AU2020230311A1 - A system and method for use in brokering of loans or enabling the assessment of or comparison of loans - Google Patents

Abstract

A method is disclosed for use in brokering of loans or enabling assessment of or comparison of loans. The method includes: receiving, on a data interface and from a prospective borrower, loan information including information of a desired loan and financial and/or other information of the prospective borrower; determining, on a processor, one or more potentially suitable loans from one or more lenders, the one or more potentially suitable loans representative of loans that are likely to be available to the prospective borrower, the one or more potentially suitable loans determined based upon the loan information and also upon one or more lender models, the one or more lender models formed using knowledge of the one or more lenders' requirements and also knowledge and/or experience of actual lending by the respective lenders; and providing, to the prospective borrower, a user interface including the one or more potentially suitable loans, the user interface configured to enable a comparison of one or more characteristics of each of the potentially suitable loans to be made. 7/9 V) 0 U C0 0 0 C0 0-C CN LLu -J D- 0 C\J D o 0 LU V) 5 z z Lu VU 0 iu LO) u0 _ A -- ( a) z 0 _: Hi L <J < z z D Du < U 0 0 4-J 4-0 CU C 0 E u 00 '4 U)-. CU E 02 0 E 4-J 0)U x =3 Luj Uu

Description

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A SYSTEM AND METHOD FOR USE IN BROKERING OF LOANS OR ENABLING THE ASSESSMENT OF OR COMPARISON OF LOANS TECHNICAL FIELD

[0001] The present invention may find use in relation to the brokering of loans and financial products, and/or in enabling an assessment of, or comparison between, different loans and financial products. In particular, although not exclusively, the invention relates to automated systems and methods that may find use in these areas.

BACKGROUND

[0002] Many potential borrowers find it difficult to understand which one(s) out of the often large number of loan and finance options available on the market are of relevance to them (or accessible by them), let alone compare the different options in an objective manner. As such, brokers are often engaged by potential borrowers to assist in finding suitable loans or financial products.

[0003] Traditionally, brokers essentially act as a conduit between the potential borrower and lenders. A broker will typically assess the financial situation of the potential borrower initially, and help the potential borrower determine or narrow down which one(s) out of a plurality of loan offerings may be accessible to them and suit their needs. The broker will generally also assist the potential borrower in applying for and (hopefully) obtaining a loan.

[0004] One problem for brokers is that their work is very time consuming, and there is a large amount of information to consider, as they must take a large number of factors into account when making recommendations regarding particular loans options to potential borrowers, and also when assisting them in applying for a loan. Several tools exist to help brokers with this work, but it is still a generally time consuming process.

[0005] Another problem is that brokers generally rely largely upon their own personal experience and judgement when making recommendations to guide potential borrowers, but this may mean that not all relevant loan options are always considered for recommendation to the potential borrower. For example, it is possible that a particular loan or financial product may be available on the market, which would be accessible by, and well-suited to, a particular potential borrower, but if the broker is not aware of that particular loan or financial product, the broker will not recommend it to the potential borrower, and as a result the potential borrower may opt for a loan or financial product which is less well-suited to their needs. As a result, potential borrowers may be missing out on potentially preferable opportunities or options that may actually be available to them.

[0006] A further problem is that brokers' advice may sometimes be biased towards lenders from which the broker receives the most commission, or with which they are otherwise associated or affiliated. As an example, a broker may be associated with a particular lender, and due to that relationship, may provide advice or recommendations to potential borrowers that is biased towards loans or financial products offered by that lender, leading to conflicted broker remuneration issues as a result of this bias, and also leading to borrowers obtaining loans that may not be the most suitable ones available.

[0007] Several attempts have been made to alleviate one or more of the above problems with brokers, including by offering automation of loan applications. In some such cases, multiple loan applications for a potential borrower may be filed simultaneously with multiple lenders. A problem, however, with this approach is that even the mere filing of an application for a loan can affect the borrower's credit rating. As such, this approach of filing multiple loan applications simultaneously with multiple lenders, given that most of the simultaneously filed loan applications will (at the very least) not be taken up by the potential borrower (generally only one of the loans applied for will be taken up by the borrower, and some of them may be refused by the various lenders), can lead to harm to the potential borrower's credit rating, which may in turn make it more difficult for them to obtain a loan or finance or credit in the future.

[0008] It can therefore be difficult for a potential borrower to make good financial decisions relating to loan offerings based on their situation, and there would appear to be a need for improved systems and/or methods which may help to alleviate the one or more problems that lead to this difficulty.

[0009] It will be clearly understood that, if a prior art publication is referred to herein, this reference does not constitute an admission that the publication forms part of the common general knowledge in the art in Australia or in any other country.

