Claims:1. A system (10) for assisting transaction management, wherein the system (10) comprises:
a processing subsystem (20) hosted on a server (30), and configured to execute on a network to control bidirectional communications among a plurality of modules comprising:
an input module (40) configured to:
receive information corresponding to at least one of one or more products and one or more services made available for sale by a first user, via a chatbot (130) upon registering the first user; and
receive one or more purchase preferences of a second user via the chatbot (130) upon registration, based on a personalized purchase-based questionnaire conducted via the chatbot (130) with the second user;
an input processing module (50) operatively coupled to the input module (40), wherein the input processing module (50) is configured to:
verify availability of at least one of the one or more products and the one or more services by conducting a personalized sale-based questionnaire with the first user in real-time based on a processing of the one or more purchase preferences; and
share the information corresponding to at least one of the one or more products and the one or more services with the second user via the chatbot (130), upon verifying the availability;
a follow-up module (60) operatively coupled to the input processing module (50), wherein the follow-up module (60) is configured to conduct a follow-up questionnaire with the second user at a predefined time interval until a positive response on purchasing of the at least one of the one or more products and the one or more services is received from the second user based on the information shared by the input processing module (50);
a categorization module (70) operatively coupled to the follow-up module (60), wherein the categorization module (70) is configured to:
create one or more labels based on at least one of the personalized purchase-based questionnaire and the follow-up questionnaire conducted with the second user; and
categorize the second user under a predefined category upon assigning with the one or more labels;
a connection module (80) operatively coupled to the categorization module (70), wherein the connection module (80) is configured to connect the second user with the first user via the chatbot (130) based on the categorization of the second user, upon receiving the positive response from the second user, wherein the positive response corresponds to the purchasing of at least one of the one or more products and the one or more services; and
a transaction module (90) operatively coupled to the connection module (80), wherein the transaction module (90) is configured to:
conduct a transaction-based questionnaire corresponding to the purchase, with the second user via the chatbot (130) upon connecting the second user with the first user; and
initiate a monetary transaction process between the first user and the second user via a predefined transaction mode based on the transaction-based questionnaire conducted with the second user to purchase at least one of the one or more products and the one or more services, thereby assisting the transaction management.
2. The system (10) as claimed in claim 1, wherein the input processing module (50) is configured to generate one or more sale-related questions upon understating a response corresponding to each of the one or more sale-related questions using one or more artificial intelligence-based techniques to conduct the personalized sale-based questionnaire with the first user in real-time.
3. The system (10) as claimed in claim 2, wherein the one or more artificial intelligence-based techniques comprises a natural language processing technique, an image processing technique, or an optical character recognition technique.
4. The system (10) as claimed in claim 1, wherein the input processing module (50) is configured to process the one or more purchase preferences using one or more artificial intelligence-based techniques to understand the corresponding one or more purchase preferences.
5. The system (10) as claimed in claim 1, wherein the processing subsystem (20) comprises a valuation module (200) operatively coupled to the input module (40), wherein the valuation module (200) is configured to assign a purchasing amount to at least one of the one or more products and the one or more services made available for sale by the first user upon analyzing the information received by the input module (40) using a machine learning technique and a data science technique.
6. The system (10) as claimed in claim 5, wherein the processing subsystem (20) comprises a loan management module (210) operatively coupled to the valuation module (200), wherein the loan management module (210) is configured to:
receive a plurality of transaction-related documents corresponding to the second user based on the purchasing amount assigned by the valuation module (200), when the predefined transaction mode comprises a loan-based transaction; and
determine eligibility of the second user to receive a loan of the corresponding purchasing amount for completing the transaction process upon analyzing the plurality of transaction-related documents based on one or more bank-related parameters.
7. A method (280) for assisting transaction management, wherein the method (280) comprises:
receiving, by an input module (40), information corresponding to at least one of one or more products and one or more services made available for sale by a first user, via a chatbot upon registering the first user; (290)
receiving, by the input module (40), one or more purchase preferences of a second user via the chatbot upon registration, based on a personalized purchase-based questionnaire conducted via the chatbot with the second user; (300)
verifying, by an input processing module (50), availability of at least one of the one or more products and the one or more services by conducting a personalized sale-based questionnaire with the first user in real-time based on a processing of the one or more purchase preferences; (310)
sharing, by the input processing module (50), the information corresponding to at least one of the one or more products and the one or more services with the second user via the chatbot, upon verifying the availability; (320)
conducting, by a follow-up module (60), a follow-up questionnaire with the second user at a predefined time interval, until a positive response on purchasing of the at least one of the one or more products and the one or more services is received from the second user based on the information shared by the input processing module; (330)
creating, by a categorization module (70), one or more labels based on at least one of the personalized purchase-based questionnaire and the follow-up questionnaire conducted with the second user; (340)
categorizing, by the categorization module (70), the second user under a predefined category upon assigning with the one or more labels; (350)
connecting, by a connection module (80), the second user with the first user via the chatbot based on the categorization of the second user, upon receiving the positive response from the second user, wherein the positive response corresponds to the purchasing of at least one of the one or more products and the one or more services; (360)
conducting, by a transaction module (90), a transaction-based questionnaire corresponding to the purchase, with the second user via the chatbot upon connecting the second user with the first user; and (370)
initiating, by the transaction module (90), a monetary transaction process between the first user and the second user via a predefined transaction mode based on the transaction-based questionnaire conducted with the second user to purchase at least one of the one or more products and the one or more services, thereby assisting the transaction management (380).
