Embodiments of a present invention relate to the management of loans, and
more particularly, to a system and method for managing and assessing the loans within
a personalized network.
BACKGROUND
[0002] A loan is when a person receives money from a friend, bank, or financial
institution in exchange for future repayment of the principal and interest. In case
money is lent from a bank or a financial institution, then official documentation is
made, and based on one or more conditions the loan is provided by the bank. The one
or more conditions include checking for collaterals such as physical property and
ornaments of the borrower or checking income, cash flow, strength or stability of
business or employment of the borrower to make sure that the borrower can repay.
When it comes to lending and borrowing money amongst friends, family, and
acquaintances, the transactions are informal, made in cash or otherwise, unstructured,
sometimes unrecorded, difficult to track and establish in the absence of a clear way.
Also, when the lender is charging any interest on the loan extended, the same is seldom
computed in an organized way and as a result, repayments may also become irregular.
[0003] Hence, there is a gap and hence the need for an improved system and
method for managing and assessing loans within a personalized network which
addresses the aforementioned issues.
BRIEF DESCRIPTION
[0004] In accordance with one embodiment of the disclosure, a system for
managing and assessing one or more loans related to a lender and a borrower within a
personalized network is provided. The system includes one or more processors. The
system also includes a borrower module operable by the one or more processors. The
borrower module is configured to scan the personalized network of the borrower in a
real-time and dynamic fashion, so as to check for one or more lenders actively
available for lending the one or more loans in real-time upon registering the borrower
on a centralized platform via a borrower device. The borrower module is also
configured to generate a loan request upon selection of the lender by the borrower
3
within the personalized network of the borrower via a borrower interface based on one
or more lender related parameters. The system also includes a lender module operable
by the one or more processors. The lender module is configured to enable the lender
to broadcast a lending capability notification within the personalized network of the
lender via a lender interface in real-time upon registering the lender on the centralized
platform via a lender device. The lending capability notification is associated with
lending capability information. The lender module is also configured to generate a
lender response upon receiving the loan request generated by comparing the loan
request generated with the lending capability information and based on one or more
borrower related parameters. The lender response includes one of an approval for the
loan request generated, a rejection for the loan request generated, and a counteroffer
for the borrower to consider. Further, the system also includes a transaction module
operable by the one or more processors. The transaction module is configured to
generate a first notification for the lender to perform a transaction of a pre-defined
loan amount from a lender’s account to a borrower’s account when one of the lender
response is the approval for the loan request generated, the counteroffer is accepted by
the borrower, or a combination thereof. The pre-defined loan amount is linked with a
pre-defined interest rate. The transaction module is also configured to generate a
second notification for the borrower to perform a transaction of a due repayment
amount from the borrower’s account to the lender’s account periodically based on a
repayment schedule selected by the borrower from one or more repayment schedules
displayed on the borrower interface upon registering the borrower on the centralized
platform. Further, the system also includes a counteroffer generation module operable
by the one or more processors. The counteroffer generation module is configured to
generate the counteroffer for the borrower based on a plurality of factors using one or
more artificial intelligence and one or more machine learning techniques upon
receiving the loan request generated, thereby managing and assessing the one or more
loans related to the lender and the borrower within the personalized network, wherein
the counteroffer includes one of a varied interest rate, a varied loan amount, a varied
loan duration, or a combination thereof.
[0005] In accordance with another embodiment, a method for managing and
assessing one or more loans related to a lender and a borrower within a personalized
network is provided. The method includes scanning the personalized network of the
4
borrower in a real-time and dynamic fashion, so as check for one or more lenders
actively available for lending the one or more loans in real-time upon registering the
borrower on a centralized platform via a borrower device. The method also includes
generating a loan request upon selection of the lender by the borrower within the
personalized network of the borrower via a borrower interface based on one or more
lender related parameters. Further, the method also includes enabling the lender to
broadcast a lending capability notification within the personalized network of the
lender via a lender interface in real-time upon registering the lender on the centralized
platform via lender device, wherein the lending capability notification is associated
with lending capability information. Further, the method also includes generating a
lender response upon receiving the loan request generated by comparing the loan
request generated with the lending capability information, and based on one or more
borrower related parameters, wherein the lender response comprises one of an
approval for the loan request generated, a rejection for the loan request generated, and
a counteroffer for the borrower to consider. Further, the method also includes
generating a first notification for the lender to perform a transaction of a pre-defined
loan amount from a lender’s account to a borrower’s account when one of the lender
response is the approval for the loan request generated, the counteroffer is accepted by
the borrower, or a combination thereof, wherein the pre-defined loan amount is linked
with a pre-defined interest rate. Further, the method also includes generating a second
notification for the borrower to perform a transaction of a due repayment amount from
the borrower’s account to the lender’s account periodically based on a repayment
schedule selected by the borrower from one or more repayment schedules displayed
on the borrower interface upon registering the borrower on the centralized platform.
Further, the method also includes generating the counteroffer for the borrower based
on a plurality of factors using one or more artificial intelligence and one or more
machine learning techniques upon receiving the loan request generated, thereby
managing and assessing the one or more loans related to the lender and the borrower
within the personalized network, wherein the counteroffer includes one of a varied
interest rate, a varied loan amount, a varied loan duration, or a combination thereof.