SUMMARY OF THE INVENTION

[0010] With the foregoing in view, the present invention in one form (although this need not be the only or broadest form) resides broadly in a method for use in brokering of loans or enabling assessment of or comparison of loans, the method including: receiving, on a data interface and from a prospective borrower, loan information including information of (or about) a desired loan (i.e. information about a loan being sought by the prospective borrower including e.g. how much and for what) and financial and/or other information of (or about) the prospective borrower; determining, on a processor, one or more (if there are any) potentially suitable loans from one or more lenders, the one or more potentially suitable loans representative of loans that are actually likely to be available to the prospective borrower, the one or more potentially suitable loans determined based upon the loan information and financial and/or other information of the prospective borrower and also upon one or more lender models, the one or more lender models formed using (at least) knowledge of the one or more lenders' requirements and also knowledge and/or experience of actual lending by the respective lenders; and providing, on the data interface and to the prospective borrower, a user interface including the one or more potentially suitable loans (if there are any), the user interface configured to enable a comparison of one or more characteristics of each of the potentially suitable loans to be made (if there is more than one potentially suitable loan).

[0011] The above method may include, as an optional but advantageous feature, providing, on the user interface, for each potentially suitable loan, an indication of the likelihood that the prospective borrower would be successful in obtaining the loan (i.e. the likelihood that their application would be approved if they were to actually apply to the lender for that loan), the likelihood determined based upon the loan information and financial and/or other information of (or about) the prospective borrower and the one or more lender models.

[0012] The above method may also include, as another optional but advantageous feature, determining, on the processor, based on the loan information and financial and/or other information of the prospective borrower and also on one or more lender models, one or more (if there are any) possible further loans from one or more lenders, the one or more possible further loans representative of loans that are not likely to be available to the prospective borrower, but which would likely be available to the prospective borrower if changes were made to the prospective borrower's circumstances, and providing, on the user interface, for each possible further loan, information about the changes to the prospective borrower's circumstances required for eligibility for the loan.

[0013] The above method may further include, as a further optional but advantageous feature, automatically generating a loan application based upon a selection from among the one or more potentially suitable loans (i.e. automatically generating an actual application by (or on behalf of) the user to the relevant lender based on a selection made by (or on behalf of) the user of a (or one of the) potentially suitable loans provided on the user interface). As part of automatically generating a loan application, the system may also automatically generate loan documentation for completion or execution by the prospective borrower. The system may also have the capability to actually submit the loan application (including supporting documentation) to the lender.

[0014] Advantageously, the method described above helps to enable or improve transparency in presenting different loan offerings to prospective borrowers. It does so, at least in part, by presenting to the prospective borrower one or more "genuine" loan offerings representing actual loan offerings (i.e. loans or other financial products) that are currently being offered by lenders in the marketplace but also limited or filtered (based on the loan information and financial and/or other information of the prospective borrower and through the use of the one or more lender models) to those loans which are determined to be likely available and suitable for the prospective borrower (i.e. the system provides only those loan offerings which the prospective borrower is likely to be able to obtain) based on their actual circumstances, and the method also enables the prospective borrower to make a comparison of the different potentially suitable loan offerings, and optionally also gives the prospective borrower an indication of the assessed likelihood (again based on the loan information and financial and/or other information of (or about) the prospective borrower and through the use of the one or more lender models) of obtaining the respective loan offerings, in a fast and easy to use manner. This in turn helps prospective borrowers to make good financial decisions, based on their own individual situation, in an easy way.

[0015] The method may be used by brokers when interacting with prospective borrowers, and may help to enable brokers to give accurate advice quickly, and thus utilise their time more efficiently. (The method may also be used by the prospective borrower directly.) Furthermore, as the method may often present a plurality of loans options to the prospective borrower which may potentially be accessible and suitable to them based on their particular requirements and circumstances, the advice given by the broker (through the use of the above method) should not be limited to or by the broker's personal experience and judgement, or influenced by any broker bias.

[0016] Furthermore, the method does not require details of (or access to or knowledge of) the algorithms or other assessment criteria actually used by individual lenders when assessing (and approving or denying) loans, nor does it need actual feedback from the lenders to present potentially suitable loan options to the prospective borrowers (for comparison by the prospective borrower and also optionally giving them an indication of likelihood of success). As such, the method is able to operate separately of lenders, and does not create a large number of credit enquiries or applications, which can negatively affect a prospective borrower's credit rating, as discussed above.

[0017] The one or more potentially suitable loans may be provided (i.e. presented to the prospective borrower on the data interface) nearly instantaneously after receiving the loan information. As such, the prospective borrower may be able to make an evaluation of the one or more potentially suitable loans effectively immediately upon submitting the loan information.

[0018] The one or more lender models each include a plurality of parameters relating to consumer information and lender guidelines. Each of the one or more lender models will also generally be generated from data from a plurality of sources. Furthermore, each of the one or more lender models will generally be generated at least in part through the use of machine learning and/or artificial intelligence based on gathered and/or empirical data.