8. The method (280) as claimed in claim 7, wherein conducting the personalized purchase-based questionnaire, the follow-up questionnaire, and the transaction-based questionnaire with the second user comprises generating one or more purchase-related questions, one or more follow-up questions, and one or more transaction-related questions upon understating a response corresponding to each of the one or more purchase-related questions, the one or more follow-up questions, and the one or more transaction-related questions respectively using one or more artificial intelligence-based techniques.
9. The method (280) as claimed in claim 7, comprises assigning, by a valuation module (200), a purchasing amount to at least one of the one or more products and the one or more services made available for sale by the first user upon analyzing the information received by the input module using a machine learning technique and a data science technique.
10. The method (280) as claimed in claim 9, comprises:
receiving, by a loan management module (210), a plurality of transaction-related documents corresponding to the second user based on the purchasing amount assigned by the valuation module when the predefined transaction mode comprises a loan-based transaction; and
determining, by the loan management module (210), eligibility of the second user to receive a loan of the corresponding purchasing amount for completing the transaction process upon analyzing the plurality of transaction-related documents based on one or more bank-related parameters.
Dated this 19th day of August 2021 Signature

Harish Naidu
Patent Agent (IN/PA-2896)
Agent for the Applicant
, Description:FIELD OF INVENTION
[0001] Embodiments of a present disclosure relate to a management of one or more transactions, and more particularly to a system and a method for assisting transaction management.
BACKGROUND
[0002] Transaction refers to a completed agreement between a buyer and a seller to exchange goods, services, or financial assets. Further, assisting the transaction management refers to helping the buyer and the seller in planning, organizing, managing, decision making, and the like about the exchange of the goods, the services, or the financial assets. In a conventional approach, people visit stores physically and search for the desired product and then purchase. However, such an approach possesses certain drawbacks such as it is time-consuming, tiring, and very difficult for people to actually find out the exact product. There are multiple approaches implemented to overcome such drawbacks.
[0003] One such approach includes a system and method which include searching for products on an online platform by applying multiple filters based on pre-stored data. However, in such an approach, there is a high probability that the pre-stored data is not up to date as an owner of the product may forget to update the data associated with the product. Therefore, misleading customers about the availability of the product. Also, in such an approach, the customers are supposed to invest some time to search for the desired product. Before actually searching for the product the customers have to plan, gather information about the product, and the like, thereby making such an approach time-consuming.
[0004] Hence, there is a need for an improved system and method for assisting transaction management which addresses the aforementioned issues.
BRIEF DESCRIPTION
[0005] In accordance with one embodiment of the disclosure, a system for assisting transaction management is provided. The system includes a processing subsystem hosted on a server. The processing subsystem is configured to execute on a network to control bidirectional communications among a plurality of modules. The processing subsystem includes an input module. The input module is configured to receive information corresponding to at least one of one or more products and one or more services made available for sale by a first user, via a chatbot upon registering the first user. The input module is also configured to receive one or more purchase preferences of a second user via the chatbot upon registration, based on a personalized purchase-based questionnaire conducted via the chatbot with the second user. The processing subsystem also includes an input processing module operatively coupled to the input module. The input processing module is configured to verify availability of at least one of the one or more products and the one or more services by conducting a personalized sale-based questionnaire with the first user in real-time based on a processing of the one or more purchase preferences. The input processing module is also configured to share the information corresponding to at least one of the one or more products and the one or more services with the second user via the chatbot, upon verifying the availability. Further, the processing subsystem also includes a follow-up module operatively coupled to the input processing module. The follow-up module is configured to conduct a follow-up questionnaire with the second user at a predefined time interval until a positive response on purchasing of the at least one of the one or more products and the one or more services is received from the second user based on the information shared by the input processing module. Furthermore, the processing subsystem also includes a categorization module operatively coupled to the follow-up module. The categorization module is configured to create one or more labels based on at least one of the personalized purchase-based questionnaire and the follow-up questionnaire conducted with the second user. The categorization module is also configured to categorize the second user under a predefined category upon assigning with the one or more labels. Furthermore, the processing subsystem also includes a connection module operatively coupled to the categorization module. The connection module is configured to connect the second user with the first user via the chatbot based on the categorization of the second user, upon receiving the positive response from the second user. The positive response corresponds to the purchasing of at least one of the one or more products and the one or more services. Furthermore, the processing subsystem also includes a transaction module operatively coupled to the connection module. The transaction module is configured to conduct a transaction-based questionnaire corresponding to the purchase, with the second user via the chatbot upon connecting the second user with the first user. The transaction module is also configured to initiate a monetary transaction process between the first user and the second user via a predefined transaction mode based on the transaction-based questionnaire conducted with the second user to purchase at least one of the one or more products and the one or more services, thereby assisting the transaction management.
[0006] In accordance with another embodiment, a method for assisting transaction management is provided. The method includes receiving information corresponding to at least one of one or more products and one or more services made available for sale by a first user, via a chatbot upon registering the first user. The method also includes receiving one or more purchase preferences of a second user via the chatbot upon registration, based on a personalized purchase-based questionnaire conducted via the chatbot with the second user. Further, the method also includes verifying availability of at least one of the one or more products and the one or more services by conducting a personalized sale-based questionnaire with the first user in real-time based on a processing of the one or more purchase preferences. Furthermore, the method also includes sharing the information corresponding to at least one of the one or more products and the one or more services with the second user via the chatbot, upon verifying the availability. Furthermore, the method also includes conducting a follow-up questionnaire with the second user at a predefined time interval until a positive response on purchasing of the at least one of the one or more products and the one or more services is received from the second user based on the information shared by the input processing module. Furthermore, the method also includes creating one or more labels based on at least one of the personalized purchase-based questionnaire and the follow-up questionnaire conducted with the second user. Furthermore, the method also includes categorizing the second user under a predefined category upon assigning with the one or more labels. Furthermore, the method also includes connecting the second user with the first user via the chatbot based on the categorization of the second user, upon receiving the positive response from the second user, wherein the positive response corresponds to the purchasing of at least one of the one or more products and the one or more services. Furthermore, the method also includes conducting a transaction-based questionnaire corresponding to the purchase, with the second user via the chatbot upon connecting the second user with the first user. Furthermore, the method also includes initiating a monetary transaction process between the first user and the second user via a predefined transaction mode based on the transaction-based questionnaire conducted with the second user to purchase at least one of the one or more products and the one or more services, thereby assisting the transaction management.