[0006] 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
5
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:
[0007] FIG. 1 is a block diagram representation of a system for managing and
assessing one or more loans related to a lender and a borrower within a personalized
network in accordance with an embodiment of the present disclosure;
[0008] FIG. 2 is a block diagram representation of an exemplary embodiment of
the system for managing and assessing the one or more loans related to the lender and
the borrower within the personalized network of FIG. 1 in accordance with an
embodiment of the present disclosure;
[0009] FIG. 3 is a block diagram of a loan management computer or a loan
management server in accordance with an embodiment of the present disclosure; and
[0010] FIG. 4 is a flow chart representing steps involved in a method for managing
and assessing one or more loans related to a lender and a borrower within a
personalized network in accordance with an embodiment of the present disclosure.
[0011] 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.
6
DETAILED DESCRIPTION
[0012] 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.
[0013] 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.
[0014] 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.
[0015] 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.
[0016] Embodiments of the present disclosure relate to a system for managing and
assessing one or more loans related to a lender and a borrower within a personalized
network. As used herein, the term “personalized network” may be defined as a trusted
network of one or more individuals including one of friends, family, acquaintances,
7
and the like, or a combination thereof. Thus, the one or more individuals may use the
system and be a borrower, whenever the one or more individuals are in need of money
and borrow a preferred amount from within the personalized network. Also, the one
or more individuals may use the system and be a lender, whenever the one or more
individuals are willing to lend money within the personalized network. The
personalized network being the trusted network, there is no need for any official
underwriting between the lender and the borrower, as the lender and the borrower are
already well connected with each other, and shall be connected to each other on a
centralized platform to perform a transaction of the money at mutually agreeable terms
and conditions with adequate record keeping. The system as described hereafter in
FIG. 1 is the system for managing the one or more loans related to the lender and the
borrower within the personalized network.
[0017] FIG. 1 is a block diagram representation of a system (10) for managing and
assessing one or more loans related to a lender and a borrower within a personalized
network in accordance with an embodiment of the present disclosure. The system (10)
includes one or more processors (20). In one embodiment, whenever a user needs
money, the user explores multiple options such as banks, Non-Banking Financial
Company (NBFC), local lenders, social networks, and the like. In another
embodiment, the user might borrow the money from within the personalized network.
In an exemplary embodiment, the personalized network may include a contact list, an
E-mail list, social connects, and the like of the user, on whom the user can be
dependent as the trust factor between the user the personalized network may be good.
Thus, the user may give preference to the personalized network. Also, the user may be
willing to lend money to other people and hence may prefer the personalized network
of the user because of the trust factor being good. Therefore, the user may use the
system (10) for managing and assessing the one or more loans of the user within the
personalized network.
[0018] Further, the user may have to register on a centralized platform for the user
to be able to use the system (10). Thus, in one embodiment, the system (10) may
include a registration module (as shown in FIG. 2) operable by the one or more
processors (20). The registration module may be configured to register the user on the
centralized platform as one of the lender, the borrower, or a combination thereof upon
8
receiving one of a plurality of lender details, a plurality of borrower details, or a
combination thereof respectively.
[0019] In one embodiment, the plurality of lender details may include lender’s
name, lender’s gender, lender’s age, lender’s communication address, lender’s contact
number, a lender’s E-mail Identifier (ID), lender’s account details, and the like In one
embodiment, the plurality of borrower details may include borrower’s name,
borrower’s gender, borrower’s age, borrower’s communication address, borrower’s
contact number, a borrower’s E-mail ID, borrower’s account details, and the like. In
one embodiment, the plurality of lender details and the plurality of borrower details
may be stored in a database (as shown in FIG. 2) of the system (10). In one
embodiment, the database may include a local database or a cloud database.
[0020] Further, in one embodiment, the user becomes the borrower upon
registering on the centralized platform as the borrower. In such embodiment, the
borrower may have to generate a loan request to be able to receive a loan from the
lender within the personalized network. Thus, the system (10) also includes a borrower
module (30) operable by the one or more processors (20). The borrower module (30)
is configured to scan the personalized network of the borrower in a real-time and
dynamic fashion, so as check for one or more lenders actively available for lending
the one or more loans in real-time upon registering the borrower on the centralized
platform via a borrower device (40). In one embodiment, the borrower device (40)
may include a mobile phone, a tablet, a laptop, and the like.
[0021] Further, the borrower module (30) is also configured to generate the loan
request upon selection of the lender by the borrower within the personalized network
of the borrower via a borrower interface based on one or more lender related
parameters. In one embodiment, the loan request may include one of a pre-defined
loan amount, a loan duration, and the like, or a combination thereof. The pre-defined
loan amount may be an amount which the borrower may need as the loan from the
lender selected. Similarly, the loan duration may be a time after which the borrower
may be able to repay the pre-defined loan amount borrowed. In one embodiment, the
borrower may have to select a repayment schedule from one or more repayment
schedules displayed on the borrower interface as per convenience of the borrower
upon registering on the centralized platform, and while generating the loan request for
9
the lender. Further, in one exemplary embodiment, the borrower module (30) may
enable the borrower to sort, search, and filter the one or more lenders in the
personalized network of the borrower via the borrower interface. In one embodiment,
the borrower module (30) may enable the borrower to borrow the one or more loans
from one or more financial institutions via the borrower interface, when nobody in the
personalized network of the borrower is actively available for lending the one or more
loans.