[0019] Each of the one or more lender models may also be updated overtime. Forexample, one or more of the lender models may be updated according to an outcome of a loan application by a prospective borrower. In other words, if a prospective borrower submits a formal application for a particular loan to the relevant lender (whether through the use of the present invention or not), once the outcome of that loan application is determined (i.e. whether the loan has been approved or denied), that outcome may be used (e.g. by the machine learning and/or artificial intelligence used to create the one or more lender models) to update the one or more lender models (e.g. this new information may be used to update at least the lender model for the particular lender concerned).

[0020] Preferably, the loan information (provided by the prospective borrower) includes a loan purpose. The loan purpose may define asset information for which the loan is to be used, e.g. information on a vehicle which the loan is to be used to purchase.

[0021] The method may include automatically selecting one or more assets from a plurality of assets according to the asset information.

[0022] The one or more assets may also be selected according to one or more lender requirements. An example of a lender requirement is a maximum age of a vehicle.

[0023] The loan purpose may define inventory information (e.g. vehicles available for purchase at a particular dealership). The method may include providing on the data interface a selection of inventory (e.g. a selection of the vehicles available for purchase at the particular dealership) that is able to be financed based on the one or more potentially suitable loans determined to be potentially available to the prospective borrower.

[0024] The method may include providing a user interface, from which the loan information is captured. The user interface may include a plurality of data entry elements, such as drop down menus and free text fields.

[0025] The loan information may include supporting documentation, and the user interface may be configured to provide (or enable the provision or acquisition of) such supporting documentation.

[0026] The user interface may be configured to capture imagery of the supporting documentation using a camera e.g. of a smartphone or other computing device. As an illustrative example, the user interface may be configured to capture images of an identification document (e.g. driver's license) of the prospective borrower.

[0027] The method may include automatically verifying that a captured image is suitable as supporting documentation. This may include determining legibility and/or the accuracy of optical character recognition (OCR) of the information in the captured image.

[0028] The method may include automatically recognising data from the image data, and including such data in the loan information. The data may be in the form of text (e.g. name and address) and/or numbers (e.g. license number).

[0029] The method may include obtaining, from the prospective borrower, authorisation to provide access to the prospective borrower's data to third parties. The prospective borrower's data may be provided according to Open Banking or Consumer Data Right (CDR) standards.

[0030] The method may include logging compliance data relating to one or more regulatory standards. The method may include providing the compliance data to a lender.

[0031] The compliance data may include data relating to one or more of a) completion of income and expenses validation; b) completion of serviceability validation; c) completion of lender eligibility validation; d) completion of assessment of serviceability including new lend and max. lend; e) confirming financial data; and f) validating the legitimacy of an asset (e.g. a vehicle) which is being secured if any.

[0032] In embodiments such as those mentioned above, namely where the method includes automatically generating a loan application (by or on behalf of the prospective borrower) based upon a selection from among the one or more potentially suitable loans, and submitting the automatically generated loan application, the method may include providing a bi-directional application program interface (API), to enable sharing of information to the lender (from the prospective borrower) and receiving information from the lender (to the prospective borrower). The lender may, for example, use the API to update a status associated with the selected option (e.g. whether the loan is approved), or request further information from the prospective borrower. The method in these embodiments may further include receiving confirmation that a loan location associated with the selected option is approved, and generating documents for the loan to be signed by the prospective borrower to finalise the loan. The documents may be provided to the prospective borrower on the data interface to be electronically signed.

[0033] The plurality of suitable loans may include multiple loan options with different outcomes, including multiple options from a single lender.

[0034] The method may further include lender risk profiling. The method may include artificial intelligence (AI) analysis of human payment and demographic behaviour to predict a likelihood of defaults.

[0035] In another form (although, again, this need not be the broadest form), the invention resides broadly in a system for use in brokering of loans or enabling assessment of or comparison of loans, the system including: a central server, and a user device, the user device operable by a prospective borrower and able to communicate with the central server; the central server including a processor, a data interface, and a memory; the user device also including a processor, a data interface, and a memory; the memory of the central server including instruction code executable by the processor of the central server, and the memory of the user device including instruction code executable by the processor of the user device, such that together the central server and user device enable: receiving, on the data interface of the central server and from a prospective borrower via the user device, loan information of (or about) a desired loan (i.e. information about a loan being sought by the prospective borrower including e.g. how much and for what) and financial and/or other information of (or about) the prospective borrower; determining, on the processor of the central server, one or more (if there are any) potentially suitable loans from one or more lenders, the one or more potentially suitable loans representative of loans that are actually likely to be available to the prospective borrower, the one or more potentially suitable loans determined based upon the loan information and financial and/or other information of (or about) the prospective borrower and also upon one or more lender models, the one or more lender models formed using (at least) knowledge of the one or more lenders' requirements and also knowledge and/or experience of actual lending by the respective lenders; providing, on the data interface of the user device and to the prospective borrower, a user interface including the one or more potentially suitable loans (if there are any), the user interface of the user device configured to enable a comparison of one or more characteristics of each of the potentially suitable loans to be made (if there is more than one potentially suitable loan).