[0007] To further clarify the advantages and features of the present disclosure, a more particular description of the disclosure will follow by reference to specific embodiments thereof, which are illustrated in the appended figures. It is to be appreciated that these figures depict only typical embodiments of the disclosure and are therefore not to be considered limiting in scope. The disclosure will be described and explained with additional specificity and detail with the appended figures.
BRIEF DESCRIPTION OF THE DRAWINGS
The disclosure will be described and explained with additional specificity and detail with the accompanying figures in which:
[0008] FIG. 1 is a block diagram representation of a system for assisting transaction management in accordance with an embodiment of the present disclosure;
[0009] FIG. 2 is a block diagram representation of an exemplary embodiment of the system for assisting the transaction management of FIG. 1 in accordance with an embodiment of the present disclosure;
[0010] FIG. 3 is a block diagram of a transaction management computer or a transaction management server in accordance with an embodiment of the present disclosure; and
[0011] FIG. 4 (a) and FIG. 4(b) are flow charts representing steps involved in a method for assisting transaction management in accordance with an embodiment of the present disclosure.
[0012] Further, those skilled in the art will appreciate that elements in the figures are illustrated for simplicity and may not have necessarily been drawn to scale. Furthermore, in terms of the construction of the device, one or more components of the device may have been represented in the figures by conventional symbols, and the figures may show only those specific details that are pertinent to understanding the embodiments of the present disclosure so as not to obscure the figures with details that will be readily apparent to those skilled in the art having the benefit of the description herein.
DETAILED DESCRIPTION
[0013] For the purpose of promoting an understanding of the principles of the disclosure, reference will now be made to the embodiment illustrated in the figures and specific language will be used to describe them. It will nevertheless be understood that no limitation of the scope of the disclosure is thereby intended. Such alterations and further modifications in the illustrated system, and such further applications of the principles of the disclosure as would normally occur to those skilled in the art are to be construed as being within the scope of the present disclosure.
[0014] The terms "comprises", "comprising", or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a process or method that comprises a list of steps does not include only those steps but may include other steps not expressly listed or inherent to such a process or method. Similarly, one or more devices or sub-systems or elements or structures or components preceded by "comprises... a" does not, without more constraints, preclude the existence of other devices, sub-systems, elements, structures, components, additional devices, additional sub-systems, additional elements, additional structures or additional components. Appearances of the phrase "in an embodiment", "in another embodiment" and similar language throughout this specification may, but not necessarily do, all refer to the same embodiment.
[0015] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this disclosure belongs. The system, methods, and examples provided herein are only illustrative and not intended to be limiting.
[0016] In the following specification and the claims, reference will be made to a number of terms, which shall be defined to have the following meanings. The singular forms “a”, “an”, and “the” include plural references unless the context clearly dictates otherwise.
[0017] Embodiments of the present disclosure relate to a system for assisting transaction management. In one embodiment, the transaction management may refer to planning, organizing, managing, and the like of an agreement between the buyer and the seller. Further, assisting the transaction management may refer to helping the buyer and the seller in planning, organizing, managing, decision making, and the like about the exchange of the goods, the services, or the financial assets. Basically, in an embodiment, in order to purchase a product, a user may have to either physically visit the store and search for the product or search online. However, while searching for the product, the user may or may not find the product, but a lot of time gets invested. Thus, the system described hereafter in FIG. 1 is the system for assisting the transaction management.
[0018] FIG. 1 is a block diagram representation of a system (10) for assisting transaction management in accordance with an embodiment of the present disclosure. The system (10) includes a processing subsystem (20) hosted on a server (30). In one embodiment, the server (30) may include a cloud server. In another embodiment, the server (30) may include a local server. The processing subsystem (20) is configured to execute on a network (not shown in FIG. 1) to control bidirectional communications among a plurality of modules. In an embodiment, for the system (10) to be able to assist a user while performing one or more transactions, the system (10) may have to be aware of one or more products or one or more services that are available for sale. Thus, the processing subsystem (20) includes an input module (40). In one embodiment, the user may include a first user and a second user. In one exemplary embodiment, the first user may include a seller, a service provider, a vendor, a driving school, an insurance company, a finance company, an automobile industry, or the like. Similar, in one exemplary embodiment, the second user may include a buyer, a service seeker, a customer, or the like.
[0019] The input module (40) is configured to receive information corresponding to at least one of the one or more products and the one or more services made available for sale by the first user, via a chatbot upon registering the first user. As used herein, the term “chatbot” refers to a technology that simulates human conversation through voice commands, text chats, or both. In one exemplary embodiment, the one or more products may include at least one of new cars, old cars, spare parts, accessories, electronic products, apparel, real estate, and the like. Also, in one exemplary embodiment, the one or more services may include at least one of a repairing service, a décor service, a cleaning service, a maintenance service, a renovation service, and the like. Thus, in one embodiment, the information corresponding to at least one of the one or more products and the one or more services may include a product name, a service name, a preferred product cost, a preferred service cost, a product type, a service type, a market value of the product or the service, one or more features of the product or the service, an initial purchase date of the product, a launch date of the product, and the like. In one exemplary embodiment, the one or more features may include a color, a size, a purchase time, a quality, and the like of the one or more products, and a service time, an extent of the service needed, and the like of the one or more services. In one exemplary embodiment, the information may be stored in a database (as shown in FIG. 2) associated with the processing subsystem (20). In one exemplary embodiment, the database may include a local database or a cloud database.