[0022] Further, in one embodiment, the one or more lender related parameters may
include one of a lender rating, lending capability information, the plurality of lender
details, and the like, or a combination thereof. The lender rating may be a rating
provided by one or more borrowers who borrowed the money from the lender. Thus,
in one embodiment, the system (10) may also include a rating module (as shown in
FIG. 2) operable by the one or more processors (20). The rating module may be
operatively coupled to the borrower module (30). The rating module may be
configured to enable the borrower to provide the lender rating to the lender via the
borrower interface based on a behavior of the lender with the corresponding borrower.
In one embodiment, the behavior of the lender may include one of whether the lender
has lent the pre-defined loan amount requested by the borrower in time, whether a predefined interest rate offered by the lender is appreciated by the borrower, and the like,
or a combination thereof.
[0023] Further, the rating module may be also configured to track the behavior of
the lender and validate the lender rating received from the borrower about the lender
upon comparing the lender rating with the behavior tracked by the rating module. In
one embodiment, the lender rating may include one of a good lender rating and an
average lender rating. Further, in one embodiment, the system (10) may also include
a recommendation module (as shown in FIG. 2) operable by the one or more
processors (20). The recommendation module may be operatively coupled to the rating
module. The recommendation module may be configured to generate a
recommendation for the borrower based on the behavior of the lender tracked by the
rating module and the one or more lender related parameters. The recommendation
may include the lender to be selected by the borrower for the borrower to have a better
experience, about a preferable frequency of borrowing, and the like.
10
[0024] Furthermore, in one embodiment, the user becomes the lender upon
registering on the centralized platform as the lender. In such embodiment, the lender
may have to declare about a lender’s lending capability within the personalized
network. Thus, the system (10) also includes a lender module (50) operable by the one
or more processors (20). The lender module (50) is operatively coupled to the
borrower module (30). The lender module (50) is configured to enable the lender to
broadcast a lending capability notification within the personalized network of the
lender via a lender interface in real-time upon registering the lender on the centralized
platform via a lender device (60). In one embodiment, the lender device (60) may
include a mobile phone, a tablet, a laptop, or the like. The lending capability
notification is associated with the lending capability information. In one exemplary
embodiment, the lending capability information may include one of a maximum
amount limit for lending the one or more loans, the pre-defined interest rate, one or
more repayment schedules, a lender’s account balance, and the like, or a combination
thereof.
[0025] Moreover, the lender module (50) is also configured to generate a lender
response upon receiving the loan request generated by comparing the loan request
generated with the lending capability information, and based on one or more borrower
related parameters. In one embodiment, the one or more borrower related parameters
may include one of a borrower rating, the plurality of borrower details, and the like,
or a combination thereof. The borrower rating may be a rating provided by the one or
more lenders who lent the money to the borrower. Thus, in one embodiment, the rating
module of the system (10) may also be operatively coupled to the lender module (50).
Further, the rating module may also be configured to enable the lender to provide the
borrower rating to the borrower via the lender interface based on a behavior of the
borrower with the corresponding lender. In one embodiment, the behavior of the
borrower may include one of whether the pre-defined loan amount borrowed by the
borrower was repaid in time, whether the repayment was made with the pre-defined
interest rate offered by the lender to the borrower, and the like, or a combination
thereof.
[0026] Further, the rating module may be also configured to track the behavior of
the borrower and validate the borrower rating received from the lender about the
11
borrower upon comparing the borrower rating with the behavior tracked by the rating
module. In one embodiment, the borrower rating may include one of a good borrower
rating and an average borrower rating. Further, in one embodiment, the
recommendation module may also be configured to generate a recommendation for
the lender based on the behavior of the borrower tracked by the rating module and the
one or more borrower related parameters. The recommendation may include about the
borrower whose loan request to be accepted by the lender for the lender to have a
better experience, about a preferable frequency of lending, a preferable value to be set
for the pre-defined interest rate, and the like. In one exemplary embodiment, the lender
module (50) may also enable the lender to waive the pre-defined interest rate which
may be associated with the pre-defined loan amount.
[0027] Further, the lender response includes one of an approval for the loan request
generated, a rejection for the loan request generated, and a counteroffer for the
borrower to consider. In one embodiment, the lender response may include the
approval when the borrower has the good borrower rating and the loan request
generated matches with the lending capability information. In another embodiment,
the lender response may include the rejection when the borrower has one of the
average borrower rating but the loan request generated matching with the lending
capability information, the average borrower rating and the loan request generated not
matching with the lending capability information, and the good borrower rating but
the loan request generated not matching with the lending capability information.