[0036] The system just described may also, as an optional but advantageous feature, be able to provide, on the user interface of the user device to the prospective borrower, for each potentially suitable loan, an indication of the likelihood that the prospective borrower would be successful in obtaining the loan (i.e. the likelihood that their application would be approved if they were to actually apply to the lender for that loan), the likelihood determined based upon the loan information and financial and/or other information of (or about) the prospective borrower and the one or more lender models.

[0037] The system may further, as another optional but advantageous feature, be able to automatically generate a loan application based upon a selection, made by the prospective borrower on the user interface of the user device, from among the one or more potentially suitable loans provided to the prospective borrower on the data interface of the user device (i.e. it may automatically generate an actual application by (or on behalf of) the user to the relevant lender based on a selection made by (or on behalf of) the user of a (or one of the) potentially suitable loans provided on the user interface).

[0038] Features and aspects described above with reference to the method form of the invention may also be used or form part of embodiments of the system form of the invention, and vice versa. Also, any of the features described herein can be combined in any combination with any one or more of the other features described herein within the scope of the invention.

BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Aspects and embodiments of the invention will be described with reference to the following drawings, in which:

[0040] Figure 1 schematically illustrates the architecture of a system for use in brokering of loans or enabling assessment of or comparison of loans according to an embodiment of the present invention.

[0041] Figure 2 illustrates a screenshot of a loan details screen of the system in Figure 1.

[0042] Figure 3 illustrates a screenshot of a supporting documents screen of the system in Figure 1.

[0043] Figures 4(i)a, 4(ii)a, 4(iii)a and 4(iv)a each contain a table setting out (simplified) details of a number of loan products available from a number of (hypothetical) lenders and the requirements and eligibility criteria applied by the different lenders (in this simplified example) in assessing a prospective borrower's eligibility for each particular loan product shown. The various loan products, and the eligibility criteria, shown in each of Figures 4(i)a, 4(ii)a, 4(iii)a and 4(iv)a are the same. However, Figures 4(i)a, 4(ii)a, 4(iii)a and 4(iv)a, respectively, are each used to help explain and illustrate which one(s) of the different loan products are potentially available to a different hypothetical prospective borrower with different financial and personal circumstances. The hypothetical borrower described with reference to Figure 4(i)a is referred to as "John Smith". The hypothetical borrower described with reference to Figure 4(ii)a is referred to as "Tom Smith". The hypothetical borrower described with reference to Figure 4(iii)a is referred to as "Rob Smith". The hypothetical borrower described with reference to Figure 4(iv)a is referred to as "Ben Smith".

[0044] Figures 4(i)b, 4(ii)b, 4(iii)b and 4(iv)b, respectively, each contains a screenshot of the loan options screen produced by the system in Figure 1, showing the one or more potentially suitable loans available to the relevant hypothetical prospective borrower (i.e. John Smith, Tom Smith, Rob Smith and Ben Smith) in each of the example scenarios described with reference to the tables in Figures 4(i)a, 4(ii)a, 4(iii)a and 4(iv)a.

[0045] Figure 5 is a schematic of the server of the system in Figure 1.

[0046] Figure 6 is a schematic representation of a system for use in brokering of loans or enabling assessment of or comparison of loans, according to an embodiment of the present invention.

[0047] Figure 7 illustrates a method for use in brokering of loans or enabling assessment of or comparison of loans, according to an embodiment of the present invention.

[0048] Preferred features, embodiments and variations of the invention may be discerned from the following Detailed Description which provides sufficient information for those skilled in the art to perform the invention. The Detailed Description is not to be regarded as limiting the scope of the preceding Summary of the Invention in any way.

DETAILED DESCRIPTION

[0049] Figure 1 is a schematic illustration of an system 100, according to an embodiment of the present invention, for use in brokering of loans or enabling assessment of or comparison of loans. The system 100 is particularly useful for enabling prospective borrowers to quickly and easily obtain details of one or more loan options that may potentially be available to them, and suitable for their requirements, based upon their actual circumstances when assessed together with one or more lender models built using artificial intelligence and machine learning based on knowledge of the lenders' requirements and also knowledge and/or experience (and empirical data derived therefrom) of actual lending by the respective lenders.

[0050] The system 100 utilises judgemental lending principals backed by empirical data (incorporated within the one or more lender models), as it uses a wide range of information about borrowers and the credit experience of similar applicants when assessing loans, rather than a pure credit scoring model, as outlined in further detail below.