[0020] However, even before receiving such information, the first user may have to register with the system (10). Thus, in one embodiment, the processing subsystem (20) may also include a registration module (as shown in FIG. 2) operatively coupled with the input module (40). The registration module may be configured to register the first user upon receiving a plurality of first user details via a first user device. In one embodiment, the plurality of first user details may include a first username, one or more first user contact details, location, and the like. Moreover, in an embodiment, the plurality of first user details may be stored in the database. Also, in an embodiment, the first user device may include a mobile phone, a tablet, a laptop, or the like.
[0021] Further, the registration module may also be configured to register the second user with the system (10) upon receiving a plurality of second user details via a second user device. In one embodiment, the plurality of second user details may include a second username, one or more second user contact details, location, and the like. Moreover, in an embodiment, the plurality of second user details may also be stored in the database. Also, in an embodiment, the second user device may include a mobile phone, a tablet, a laptop, or the like. Upon registering the second user, one or more preferences of the user corresponding to a purchase which the user may be interested in making may have to be known by the system (10). Thus, the input module (40) is also configured to receive one or more purchase preferences of the second user via the chatbot upon registration, based on a personalized purchase-based questionnaire conducted via the chatbot with the second user. In one exemplary embodiment, the one or more purchase preferences may include at least one of one or more preferred features of the product to be purchased, a cost range of the product to be purchased, a service type, a preferred service schedule, to know reviews of the product or the service, and the like.
[0022] Basically, in an embodiment, the chatbot may be communicatively coupled with the first user device and the second user device. Also, in an exemplary embodiment, the chatbot may be operatively coupled to one or more social media platforms, so that the first user and the second user may communicate with the system (10), with each other, and one or more additional platforms via the chatbot simply using the first user device and the second user device respectively. In one embodiment, the one or more additional platforms may include at least one of a banking platform, a service providing platform, a financial assistance providing platform, and the like. In one exemplary embodiment, the input module (40) may be configured to generate one or more purchase-related questions upon understating a response corresponding to each of the one or more purchase-related questions using one or more artificial intelligence (AI)-based techniques to conduct the personalized purchase-based questionnaire with the second user in real-time. In one exemplary embodiment, the one or more purchase-related questions may include at least one of asking of customer’s interests, asking for customer’s cost range, asking for a certain type of a service that may be needed, and the like. Then, the second user may respond for the same with a certain type of product or service, a certain acceptable cost range, and the like. Further, the one or more AI-based techniques may be used for understanding such a response and generate a next set of the one or more purchase-related questions. Thus, in one exemplary embodiment, the one or more AI-based techniques may include at least one of a natural language processing (NLP) technique, an image processing technique, an optical character recognition (OCR) technique, and the like.
[0023] As used herein, the term “natural language processing” is defined as a branch of artificial intelligence that helps computers understand, interpret and manipulate human language. Thus, the NLP technique may be used to not only analyze and understand the response of the user via the chatbot but also understand intent of a conversation. Basically, the database associated with the system (10) may be pre-fed with a plurality of words with meaning, for the system (10) to understand the response of the user. Also, with time the chatbot may get trained with analyzing and understanding one or more new words, one or more new questions, one or more new responses, and the like, using a machine learning (ML) technique, and hence may get updated, thereby improving an experience of the user with time. As used herein, the term “machine learning” is defined as an application of AI that provides systems the ability to automatically learn and improve from experience without being explicitly programmed.
[0024] Furthermore, as used herein, the term “image processing” is defined as a method of manipulating an image to either enhance the quality or extract relevant information from it. In AI, image processing may refer to combining one or more image processing services with ML and computer vision to process large volumes of one or more images easily and quickly. Basically, in an embodiment, the chatbot may also receive the one or more images. Thus, in an embodiment, in order to analyze and understand the corresponding one or more images, the image processing technique may be used. In such embodiment, the chatbot may be pre-fed with a plurality of pre-captured images of a plurality of products and a plurality of services and may be trained with analyzing and understanding one or more new images using the ML technique, and hence may get updated, thereby improving an experience of the user with time.
[0025] Moreover, as used herein, the term “optical character recognition” is defined as a form of technology that identifies the characters like numbers and letters included in an image. The OCR also recognizes patterns and classifies information for AI to use. Basically, in an embodiment, whenever the user is responding with an image having text and numbers, for the system (10) to analyze and understand the same, the OCR technique may be used. Mainly, one or more image processing techniques may be used to understand the text and the numbers present in an image. Initially, the image is read with a scanner and converted to binary data. Then image acquisition may be performed followed by segmentation, feature extraction, classification, and the like, thereby detecting and identifying letters, characters, numbers, symbols, and the like.
[0026] In one exemplary embodiment, the processing subsystem (20) may include a valuation module (as shown in FIG. 2) operatively coupled to the input module (40). The valuation module may be configured to assign a purchasing amount to at least one of the one or more products and the one or more services made available for sale by the first user upon analyzing the information received by the input module (40) using the ML technique and a data science technique. In one embodiment, the purchasing amount may refer to the cost of at least one of the one or more products and the one or more services made available for sale by the first user. As used herein, the term “data science” refers to a field of study that combines domain expertise, programming skills, and knowledge of mathematics and statistics to extract meaningful insights from data. Basically, data science uses techniques such as ML and AI to extract meaningful information and to predict future patterns and behaviors.