[0028] Further, once the lender response includes the approval, a transaction of the
pre-defined loan amount may have to proceed. Thus, the system (10) also includes a
transaction module (70) operable by the one or more processors (20). The transaction
module (70) is operatively coupled to the lender module (50). The transaction module
(70) is configured to generate a first notification for the lender to perform the
transaction of the pre-defined loan amount from a lender’s account to a borrower’s
account when the lender response is the approval for the loan request generated, the
counteroffer is accepted by the borrower, or a combination thereof. In one
embodiment, the first notification generated may be generated in a form of one a text
message, an E-mail, a pop-up notification on the lender interface, and the likes.
12
[0029] Further, the pre-defined loan amount is linked with the pre-defined interest
rate. In one embodiment, the transaction module (70) may include a payment
subsystem (as shown in FIG. 2). The payment subsystem may be configured to enable
the lender to perform the transaction of the pre-defined loan amount from the lender’s
account to the borrower’s account using one or more payment modes via a payment
gateway. In one exemplary embodiment, the one or more payment modes may include
one of intra-bank transfer, Immediate Payment Service (IMPS), National Electronic
Fund Transfer (NEFT), Unified Payment Interface (UPI), and the like.
[0030] Further, upon receiving the pre-defined loan amount, the borrower may
have to start to repay to the lender. Thus, the transaction module (70) is also configured
to generate a second notification for the borrower to perform a transaction of a due
repayment amount from the borrower’s account to the lender’s account periodically
based on the repayment schedule selected by the borrower from the one or more
repayment schedules displayed on the borrower interface upon registering the
borrower on the centralized platform. In one embodiment, the second notification may
be generated in a form of one a text message, an E-mail, a pop-up notification on the
borrower interface, and the like. In one embodiment, the one or more repayment
schedules may include daily repayment, weekly repayment, monthly repayment,
quarterly repayment, a single payment after completion of the loan duration, or the
like. In one embodiment, the due repayment amount may be associated with the predefined interest rate.
[0031] In one exemplary embodiment, the transaction module (70) may also
include a monitoring subsystem (as shown in FIG. 2), wherein the monitoring
subsystem may be operatively coupled to the payment subsystem. The monitoring
subsystem may be configured to keep a track of the transaction of the due repayment
amount from the borrower’s account to the lender’s account periodically based on the
repayment schedule selected by the borrower until the pre-defined loan amount along
with an additional amount corresponding to the pre-defined interest rate is transferred
into the lender’s account. Further, the monitoring subsystem may be also configured
to terminate the one or more loans once the repayment is completed. Also, in one
embodiment, the monitoring subsystem enables the lender to terminate the one or more
loans via the lender interface when the repayment may be completed via cash.
13
[0032] Further, upon receiving the loan request generated from the borrower, the
lender response may include the counteroffer for the borrower to consider. Thus, the
system (10) also includes a counteroffer generation module (80) operable by the one
or more processors (20). The counteroffer generation module (80) is operatively
coupled to the lender module (50). The counteroffer generation module (80) is
configured to generate the counteroffer for the borrower based on a plurality of factors
using one or more artificial intelligence (AI) and machine learning (ML) techniques
upon receiving the loan request generated, thereby managing and assessing the one or
more loans related to the lender and the borrower within the personalized network.
[0033] Further, the counteroffer includes one of a varied interest rate, a varied loan
amount, a varied loan duration, and the like, or a combination thereof. Later, the
borrower may review the counteroffer generated and respond with an acceptance or a
rejection for the counteroffer based on the convenience of the borrower. Further, based
on the response of the borrower, the lender may proceed with the transaction or
terminate the corresponding one or more loans. In one embodiment, the plurality of
factors may include one of a trust factor between the lender and the borrower, a
transaction history of the lender and the borrower, and the like, or a combination
thereof.
[0034] Further, in one exemplary embodiment, the system (10) may also include a
communication module (as shown in Fig. 2) operable by the one or more processors
(20). The communication module may be operatively coupled to the registration
module. The communication module may be configured to enable the borrower and
the lender to communicate with each other via at least one communication means. The
at least one communication means may include a text message, an E-mail, a phone
call, or the like. In one embodiment, the borrower may communicate one or more
borrower’s concerns to the lender using the communication module. In one exemplary
embodiment, the one or more borrower’s concerns may include a request to change
the pre-defined interest rate associated with the pre-defined loan amount, a request for
delaying the repayment, a request to change a payment mode, and the like. In another
embodiment, the lender may communicate one or more lender’s concerns to the
borrower using the communication module. In one exemplary embodiment, the one or
14
more lender’s concerns may include a reminder message about the repayment, a
response to the request received from the borrower, and the like.
[0035] Further, in one exemplary embodiment, the borrower module (30) may also
be configured to enable the borrower to track and monitor the one or more loans
received, trends across the one or more loans received, identify and highlight the one
or more loans that may turn overdue, and the like via the borrower interface. Moreover,
in one embodiment, the borrower module (30) may also be configured to generate a
favorite lender list of the borrower based on the plurality of factors.