[0051] The system 100 includes a central server 105, with which a prospective borrower 110 interacts typically by using a smartphone 115. The smartphone 115 includes a software application (app), in which the prospective borrower 110 may enter details of a desired loan (i.e. information about the loan they are seeking including e.g. the desired loan amount and the purpose for which the loan is sought), together with his or her details and information about his or her circumstances.

[0052] Figure 2 shows a screenshot 200 of a loan details screen of the app running on the smartphone 115 in the system 100. The loan details screen includes a loan purpose section 205, and a contact details section 210. The loan purpose section 205 and the contact details section 210 each include a plurality of data entry elements 215 in the form of drop down menus and free text fields, and these enable the prospective borrower 110 to enter details regarding the purpose of the loan (e.g. to purchase a vehicle, equipment or the like), and his or her contact details.

[0053] It will be readily appreciated that the loan details screen may include any number of suitable sections, requesting any relevant information regarding the loan, the prospective borrower 110, his or her circumstances, etc.

[0054] Once the details of the loan are captured in the loan details screen, they are uploaded to the server 105, and associated with a profile of the prospective borrower 110. The profile may also include other basic details of the prospective borrower 110, such as a username password and the like.

[0055] The prospective borrower 110 is then prompted to add financial and other personal circumstances information, including his or her income, expenditure, details of existing assets and debts, age, employment and employment history information, current home/residence information as well as any other financial or other personal circumstances information of relevance. A financial and personal circumstances information screen (not shown), including a plurality of data entry elements similar to those on the loan details screen in Figure 2 may be used to obtain the financial and other personal circumstances information.

[0056] Once the financial and other personal circumstances information is added, the prospective borrower 110 is prompted to review and confirm the information, which is then also uploaded to the server 105 and associated with the profile of the prospective borrower 110.

[0057] Finally, the prospective borrower 110 can also be prompted to add supporting documentation, as may be necessary if the prospective borrower 110 intends to submit a formal loan application via (or through the use of or with the aid of) the system 100. The supporting documentation required may be determined according to (and what documentation will be required will depend on) the data entered in the loan details and financial and other personal circumstances information screens, and will thus be tailored to the specific circumstances of the prospective borrower 110 (and the supporting documentation required will also be dependent on the requirements of the particular lender(s)).

[0058] Figure 3 shows a screenshot 300 of a supporting documents screen of the app running on the smartphone 115 in the system 100.

[0059] The supporting documents screen includes a plurality of supporting document elements 305, each relating to a supporting document that is required. Examples of supporting documents may include identification documents (e.g. driver's license or passport or government-issued ID card), and documents supporting the data entered earlier (e.g. recent payslips and/or bank account balances), proof of employment, proof of housing/residence circumstances), etc.

[0060] Each supporting document element 305 includes an add-document button 310, which enables the prospective borrower 110 to add the corresponding supporting document. In this regard, the prospective borrower 110 may be prompted to choose a file to upload (i.e. a file already stored on or accessible by the smartphone), or capture a document using a camera of the smartphone 115. It may also be possible for the smart phone (and/or the app running on the smartphone) to directly access other data sources (or retrieve data from other sources) like e.g. bank records.

[0061] As an example, in Figure 3 a supporting document element 305 is provided for capturing a driver's license of the prospective borrower 110. In this regard, the prospective borrower 110 may be prompted to capture an image of his or her driver's license 120 using a camera of the smartphone 115. The system may automatically verify that the image of the driver's license is suitable (e.g. is legible or of sufficient optical character recognition (OCR) accuracy), and prompt the user to re-capture an image of the driver's license if that is not the case.

[0062] In alternative embodiments, the system may be configured to capture details of e.g. a government issued identification card, or any other suitable form of identification. The system 100 may prompt the user to capture an image of both sides of an identification card, if appropriate.

[0063] The system may be configured to automatically read (e.g. using OCR) and verify data from the driver's license (or other identification document which has been image captured), such as (in the case of driver's licences) the license number, name and address details, and to automatically enter such information as separate data into the system.

[0064] The supporting documents are then uploaded to the server 105, and associated with the profile of the prospective borrower 110.

[0065] The prospective borrower 110 may be prompted (e.g. by the app) to authorise access to their data by third parties (e.g. potential lenders 125 or brokers or the system 100). Such authorisation may be in the form of privacy forms (or electronic versions thereof) signed by (or electronically signed by) the prospective borrower 110 allowing access to e.g. their credit file (or credit history information), or bank records, or any other kind of data of the prospective borrower that may be relevant to the prospective borrower's eligibility or ability to access a loan but for which authorisation from the borrower is required before the data may be accessed or viewed by lenders 125 or the system 100 or a broker, etc.