[0027] For example, at least one of the one or more products and the one or more services may be associated with a unique identifier. The unique identifier may be linked with the information corresponding to at least one of the one or more products and the one or more services. Thus, in an embodiment, the data fed to the system (10) which is referred while using the data science technique, may include the unique identifier and the corresponding information. Basically, in an embodiment, the information is received by the system (10) via the input module (40) upon scanning the unique identifier. In one exemplary embodiment, the unique identifier may include a registration certificate of the one or more products and the one or more services. Upon scanning the unique identifier, the information may be extracted using the OCR technique, and hence received by the input module (40). In an embodiment, the data may also include any damage that may be identified in the one or more products upon analyzing the one or more images of the one or more products using the image processing technique. Thus, in an embodiment, assigning the purchasing amount upon analyzing the corresponding data by the valuation module may refer to assigning an average of one or more cost predictions made based on at least one of the market value, the product type, the service type, the one or more features, any damage, and the like of at least one of the one or more products and the one or more services.
[0028] Upon knowing the one or more purchase preferences of the second user, an availability of at least one of the one or more products and the one or more services may have to be verified to provide a real-time experience to the second user. Thus, the processing subsystem (20) also includes an input processing module (50) operatively coupled to the input module (40). The input processing module (50) is configured to verify the availability of at least one of the one or more products and the one or more services by conducting a personalized sale-based questionnaire with the first user in real-time based on a processing of the one or more purchase preferences. In one embodiment, the input processing module (50) may be configured to generate one or more sale-related questions upon understating a response corresponding to each of the one or more sale-related questions using the one or more AI-based techniques to conduct the personalized sale-based questionnaire with the first user in real-time. In one exemplary embodiment, the one or more sale-related questions may include at least one of asking if a certain product or service is available, asking a cost of the product or the service, and the like. Then, the first user may respond for the same with a certain type of product or service is available or not, a maximum cost range, one or more offers, and the like. Further, the one or more AI-based techniques may be used for understanding such a response and generate a next set of the one or more sale-related questions. Also, in one embodiment, the input processing module (50) may be configured to process the one or more purchase preferences using the one or more AI-based techniques to understand the corresponding one or more purchase preferences. Upon verifying the availability, the second user may have to be updated about the same. Thus, the input processing module (50) is also configured to share the information corresponding to at least one of the one or more products and the one or more services with the second user via the chatbot, upon verifying the availability.
[0029] Upon receiving the information, the second user now may be in a position to decide whether to purchase the corresponding one or more products or use the corresponding one or more services or not. However, the second user may not respond immediately, and hence the system (10) may have to follow up so that the first user can be updated regarding whether the second user is interested in purchasing the corresponding one or more products or using the corresponding one or more services or not. Thus, the processing subsystem (20) also includes a follow-up module (60) operatively coupled to the input processing module (50). The follow-up module (60) is configured to conduct a follow-up questionnaire with the second user at a predefined time interval until a positive response on purchasing at least one of the one or more products and the one or more services is received from the second user based on the information shared by the input processing module (50).
[0030] In one embodiment, the follow-up module (60) may be configured to generate one or more follow-up questions upon understating a response corresponding to each of the one or more follow-up questions using the one or more AI-based techniques to conduct the follow-up questionnaire with the first user in real-time. In one exemplary embodiment, the one or more follow-up questions may include asking if the first user is still interested in purchasing the product or using the service, informing about the one or more offers which are associated with the product or the service, informing change in a price of the product or the service, and the like. Then, the first user may respond for the same with interested to purchase the product, not interested to purchase the product, interested to use the service, not interested to use the service, and the like. Further, the one or more AI-based techniques may be used for understanding such a response and generate a next set of the one or more follow-up questions. In one exemplary embodiment, the predefined time interval may include daily one time, weekly one time, monthly twice, or the like. Also, in an embodiment, the positive response may refer to the second user may be interested in purchasing the corresponding one or more products or interested in using the corresponding one or more services. However, in an embodiment, if a negative response may be received from the second user, then as the second user may not be interested in purchasing or using at least one of the one or more products and the one or more services, and the first user may be updated about the same.
[0031] Furthermore, the processing subsystem (20) also includes a categorization module (70) operatively coupled to the follow-up module (60). The categorization module (70) is configured to create one or more labels based on at least one of the personalized purchase-based questionnaire and the follow-up questionnaire conducted with the second user. The categorization module (70) is also configured to categorize the second user under a predefined category upon assigning with the one or more labels. Suppose the second user is actively responding in at least one of the personalized purchase-based questionnaire and the follow-up questionnaire conducted with the second user, then the second user may be belonging to the predefined category including an active lead, and hence may be categorized under the same. Similarly, suppose the second user is poorly responding in at least one of the personalized purchase-based questionnaire and the follow-up questionnaire conducted with the second user, then the second user may be belonging to the predefined category including an in-active lead. Moreover, suppose the second user may be responding but moderately in at least one of the personalized purchase-based questionnaire and the follow-up questionnaire conducted with the second user, then the second user be belonging to the predefined category including a moderately active lead. Therefore, in one embodiment, one or more labels generated may include active, inactive, moderately active, or the like. Upon categorization of the second user, the same may be updated to the first user. Later, suppose the positive response may have been received from the second user, then based on the categorization of the second user, a decision may have to be taken about whether to connect the second user with the first user or not. Thus, the processing subsystem (20) also includes a connection module (80) operatively coupled to the categorization module (70). The connection module (80) is configured to connect the second user with the first user via the chatbot based on the categorization of the second user, upon receiving the positive response from the second user. The positive response corresponds to the purchasing of at least one of the one or more products and the one or more services. In one embodiment, the second user may be connected with the first user, when the second user may be categorized under the active lead.
