT* exchange. Post Office Protocol (POP), Simple Mail Transfer Protocol (SMTP), or the like. In some embodiments, the computer system 600 may implement a mail client stored program component. The mail client (not shown in Figure) may be a mail viewing application, such as APPLE* MAIL™, MICROSOFT* ENTOURAGE™, MICROSOFT ^R OUTLOOK™, MOZILLA* THUNDERBIRD™, etc. [0053] Furthermore, one or more computer-readable storage media may be utilized in implementing embodiments consistent with the present disclosure. A computer-readable storage medium refers to any type of physical memory on which information or data readable by a processor may be stored. Thus, a computer-readable storage medium may store instructions for execution by one or more processors, including instructions for causing the processors) to perform steps or stages consistent with the embodiments described herein. The term ^" computer- readable medium” should be understood to include tangible items and exclude carrier waves and transient signals, i.e., be non -transitory'. Examples include Random Access Memory (RAM), Read-Only Memory (ROM), volatile memory, non-volatile memory, hard drives, Compact Disc Read-Only Memory' (CD ROMs), Digital Video Disc (DVDs), flash drives, disks, and any other known physical storage media.

[0054] Embodiments of the present disclosure considers cash transactions of a target entity, along with digital transactions to generate a financial profile. Further, different parameters such as Current Account and Savings Account (CASA) data and business data are considered to generate the financial profile. Hence, accurate analysis of the target entity is ensured. Also, financial entities such as banks can take data driven decision using th e analysis, to provide the financial sen/ices to the target entity. The cash transactions of the target entity are used to determining feasibility of installing cash at Point of Sale (PoS) service at the target entity-. Hence, the banks may use this analysis for installing the cash at PoS service.

[0055] Embodiments of the present disclosure provisions banking channel optimization sendee. The present disclosure notifies a user, target entities with the cash at PoS service, when the cash is not available at ATM. The target entities are notified by considering relationship of the user with the target entities. Hence, it is convenient for the user to withdraw- the cash and avail services at th0 target entities at a same time.

[0056] The terms "an embodiment", "embodiment", "embodiments", "the embodiment", "the embodiments", "one or more embodiments", "some embodiments", and "one embodiment" mean "one or more (but not all) embodiments of the invention(s)" unless expressly specified otherwise.

[0057] The terms "including", "comprising", “having” and variations thereof mean "including but not limited to", unless expressly specified otherwise. [0058] The enumerated listing of items does not imply that any or ail of the items are mutually exclusive, unless expressly specified otherwise. The terms "a", "an" and "the" mean "one or more", unless expressly specified otherwise.

[0059] A description of an embodiment with several components in communication with each other does not imply that all such components are required. On the contrary' a variety of optional components are described to illustrate the wide variety of possible embodiments of the invention.

[0060] When a single device or article is described herein, it will be readily apparent that more than one device/article (whether or not they cooperate) may be used in place of a single device/article. Similarly, where more than one device or article is described herein (whether or not they cooperate), it will be readily apparent that a single device/article may be used in place of the more than one device or article or a different number of devices/articles may be used instead of the shown number of devices or programs. The functionality and/or the features of a de vice may be alternatively embodied by one or more other devices winch are not explicitly described as having such functionality/features. Thus, other embodiments of the invention need not include the device itself.

[0061] The illustrated operations of Figure 3 show certain events occurring in a certain order, in alternative embodiments, certain operations may be performed in a different order, modified, or removed. Moreover, steps may be added to the above described logic and still conform to the described embodiments. Further, operations described herein may occur sequentially or certain operations may be processed in parallel. Yet further, operations may be performed by a single processing unit or by distributed processing units.

[0062] Finally, the language used in the specification has been principally selected for readability and instructional purposes, and it may not have been selected to delineate or circumscribe the inventive subject mater. It is therefore intended that the scope of the invention be limited not by this detailed description, but rather by any claims that issue on an application based here on. Accordingly, the disclosure of the embodiments of the invention is intended to be illustrative, but not limiting, of the scope of the invention, which is set forth in the following claims. [0063] While various aspects and embodiments have been disclosed herein, other aspects and embodiments will be apparent to those skilled in the art. The various aspects and embodiments disclosed herein are for purposes of illustration and are not intended to be limiting, with the true scope being indicated by the following claims.