[0066] The data of the prospective borrower 110 may be provided according to Open Banking or Consumer Data Right (CDR) standards.

[0067] The server 105 analyses the uploaded data and determines a plurality of loan options available to the prospective borrower 110 using the one or more lender models that have been formed using (at least) knowledge of the one or more lenders' requirements and also knowledge and/or experience of actual lending by the respective lenders . As a result, the loan options are provided to the prospective borrower without having to actually query the lenders 125 (or even contact the lenders in any way), and also without requiring access to or knowledge of the actual algorithms etc used by the lenders 125 in assessing loan applications, while at the same time the loan options presented to the prospective borrower are "genuine" offerings in that they are actual loan offerings currently available from the lenders 125, but filtered and presented based on the actual circumstances of the prospective borrower.

[0068] The knowledge of lenders' requirements may include knowledge of requirements imposed by different lenders relating to things like the prospective borrower's minimum income, employment, housing/residence circumstances, other current debts or liabilities, and/or any other suitable requirements, as discussed further by way of example below. The experience regarding actual lending of the lender is based upon empirical data, as also discussed below.

[0069] To help explain one possible way in which the present invention may be implemented, in order to initially create lender model(s) and in particular the aspects of the initial lender model(s) that rely upon and use knowledge and/or experience of actual lending by different lenders, the present applicant used an initial dataset comprising 4.7 million fields of consumer information, 54,000 lender guideline fields and 2000 credit and security database fields, from a plurality of different sources, and this data was used to create the initial lender model(s). The lender model(s) created from this information (and remember that the lender model(s) also incorporate knowledge of the one or more lenders' requirements) can be applied to the data input by a prospective borrower 110, and that is what the present applicant has done. In different embodiments of the invention, one model may be generated for all lenders 125 (to which the lender may be a parameter), or a separate model or models may be generated for each of the lenders 125.

[0070] By way of further explanation, the initial lender model(s) created by the present applicant were generated, or more specifically the aspects of the model(s) that rely upon and use knowledge and/or experience of actual lending by different lenders were generated, based on (and using) the datasets mentioned in the previous paragraph. This was done by a combination of: cross referencing of data, mathematical analysis (e.g. identifying statistical relationships, correlations and trends from within the data using known mathematical techniques), and also through the use of artificial intelligence and machine learning using the data from the above datasets. The specific details of the actual model(s) created by the present applicant based on the particular above-mentioned datasets (and also based on knowledge of lenders' requirements which also form part of the model(s)) are not critical to the present disclosure (and the specific details need not be described) because, as explained above, the aspects of the model(s) that rely upon and use knowledge and/or experience of actual lending by different lenders which are used in the model(s) in different embodiments and implementations of the present invention will likely be formed (as the present applicant did) through cross-referencing of data, mathematical analysis (e.g. by identifying statistical relationships, correlations and trends within the data), and/or through the use of artificial intelligence and machine learning. As all of these things are necessarily (and inherently) linked to (and dependent upon) the contents of the data (or dataset(s)) from which they are developed, the actual model(s) developed and employed in different embodiments and implementations of the invention will therefore necessarily differ from one another, assuming (as will invariably be the case) that the data upon which these aspects of the model(s) are based (or from which they are formed) is different and/or the specific kinds of data cross-referencing and/or mathematical analyses, etc, used (or the way in which these things were done) in the development of these aspects of the models are different. And of course, the fact that the different lenders with which different embodiments and implementations of the invention will be concerned will also be different, and that such different lenders will have different lending criteria and requirements etc, will also mean that the model(s) used in different embodiments and implementations of the invention will necessarily be different.

[0071] Also, the actual model(s) developed, and specifically the aspects thereof developed based on data relating to experience of previous lending by different lenders, for use in different embodiments or implementations of the invention, will necessarily depend on things like, the different kinds of loans available in different places/markets/countries where the invention is to be implemented, differing regulatory requirements which impact on the way in which (and to whom) loans are offered, differing requirements, criteria, etc, used by different lenders to assess (and approve or deny) loan applications, differing income levels and social demographics of the population, etc, in the different places/markets/countries where the invention is implemented, etc.

[0072] Thus, the specific details of the actual model(s) used (or how it/they are created) are not critical to the present invention. That is to say, the implementation of the present invention is not limited to or by the specifics of the different model(s) (or any particular model(s)) that may be used to (in effect) "model" the way in which different lenders may treat applications for different loan products by different prospective borrowers with different financial and personal circumstances in different embodiments or implications of the invention (which may be developed for different places/markets/countries or the like). Rather, the present invention is more concerned with the concept of employing such model(s) (regardless of the specifics of how such a model(s) were created and regardless of the specifics of the model(s) themselves) in order to determine which one(s) out of a potentially large number of loan products being offered by different lenders will (or are likely to be) available to a prospective borrower having particular financial and personal circumstances, and then providing to the prospective borrower (or presenting to them with) the (one or more) potentially suitable loans for which they may be eligible in a way which enables them to make a comparison between different aspects or characteristics of each such loan product. And, as explained above, a feature or aspect of the invention which is optional but which is thought to be additionally advantageous, is that the model(s) may also be used not only to present the prospective borrower with the various potentially suitable loans which they may be eligible for (to enable a comparison between them), but also with an indication of the likelihood that they would be successful if they were to actually apply for each of those loans.