[0032] Upon establishing the connection, as the second user may be interested in purchasing at least one of the one or more products, and the one or more services, and payment may have to be initiated to complete purchase and sale. Thus, the processing subsystem (20) also includes a transaction module (90) operatively coupled to the connection module (80). The transaction module (90) is configured to conduct a transaction-based questionnaire corresponding to the purchase, with the second user via the chatbot upon connecting the second user with the first user. In one embodiment, the transaction module (90) may be configured to generate one or more transaction-related questions upon understating a response corresponding to each of the one or more transaction-related questions using the one or more AI-based techniques to conduct the transaction-based questionnaire with the second user in real-time. In one exemplary embodiment, the one or more transaction-based questions may include asking to make the payment, asking to confirm the payment, asking if a loan is needed, asking to select a loan installment plan, or the like. Then, the second user may respond for the same with agreeing to make the payment, confirming to make the payment, responding with yes or no when regarding the need for the loan was asked, selecting the loan installment plan, or the like. The transaction module (90) is also configured to initiate a monetary transaction process between the first user and the second user via a predefined transaction mode based on the transaction-based questionnaire conducted with the second user to purchase at least one of the one or more products and the one or more services, thereby assisting the transaction management. In one embodiment, the predefined transaction mode may include make complete payment via cash, card, net banking, or the like, make the payment upon opting for the loan by selecting the loan installment plan referred to as a loan-based transaction, or the like.
[0033] In addition, in one embodiment, the processing subsystem (20) may also include a loan management module (as shown in FIG. 2) operatively coupled to the valuation module. The loan management module may be configured to receive a plurality of transaction-related documents corresponding to the second user based on the purchasing amount assigned by the valuation module, when the predefined transaction mode may include the loan-based transaction. In one exemplary embodiment, the plurality of transaction-related documents may include at least one of one or more checkbooks, one or more transaction-related documents, one or more identity proving documents, and the like. Suppose the purchasing amount may be a huge amount, the plurality of transaction-related documents may also include one or more property-related documents, one or more asset-related documents, or the like. The loan management module may also be configured to determine eligibility of the second user to receive the loan of the corresponding purchasing amount for completing the transaction process upon analyzing the plurality of transaction-related documents based on one or more bank-related parameters. In one exemplary embodiment, the one or more bank-related parameters may include at least one of a criteria for the loan set by a predefined bank, a maximum allowed loan amount value, a minimum allowed loan amount value, a bank type, a locality, a bank account type, and the like. In an embodiment, the loan management module may analyze the plurality of transaction-related documents using the one or more AI-based techniques.
[0034] In an embodiment, analyzing the one or more transaction-related documents may include extracting data from the corresponding plurality of transaction-related documents using the one or more AI-based techniques such as the OCR technique and the image processing technique. Upon extracting, the data may be compared with the one or more bank-related parameters for determining the eligibility of the second user to receive the loan of the corresponding purchasing amount, thereby completing the transaction process. Further, in an embodiment, upon determining the eligibility of the second user for receiving the loan, the second user may be connected with the banking platform so that, further process related to the loan may be initiated to complete the purchase and the sale of at least one of one or more products and the one or more services.
[0035] FIG. 2 is a block diagram representation of an exemplary embodiment of the system (10) for assisting transaction management of FIG. 1 in accordance with an embodiment of the present disclosure. Suppose one or more automobile industries (100) are willing to reach multiple customers (110) with ease to make more profit, then the one or more automobile industries (100) may use the system (10) proposed in the present disclosure to achieve the same. The system (10) basically includes the processing subsystem (20). Further, the one or more automobile industries (100) register with the system (10) via the registration module (120) upon receiving a plurality of industry details of each of the one or more automobile industries (100) via the chatbot (130) using a respective industry laptop (140). The plurality of industry details is stored in the database (150) of the system (10). Further, for the multiple customers (110) to be able to easily contact the one or more automobile industries (100), the multiple customers (110) also register with the system (10) using a respective customer mobile phone (160). Upon registration, the one or more automobile industries (100) may have to make the information of one or more automobiles available on the system (10). Thus, the one or more automobile industries (100) may provide the information via the input module (40) using the chatbot (130) upon registration. Similarly, at a customer end, the multiple customers (110) also provide the one or more purchase preferences via the input module (40) using the chatbot (130), based on the personalized purchase-based questionnaire conducted with the corresponding multiple customers (110).
[0036] Suppose a customer ‘A’ (170) wants to purchase a car ‘C’ (180) of a brand ‘L’ within a price range of thirty lakhs to fifty lakhs. Also, the color should be red with a large space in a back seat area. Then, the customer ‘A’ (170) provides this as the one or more purchase preferences of the customer ‘A’ (170). Later, the system (10) verifies the availability of the same type of car ‘C’ (180) with the one or more automobile industries (100) in real-time via the input processing module (50). Basically, the system (10) conducts the personalized sale-based questionnaire with the one or more automobile industries (100) based on the processing of the one or more purchase preferences. Suppose an automobile industry ‘B’ (190) has posted about the sale of such a car ‘C’ (180) on the system (10). Therefore, the system (10) shares the information of the car ‘C’ (180) with the customer ‘A’ (170) via the input processing module (50) using the chatbot (130). Now, the customer goes through the information received and makes a decision of whether to go for purchasing the car ‘C’ (180) or not. Suppose the customer ‘A’ (170) liked the car ‘C’ (180) based on the information received, and hence decides to purchase the same, and hence the follow up via the follow-up module (60) may not be needed as the customer ‘A’ (170) responds with the positive response. Then, based on the personalized purchase-based questionnaire conducted with the customer ‘A’ (170), the one or more labels including a term ‘active’ is generated and the customer ‘A’ (170) is categorized under the ‘active lead’ category via the categorization module (70).