[0036] Furthermore, in one exemplary embodiment, the borrower module (30) may
also be configured to enable the borrower to generate a borrower customized invitation
link to be sent as an invitation to one or more users within the personalized network
of the borrower for registering on the centralized platform. In one embodiment, the
communication module may also be configured to send the borrower customized
invitation link generated via the at least one communication means. Further, in one
embodiment, the borrower module (30) may also be configured to generate one or
more rewards for the borrower when at least one of the one or more users who receive
the invitation from the corresponding borrower, register on the centralized platform
via the corresponding borrower customized invitation link received. In one exemplary
embodiment, the one or more rewards may include a cashback, a coupon, and the like.
[0037] Furthermore, in one exemplary embodiment, the lender module (50) may
also be configured to enable the lender to track and monitor the one or more loans lent,
trends across the one or more loans lent, identify and highlight the one or more loans
that may turn delinquent, and the like via the lender interface. Moreover, in one
embodiment, the lender module (50) may also be configured to generate a favorite
borrower list of the lender based on the plurality of factors.
[0038] Furthermore, in one exemplary embodiment, the lender module (50) may
also be configured to enable the lender to generate a lender customized invitation link
to be sent as an invitation to one or more users within the personalized network of the
lender for registering on the centralized platform. In one embodiment, the
communication module may also be configured to send the lender customized
invitation link generated via the at least one communication means. Further, in one
15
embodiment, the lender module (50) may also be configured to generate the one or
more rewards for the lender when at least one of the one or more users who receive
the invitation from the corresponding lender, register on the centralized platform via
the corresponding lender customized invitation link received.
[0039] Further, in one embodiment, a plurality of details related to the one or more
loans received by the borrower may be stored in the database. In such embodiment,
the plurality of details may include the loan request generated every time the lender is
selected by the borrower, a count of the one or more loans received, the transaction
history of the borrower, the borrow rating, and the like. Similarly, in one embodiment,
the plurality of details related to the one or more loans lent by the lender may be stored
in the database. In such embodiment, the plurality of details may include the loan
request received, a count of the one or more loans lent, the transaction history of the
lender, the lender rating, the lending capability information, and the like.
[0040] Further, in one exemplary embodiment, the system (10) may also include
an alert generation module (as shown in FIG. 2) operable by the one or more
processors (20). The alert generation module may be operatively coupled to the
registration module. The alert generation module may be configured to generate one
or more alerts for both the borrow and the lender based on a plurality of conditions. In
one embodiment, the plurality of conditions based on which the one or more alerts
may be generated to the borrower may include when the borrower forgets to make the
repayment, when the lender becomes actively available for lending the one or more
loans within the personalized network, when the one or more loans are terminated, and
the like. In another embodiment, the plurality of conditions based on which the one or
more alerts may be generated to the lender may include when the borrower forgets to
make the repayment, when the lender receives the loan request, when the one or more
loans are terminated, and the like. In one embodiment, the one or more alerts may be
generated in a form of one of a text message, an E-mail, a pop-up notification, and the
like.
[0041] FIG. 2 is a block diagram representation of an exemplary embodiment of
the system (10) for managing the one or more loans related to the lender and the
borrower within the personalized network of FIG. 1 in accordance with an
embodiment of the present disclosure. Suppose a society (90) includes people
16
including a first group of people (100) who are in need of money and a second group
of people (110) who are willing to lend money. Thus, the society (90) can use the
system (10) for managing the one or more loans of the lender and the borrower within
the society (90) as everyone in the society (90) have a contact number of each other
and form the personalized network which is a trusted network. The system (10)
includes the one or more processors (20). The first group of people (100) include the
one or more borrowers, and the second group of people (110) include the one or more
lenders.
[0042] Further, suppose a lender ‘A’ (120) registers on the centralized platform via
the registration module (130) of the system (10) upon providing the plurality of lender
details via a lender’s mobile phone (140). The plurality of lender details of the lender
‘A’ (120) may be stored in the database (150) of the system (10). Later, upon
registering, the lender ‘A’ (120) broadcasts the lending capability notification via the
lender module (50) for the one or more borrowers to know about the lender ‘A’ (120).
The lending capability notification is associated with the lending capability
information. The lending capability information includes the maximum amount limit
for the lending of 10,000 /-, the pre-defined interest rate of 4 percent (%), and the like.
[0043] Further, the lender ‘A’ (120) has a transaction history as the lender ‘A’ (120)
was involved in lending the one or more loans in past. Thus, the one or more borrowers
have provided the lender rating to the lender ‘A’ (120) via the rating module (160) of
the system (10). Also, the rating module (160) keeps a track of the behavior of the
lender ‘A’ (120) and validates the lender rating provided by the one or more borrowers.
[0044] Further, suppose a borrower ‘X’ (170) registers on the centralized platform
via the registration module (130) upon providing the plurality of borrower details via
a borrower’s mobile phone (180). The plurality of borrower details may also be stored
in the database (150). Later, upon registering, the borrower module (30) of the system
(10) scans the contact list of the borrower ‘X’ (170) in real-time to check the one or
more lenders who are actively available for lending the one or more loans. As used
herein, the term contact list is substantially similar to the term personalized network
described in the description of FIG. 1. Further, as the lender ‘A’ (120) was actively
available for lending, upon scanning, the lender ‘A’ (120) appears to be available.