[0073] The model(s) (regardless of its/their specifics or how it/they were created) can also be updated over time based upon e.g. actual lending data, or changes to the loan products available from different lenders from time to time, etc, thereby enabling the model(s) to adapt and learn. For example, each time a loan is approved or declined (e.g. a loan applied for using the system 100, although information about loans applied for without the use of the system may be used in a similar way), the model can be updated or modified according to the information relating to the loan (and the earnings derivable from) - these modifications would be used to update or modify the aspects of the model that rely upon and use knowledge and/or experience of actual lending by different lenders. Similarly, if a lender makes changes to (or removes) a particular loan product, information about such changes may also be used to update or modify the model - these modifications would be used to update or modify the aspects of the model that relate to knowledge of the different lenders, the products they offer, and their lending requirements.

[0074] Turning now to the example scenarios that will be explained with reference to Figures 4(i)a, 4(ii)a, 4(iii)a and 4(iv)a, as mentioned above, each of these figures contains a table setting out details (these are simplified details for illustrative purposes) of a number of loan products available from a number of lenders and the requirements and eligibility criteria applied by the different lenders (in these simplified examples) in assessing a prospective borrower's eligibility for each particular loan product shown. The various loan products, and the eligibility criteria, shown in each of Figures 4(i)a, 4(ii)a, 4(iii)a and 4(iv)a are the same. However, Figures 4(i)a, 4(ii)a, 4(iii)a and 4(iv)a, respectively, are each used to help explain and illustrate which one(s) of the different loan products might potentially be available to different hypothetical prospective borrowers with different financial and personal circumstances.

[0075] It will be noted that, in each of the tables in Figures 4(i)a, 4(ii)a, 4(iii)a and 4(iv)a (the details in each of these tables are the same), details are given for a number of different loan products being offered by a number of different lenders. For example, Lender A is offering two loan products (Products A.1 and A.2), Lender B is offering only a single loan product (Product B), Lender C is offering three loan products (Products C.1, C.2 and C.3), etc. Also, set out in the tables in these Figures are the following details for each one of the different loan products offered by the various lenders:

- the minimum loan amount (i.e. the minimum amount that can be lent in that particular loan product), - the maximum loan amount (i.e. the maximum amount that can be lent in that particular loan product), - the annual interest rate of that loan product, - the housing status of borrowers to whom the particular loan product can be offered (e.g. Loan Product A.1 from Lender A is only available to prospective borrowers who own their own home (although this includes those who own their home subject to a mortgage), whereas Loan Product A.2 from Lender A is also available to prospective borrowers who are renting or boarding), - the employment status of borrowers to whom the particular loan product can be offered (e.g. Loan Product A.1 from Lender A is only available to prospective borrowers who are in full-time (FT) employment, whereas Loan Product A.2 from Lender A is also available to prospective borrowers who are in part-time (PT) and casual (C) employment); - the employment tenure (i.e. period of employment) of borrowers to whom the particular loan product can be offered (e.g. Loan Product A.1 from Lender A is only available to prospective borrowers who have been in full-time employment for a period of more than two years (2Y), whereas Loan Product A.2 from Lender A is also available to prospective borrowers who are in casual or part-time employment, provided their casual or part-time employment has been for more than 12 months (12M)), - the age range of prospective borrowers to whom the particular loan product can be offered; - the type of asset which the particular loan product permits to be purchased with the lent funds; - the age of the asset which the particular loan product permits to be purchased with the lent funds; - the amount (if any) of allowable financial defaults that the prospective borrower may have and still be eligible for the particular loan product; - whether or not the prospective borrower has engaged in gambling in the last six months; - the amount of "disposable" income which the prospective borrower is required to have in order to be eligible for the particular loan product; and - the number of other ongoing/current loans that a prospective borrower may have and still be eligible for the particular loan product.

[0076] Turning now to Figure 4(i)a, as mentioned above, the hypothetical borrower that will now be described with reference to Figure 4(i)a is referred to as "John Smith". In this example described with reference to Figure 4(i)a, John Smith is the owner of his own house (Property Type = Owner), and he has been working full-time (Employment Type = Full-Time/FT) with the same company for 4 years and 10 months. John is 45 years old and he is trying to buy a brand new car priced at $50,000. John does not gamble, and the amount of his income which is

"disposable" is 15%. John has $10,000 in savings and is currently paying two (2) other personal loans plus one (1) additional car loan.