[0037] Upon receiving the positive response, contact details of the automobile industry ‘B’ (190) are shared with the customer ‘A’ (170), and hence a connection is established between the customer ‘A’ (170) and the automobile industry ‘B’ (190) by the connection module (80) based on the categorization. Later, the customer ‘A’ (170) is inquired about a payment which the customer ‘A’ (170) can pay in comparison to the price of the car ‘C’ (180) set initially by conducting the transaction-based questionnaire with the customer ‘A’ (170) via the transaction module (90), wherein the price is calculated via the valuation module (200) based on the analysis of the information of the car ‘C’ (180). Here, price is the purchasing amount of the car ‘C’ (180). Later, the transaction process is initiated based on the transaction-based questionnaire with the customer ‘A’ (170). Further, as the price of the car ‘C’ (180) is a huge amount, the customer ‘A’ (170) opts for taking the loan. Therefore, the plurality of transaction-related documents of the customer ‘A’ (170) are received via the loan management module (210), and the transaction process is completed upon determining the eligibility of the customer ‘A’ (170) to receive the loan of the purchasing amount. The eligibility is determined via the loan management module (210) upon analyzing the plurality of transaction-related documents based on one or more bank-related parameters. Basically, during this process, the customer ‘A’ (170) is connected with a banking platform ‘D’ via the chatbot (130) to initiate and complete further processes. Later, monthly loan installment is calculated via the valuation module (200), and such details are shared with the customer ‘A’ (170) and the automobile industry ‘B’ (190) to complete the purchase and the sale of the car ‘C’ (180).
[0038] FIG. 3 is a block diagram of a transaction management computer or a transaction management server (240) in accordance with an embodiment of the present disclosure. The transaction management server (240) includes processor(s) (250), and a memory (260) operatively coupled to a bus (270). The processor(s) (250), as used herein, means any type of computational circuit, such as, but not limited to, a microprocessor, a microcontroller, a complex instruction set computing microprocessor, a reduced instruction set computing microprocessor, a very long instruction word microprocessor, an explicitly parallel instruction computing microprocessor, a digital signal processor, or any other type of processing circuit, or a combination thereof.
[0039] Computer memory elements may include any suitable memory device(s) for storing data and executable program, such as read only memory, random access memory, erasable programmable read only memory, electrically erasable programmable read only memory, hard drive, removable media drive for handling memory cards and the like. Embodiments of the present subject matter may be implemented in conjunction with program modules, including functions, procedures, data structures, and application programs, for performing tasks, or defining abstract data types or low-level hardware contexts. Executable program stored on any of the above-mentioned storage media may be executable by the processor(s) (250).
[0040] The memory (260) includes a plurality of subsystems stored in the form of executable program which instructs the processor (250) to perform method steps illustrated in FIG. 4 (a) and Fig. 4 (b). The memory (260) includes a processing subsystem (20) of FIG 1. The processing subsystem (20) further has following modules: an input module (40), an input processing module (50), a follow-up module (60), a categorization module (70), a connection module (80), and a transaction module (90).
[0041] The input module (40) is configured to receive information corresponding to at least one of one or more products and one or more services made available for sale by a first user, via a chatbot (130) upon registering the first user. The input module (40) is also configured to receive one or more purchase preferences of a second user via the chatbot (130) upon registration, based on a personalized purchase-based questionnaire conducted via the chatbot (130) with the second user. The input processing module (50) is configured to verify availability of at least one of the one or more products and the one or more services by conducting a personalized sale-based questionnaire with the first user in real-time based on a processing of the one or more purchase preferences. The input processing module (50) is also configured to share the information corresponding to at least one of the one or more products and the one or more services with the second user via the chatbot (130), upon verifying the availability.
[0042] The follow-up module (60) is configured to conduct a follow-up questionnaire with the second user at a predefined time interval until a positive response on purchasing of the at least one of the one or more products and the one or more services is received from the second user based on the information shared by the input processing module (50). The categorization module (70) is configured to create one or more labels based on at least one of the personalized purchase-based questionnaire and the follow-up questionnaire conducted with the second user. The categorization module (70) is also configured to categorize the second user under a predefined category upon assigning with the one or more labels.
[0043] The connection module (80) is configured to connect the second user with the first user via the chatbot (130) based on the categorization of the second user, upon receiving the positive response from the second user, wherein the positive response corresponds to the purchasing of at least one of the one or more products and the one or more services. The transaction module (90) is configured to conduct a transaction-based questionnaire corresponding to the purchase, with the second user via the chatbot (130) upon connecting the second user with the first user. The transaction module (90) is also configured to initiate a monetary transaction process between the first user and the second user via a predefined transaction mode based on the transaction-based questionnaire conducted with the second user to purchase at least one of the one or more products and the one or more services, thereby assisting the transaction management.
[0044] FIG. 4 (a) and FIG. 4(b) are flow charts representing steps involved in a method (280) for assisting transaction management in accordance with an embodiment of the present disclosure. The method (280) includes receiving information corresponding to at least one of one or more products and one or more services made available for sale by a first user, via a chatbot upon registering the first user in step 290. In one embodiment, receiving the information may include receiving the information by an input module (40).