Also, the lender rating of the lender ‘A’ (120) displayed on the borrower interface
17
included the good lender rating as the rating was five stars out of five stars for both.
Also, the recommendation module (190) of the system (10) generates the
recommendation for the borrower ‘X’ (170) to select the lender ‘A’ (120) based on the
behavior as tracked by the rating module (160) and the one or more lender related
parameters. Thus, the borrower ‘X’ (170) generates the loan request via the borrower
module (30) based on the one or more lender related parameters, wherein the loan
request includes the pre-defined loan amount of 5000 /- and the loan duration of 6
months for the lender ‘A’ (120).
[0045] Further, the borrower ‘X’ (170) has a transaction history as the borrower
‘X’ (170) was involved in borrowing the one or more loans in past. Thus, the one or
more lenders have provided the borrower rating to the borrower ‘X’ (170) via the
rating module (160). Also, the rating module (160) keeps a track of the behavior of
the borrower ‘X’ (170) and validates the borrower rating provided by the one or more
lenders. Here, the borrower rating of the borrower ‘X’ (170) includes the good
borrower rating. Further, the recommendation module (190) generates the
recommendation for the lender ‘A’ (120) to accept the loan request received from the
borrower ‘X’ (170) based on the behavior tracked by the rating module (160) and the
one or more borrower related parameters. Also, as the loan request matches with the
lending capability information, the lender ‘A’ (120) generates the lender response
including the approval via the lender module (50).
[0046] Further, once the lender ‘A’ (120) approves the loan request, a notification
is generated for the lender ‘A’ (120) to perform the transaction via the transaction
module (70). However, the lender ‘A’ (120) generates the counteroffer including the
varied interest rate of 6 % with the varied loan duration of 12 months via the
counteroffer generation module (80) of the system (10) using the one or more AI
techniques and the one or more ML techniques as there is a possibility that the
borrower ‘X’ (170) may be incapable of repaying in time which is predicted based on
the transaction history of the borrower ‘X’ (170).
[0047] Further, the borrower ‘X’ (170) accepts the counteroffer and hence a
notification is generated to the lender ‘A’ (120) via the transaction module (70) to
perform the transaction of the pre-defined loan amount via the payment subsystem
(200) of the transaction module (70). Later, after some time, the borrower ‘X’ (170)
18
may have to initiate the repayment process according to the repayment schedule
selected. The monitoring subsystem (210) of the transaction module (70) keeps a track
of the repayment process and terminates the loan once the repayment completes.
During the repayment process, twice there was a delay in the repayment which was
communicated to the lender ‘A’ (120) by the borrower ‘X’ (170) via the
communication module (220) of the system (10). Also, when there was a delay, an
alert was generated for both the lender ‘A’ (120) and the borrower ‘X’ (170) via the
alert generation module (230) of the system (10).
[0048] FIG. 3 is a block diagram of a loan management computer or a loan
management server (240) in accordance with an embodiment of the present disclosure.
The loan management server (240) includes processor(s) (250), and a memory (260)
coupled to a bus (270). As used herein, the processor(s) (250) and the memory (260)
are substantially similar to the system (10) of FIG. 1. Here, the memory (260) is
located in a local storage device.
[0049] 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.
[0050] 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).
[0051] The memory (260) includes a plurality of modules stored in the form of
executable program which instructs the processor(s) (250) to perform method steps
19
illustrated in FIG. 3. The memory (260) has following modules: a borrower module
(30), a lender module (50), a transaction module (70), and a counteroffer generation
module (80).
[0052] The borrower module (30) is configured to scan the personalized network
of the borrower in a real-time and dynamic fashion, so as check for one or more lenders
actively available for lending the one or more loans in real-time upon registering the
borrower on a centralized platform via a borrower device (40). The borrower module
(30) is also configured to generate a loan request upon selection of the lender by the
borrower within the personalized network of the borrower via a borrower interface
based on one or more lender related parameters. The lender module (50) is configured
to enable the lender to broadcast a lending capability notification within the
personalized network of the lender via a lender interface in real-time upon registering
the lender on the centralized platform via a lender device (60), wherein the lending
capability notification is associated with lending capability information. The lender
module (50) is also configured to generate a lender response upon receiving the loan
request generated by comparing the loan request generated with the lending capability
information, and based on one or more borrower related parameters.
[0053] The transaction module (70) is configured to generate a first notification
for the lender to perform a transaction of a pre-defined loan amount from a lender’s
account to a borrower’s account when one of the lender response is the approval for
the loan request generated, the counteroffer is accepted by the borrower, or a
combination thereof, wherein the pre-defined loan amount is linked with a pre-defined
interest rate. The transaction module (70) is also configured to generate a second
notification for the borrower to perform a transaction of a due repayment amount from
the borrower’s account to the lender’s account periodically based on a repayment
schedule selected by the borrower from one or more repayment schedules displayed
on the borrower interface upon registering the borrower on the centralized platform.
The counteroffer generation module (80) is configured to generate a counteroffer for
the borrower based on a plurality of factors using one or more artificial intelligence
techniques and one or more machine learning techniques upon receiving the approval
for the loan request generated, thereby managing and assessing the one or more loans
related to the lender and the borrower within the personalized network.
20
[0054] FIG. 4 is a flow chart representing steps involved in a method (280) for
managing and assessing one or more loans related to a lender and a borrower within a
personalized network in accordance with an embodiment of the present disclosure.
The method (280) includes scanning the personalized network of the borrower in a
real-time and dynamic fashion, so as check for one or more lenders actively available
for lending the one or more loans in real-time upon registering the borrower on a
centralized platform via a borrower device in step 290. In one embodiment, scanning
the personalized network of the borrower includes scanning the personalized network
of the borrower by a borrower module (30).
[0055] In one exemplary embodiment, the method (280) also includes registering
a user on the centralized platform as one of the lender, the borrower, or a combination
thereof upon receiving one of a plurality of lender details, a plurality of borrower
details, or a combination thereof respectively. In such embodiment, registering the
user includes registering the user by a registration module (130).
[0056] The method (280) also includes generating a loan request upon selection of
the lender by the borrower within the personalized network of the borrower via a
borrower interface based on one or more lender related parameters in step 300. In one
embodiment, generating the loan request includes generating the loan request by the
borrower module (30). In such embodiment, generating the loan request includes
generating the loan request including one of the pre-defined loan amount, a loan
duration, or a combination thereof.
[0057] Furthermore, the method (280) includes enabling the lender to broadcast a
lending capability notification within the personalized network of the lender via a
lender interface in real-time upon registering the lender on the centralized platform via
a lender device, wherein the lending capability notification is associated with lending
capability information in step 310. In one embodiment, enabling the lender to
broadcast the lending capability notification includes enabling the lender to broadcast
the lending capability notification by a lender module (50).
[0058] Furthermore, the method (280) also includes generating a lender response
upon receiving the loan request generated by comparing the loan request generated
with the lending capability information, and based on one or more borrower related
21
parameters, wherein the lender response comprises one of an approval for the loan
request generated, a rejection for the loan request generated, and a counteroffer for the
borrower to consider in step 320. In one embodiment, generating the lender response
includes generating the lender response by the lender module (50).
[0059] Furthermore, the method (280) also includes generating a first notification
for the lender to perform a transaction of a pre-defined loan amount from a lender’s
account to a borrower’s account when one of the lender response is the approval for
the loan request generated, the counteroffer is accepted by the borrower, or a
combination thereof, wherein the pre-defined loan amount is linked with a pre-defined
interest rate in step 330. In one embodiment, generating the first notification includes
generating the first notification by a transaction module (70).
[0060] Furthermore, the method (280) also includes generating a second
notification for the borrower to perform a transaction of a due repayment amount from
the borrower’s account to the lender’s account periodically based on a repayment
schedule selected by the borrower from one or more repayment schedules displayed
on the borrower interface upon registering the borrower on the centralized platform in
step 340. In one embodiment, generating the second notification includes generating
the second notification by the transaction module (70).
[0061] Furthermore, the method (280) also includes generating the counteroffer for
the borrower based on a plurality of factors using one or more artificial intelligence
techniques and one or more machine learning techniques upon receiving the loan
request generated, thereby managing and assessing the one or more loans related to
the lender and the borrower within the personalized network, wherein the counteroffer
includes one of a varied interest rate, a varied loan amount, a varied loan duration, or
a combination thereof in step 350. In one embodiment, generating the counteroffer
includes generating the counteroffer by a counteroffer generation module (80).
[0062] 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.
22
[0063] Various embodiments of the present disclosure enable the lender the
borrower to manage the one or more loans within the personalized network including
friends, the family, acquaintances, and the like in a more formal, easy to track,
structured, and more efficient way. Also, there is no need for any official underwriting
between the lender and the borrower as the personalized network is the trusted network
and the system keeps a track of the transactions made, thereby making the system more
reliable and easier to use. Also, the recommendation generated or the lender and the
borrower on lending the borrowing allows the lender and the borrower to perform the
transaction in a safe and transparent manner.
[0064] 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.
[0065] 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.