[0045] The method (280) also includes receiving one or more purchase preferences of a second user via the chatbot upon registration, based on a personalized purchase-based questionnaire conducted via the chatbot with the second user in step 300. In one embodiment, receiving the one or more purchase preferences may include receiving the one or more purchase preferences by the input module (40). In such embodiment, conducting the personalized purchase-based questionnaire may include generating one or more purchase-related questions upon understating a response corresponding to each of the one or more purchase-related questions using one or more artificial intelligence-based techniques.
[0046] Furthermore, the method (280) includes verifying availability of at least one of the one or more products and the one or more services by conducting a personalized sale-based questionnaire with the first user in real-time based on a processing of the one or more purchase preferences in step 310. In one embodiment, verifying the availability may include verifying the availability by an input processing module (50).
[0047] Furthermore, the method (280) also includes sharing the information corresponding to at least one of the one or more products and the one or more services with the second user via the chatbot, upon verifying the availability in step 320. In one embodiment, sharing the information may include sharing the information by the input processing module (50).
[0048] Furthermore, the method (280) also includes conducting a follow-up questionnaire with the second user at a predefined time interval, until a positive response on purchasing at least one of the one or more products and the one or more services is received from the second user based on the information shared by the input processing module in step 330. In one embodiment, conducting the follow-up questionnaire may include conducting the follow-up questionnaire by a follow-up module (60). In such embodiment, conducting the follow-up questionnaire may include generating one or more follow-up questions upon understating a response corresponding to each of the one or more follow-up questions using the one or more artificial intelligence-based techniques.
[0049] Furthermore, the method (280) also includes creating one or more labels based on at least one of the personalized purchase-based questionnaire and the follow-up questionnaire conducted with the second user in step 340. In one embodiment, includes creating the one or more labels may include includes creating the one or more labels by a categorization module (70).
[0050] Furthermore, the method (280) also includes categorizing the second user under a predefined category upon assigning with the one or more labels in step 350. In one embodiment, categorizing the second user may include categorizing the second user by the categorization module (70).
[0051] Furthermore, the method (280) also includes connecting the second user with the first user via the chatbot based on the categorization of the second user, upon receiving the positive response from the second user, wherein the positive response corresponds to the purchasing of at least one of the one or more products and the one or more services in step 360. In one embodiment, connecting the second user with the first user may include connecting the second user with the first user by a connection module (80).
[0052] Furthermore, the method (280) also includes conducting a transaction-based questionnaire corresponding to the purchase, with the second user via the chatbot upon connecting the second user with the first user in step 370. In one embodiment, conducting the transaction-based questionnaire may include conducting the transaction-based questionnaire by a transaction module (90). In such embodiment, conducting the transaction-based questionnaire may include generating one or more transaction-related questions upon understating a response corresponding to each of the one or more transaction-related questions using the one or more artificial intelligence-based techniques.
[0053] Furthermore, the method (280) also includes initiating a monetary transaction process between the first user and the second user via a predefined transaction mode based on the transaction-based questionnaire conducted with the second user to purchase at least one of the one or more products and the one or more services, thereby assisting the transaction management in step 380. In one embodiment, initiating the monetary transaction process may include initiating the monetary transaction process by the transaction module (90).
[0054] In one exemplary embodiment, the method (280) may also include assigning a purchasing amount to at least one of the one or more products and the one or more services made available for sale by the first user upon analyzing the information received by the input module using a machine learning technique and a data science technique. In such embodiment, assigning the purchasing amount may include assigning the purchasing amount by a valuation module (200). Further, in one exemplary embodiment, the method (280) may also include receiving a plurality of transaction-related documents corresponding to the second user based on the purchasing amount assigned by the valuation module when the predefined transaction mode comprises a loan-based transaction. In such embodiment, receiving the plurality of transaction-related documents may include receiving the plurality of transaction-related documents by a loan management module (210). Furthermore, in one exemplary embodiment, the method (280) may also include determining eligibility of the second user to receive a loan of the corresponding purchasing amount for completing the transaction process upon analyzing the plurality of transaction-related documents based on one or more bank-related parameters. In such embodiment, determining the eligibility of the second user may include determining the eligibility of the second user by the loan management module (210).
[0055] Further, from a technical effect point of view, the implementation time required to perform the method steps included in the present disclosure by the one or more processors of the system is very minimal, thereby the system maintains very minimal operational speed.
[0056] Various embodiments of the present disclosure enable sellers and buyers to perform a transaction without wasting time, money, or energy because neither the sellers nor the buyers have to wait for each other, as the system performs searching operation. Also, the information received by the buyers about the one or more products or the one or more services is up to date and genuine as such information is first verified with the sellers before sharing with the buyers, thereby making the system more efficient.
[0057] While specific language has been used to describe the disclosure, any limitations arising on account of the same are not intended. As would be apparent to a person skilled in the art, various working modifications may be made to the method in order to implement the inventive concept as taught herein. The figures and the foregoing description give examples of embodiments. Those skilled in the art will appreciate that one or more of the described elements may well be combined into a single functional element. Alternatively, certain elements may be split into multiple functional elements. Elements from one embodiment may be added to another embodiment. For example, order of processes described herein may be changed and are not limited to the manner described herein. Moreover, the actions of any flow diagram need not be implemented in the order shown; nor do all of the acts need to be necessarily performed. Also, those acts that are not dependent on other acts may be performed in parallel with the other acts. The scope of embodiments is by no means limited by these specific examples.