I/WE CLAIM:
1. A system (10) for managing and assessing one or more loans related to a
lender and a borrower within a personalized network, wherein the system (10)
comprises:
one or more processors (20);
a borrower module (30) operable by the one or more processors (20),
wherein the borrower module (30) is configured to:
scan the personalized network of the borrower in a real-time and
dynamic fashion, so as to check for one or more lenders actively available
for lending the one or more loans in real-time upon registering the borrower
on a centralized platform via a borrower device (40); and
generate a loan request upon selection of the lender by the borrower
within the personalized network of the borrower via a borrower interface
based on one or more lender related parameters;
a lender module (50) operable by the one or more processors (20), wherein
the lender module (50) is configured to:
enable the lender to broadcast a lending capability notification within
the personalized network of the lender via a lender interface in real-time
upon registering the lender on the centralized platform via a lender device
(60), wherein the lending capability notification is associated with lending
capability information; and
generate a lender response upon receiving the loan request generated
by comparing the loan request generated with the lending capability
information, and based on one or more borrower related parameters,
wherein the lender response comprises one of an approval for the loan
request generated, a rejection for the loan request generated, and a
counteroffer for the borrower to consider;
24
a transaction module (70) operable by the one or more processors (20),
wherein the transaction module (70) is configured to:
generate a first notification for the lender to perform a transaction of a
pre-defined loan amount from a lender’s account to a borrower’s account
when one of the lender response is the approval for the loan request
generated, the counteroffer is accepted by the borrower, or a combination
thereof, wherein the pre-defined loan amount is linked with a pre-defined
interest rate; and
generate a second notification for the borrower to perform a transaction
of a due repayment amount from the borrower’s account to the lender’s
account periodically based on a repayment schedule selected by the
borrower from one or more repayment schedules displayed on the borrower
interface upon registering the borrower on the centralized platform; and
a counteroffer generation module (80) operable by the one or more
processors (20), wherein the counteroffer generation module (80) is configured to
generate the counteroffer for the borrower based on a plurality of factors using one
or more artificial intelligence techniques and one or more machine learning
techniques upon receiving the loan request generated, thereby managing and
assessing the one or more loans related to the lender and the borrower within the
personalized network, wherein the counteroffer comprises one of a varied interest
rate, a varied loan amount, a varied loan duration, or a combination thereof.
2. The system (10) as claimed in claim 1, comprises a registration module
(130) operable by the one or more processors (20), wherein the registration module
(130) is configured to register a user on the centralized platform as one of the
lender, the borrower, or a combination thereof upon receiving one of a plurality of
lender details, a plurality of borrower details, or a combination thereof respectively.
3. The system (10) as claimed in claim 1, wherein the loan request comprises
one of the pre-defined loan amount, a loan duration, or a combination thereof.
25
4. The system (10) as claimed in claim 1, wherein the one or more lender
related parameters comprise one of a lender rating, the lending capability
information, a plurality of lender details, or a combination thereof.
5. The system (10) as claimed in claim 1, wherein the lending capability
information comprises one of a maximum amount limit for lending the one or more
loans, the pre-defined interest rate, the one or more repayment schedules, a lender’s
account balance, or a combination thereof.
6. The system (10) as claimed in claim 1, wherein the one or more borrower
related parameters comprise one of a borrower rating, a plurality of borrower
details, or a combination thereof.
7. The system (10) as claimed in claim 1, wherein the plurality of factors
comprises one of a trust factor between the lender and the borrower, a transaction
history of the lender and the borrower, an inflation rate on the pre-defined interest
rate, or a combination thereof.
8. A method (280) for managing and assessing one or more loans related to a
lender and a borrower within a personalized network, wherein the method (280)
comprises:
scanning, by a borrower module (30), the personalized network of the
borrower in a real-time and dynamic fashion, so as check for one or more lenders
actively available for lending the one or more loans in real-time upon registering
the borrower on a centralized platform via a borrower device; (290)
generating, by the borrower module (30), a loan request upon selection of
the lender by the borrower within the personalized network of the borrower via a
borrower interface based on one or more lender related parameters; (300)
enabling, by a lender module (50), the lender to broadcast a lending
capability notification within the personalized network of the lender via a lender
interface in real-time upon registering the lender on the centralized platform via a
lender device, wherein the lending capability notification is associated with lending
capability information; (310)
26
generating, by the lender module (50), a lender response upon receiving the
loan request generated by comparing the loan request generated with the lending
capability information, and based on one or more borrower related parameters,
wherein the lender response comprises one of an approval for the loan request
generated, a rejection for the loan request generated, and a counteroffer for the
borrower to consider; (320)
generating, by a transaction module (70), a first notification for the lender
to perform a transaction of a pre-defined loan amount from a lender’s account to a
borrower’s account when one of the lender response is the approval for the loan
request generated, the counteroffer is accepted by the borrower, or a combination
thereof, wherein the pre-defined loan amount is linked with a pre-defined interest
rate; (330)
generating, by the transaction module (70), a second notification for the
borrower to perform a transaction of a due repayment amount from the borrower’s
account to the lender’s account periodically based on a repayment schedule selected
by the borrower from one or more repayment schedules displayed on the borrower
interface upon registering the borrower on the centralized platform; and (340)
generating, by a counteroffer generation module (80), the counteroffer for
the borrower based on a plurality of factors using one or more artificial intelligence
techniques and one or more machine learning techniques upon receiving the loan
request generated, thereby managing and assessing the one or more loans related to
the lender and the borrower within the personalized network, wherein the
counteroffer comprises one of a varied interest rate, a varied loan amount, a varied
loan duration, or a combination thereof (350).
9. The method (280) as claimed in claim 8, comprises registering, by a
registration module (130), a user on the centralized platform as one of the lender,
the borrower, or a combination thereof upon receiving one of a plurality of lender
details, a plurality of borrower details, or a combination thereof respectively.
10. The method (280) as claimed in claim 8, wherein generating the loan request
comprises generating the loan request comprising one of the pre-defined loan
amount, a loan duration, or a combination thereof.