[0077] In this example scenario, when John provides the above information to the system (the way in which this is done is discussed above), the system's lender model(s) (which are implemented on the processor of the central server 105) determine that the only loan products that John will currently qualify for are Product B and Product E. This is because of the number of loans John is currently servicing. Out of Product B and Product E, the preferable product is Product E because the interest rate of Product E is better (5% less) than that of Product B. This is why Product B is presented beneath (i.e. further down the list than) Product E in the screenshot in Figure 4(i)b, which is what would be presented to John by the system on the smartphone 115. Thus, the system indicates to John that he would likely (89% chance) be able to obtain a loan of $40,000 under Product E (at an interest rate of 20%), and with the $10,000 he has in savings, this would enable him to buy the new car priced at $50,000.

[0078] However, continuing to refer to the above example involving John Smith, if the system further detects (which it would do if/when this information were entered) that the remaining amount to be paid on John's current car loan is only $5000 and that he is paying 15% interest on that current car loan, then the system would further notify John that if he were to use $5000 of his current savings to pay off the current car loan, he would then also likely qualify for Product A.1 (as he would then only have two other current loans, not three). Furthermore, the system would also indicate that he would likely (80% chance) obtain approval for a loan in the amount of $45,000 under Product A.1 at an interest rate of 6.9% (which is much better than the % interest rate he is currently paying on his current car loan), and with the remaining $5000 in his savings (after paying off the current car loan), this would again enable him to purchase the new car priced at $50,000. This option would be even more preferable than the option discussed in the previous paragraph because, in this scenario (insofar as car loans are concerned) John would only be paying a single car loan at 6.9% (rather than two separate car loans at 15% for the existing car loan and 20% for the new car loan under Product E). Because this option (Product A.1) is more preferable than the option discussed in the previous paragraph, this option is shown above (i.e. further up the list) than Product E and Product B mentioned above. Note, however, that although the system would notify John of the possible availability of this option (Product A.1) if he were to do as described above, the fact remains that John is not currently (based on his circumstances as they currently stand) eligible for Product A.1. This is why a "" and a message reading "changed circumstances required - see details" are given next to the likelihood for this option in Figure 4(i)b. This would prompt John to click on the drop down button for this option in order to obtain further information about this suggestion provided by the system

(i.e. about what John could do in order to be able to access Product A.1).

[0079] Still referring to the example involving John Smith, the system would further identify that if John were to not only use $5000 of his current savings to pay off his current car loan (as in the previous paragraph), but also wait for another 2 months (i.e. until his employment tenure is greater than five years (>5Y)), he would then also be eligible to access Product D.1, which is actually the product with the lowest interest rate available (in this simplified scenario). This option would be even more preferable still (i.e. better even than the option discussed in the previous paragraph) because, in this scenario, John Smith would again only be paying a single car loan (like in the previous paragraph), but in this case the interest rate for his car repayments would be lower at 5.5%. However, note again that although the system would notify John of the possible availability of this option (Product D.1) if he were to do as described above, the fact remains that John is also not currently (based on his circumstances as they currently stand) eligible for Product D.1. This is why a "*"and a message reading "changed circumstances required - see details" are again given next to the likelihood for this option in Figure 4(i)b. This would again prompt John to click on the drop down button for this option in order to obtain further information about this suggestion provided by the system (i.e. about what John could do in order to be able to access Product D.1).

[0080] Turning now to Figure 4(ii)a, as mentioned above, the hypothetical borrower that will now be described with reference to Figure 4(ii)a is referred to as "Tom Smith". In this example described with reference to Figure 4(ii)a, Tom is currently renting the unit where he lives (Property Type = Renting), and he has been working as a casual (Employment Type = Casual/C) in the same company for the last 2 years (Tenure = 2 years). Tom is 25 years old and he wants to buy a used car which is 5 years old and priced at AU$15,000. Tom does not gamble, and 5% of his income (equivalent to $500) is "disposable". Tom has no savings but also no other loans that he is currently servicing.

[0081] In this second example scenario, when Tom provides the above information to the system, the system's lender model(s) determine that Tom will likely be eligible for four products, Products A.2, B, C.2 and E. This is mainly due to the fact that he is a casual employee, and also to the value and age of the car he wishes to purchase. Out of these four products, the preferable product is Product A.2 because the interest rate is better than in the other three. This is why Product A.2 is presented above (i.e. further up the list than) Products B, C.2 and E in the screenshot in Figure 4(ii)b, which is what would be presented to Tom by the system on the smartphone 115. Thus, the system indicates to Tom that he would likely (81% chance) be able to obtain a loan of $15,000 under Product A.2 (at an interest rate of 8.9%), and this would enable him to buy the used car priced at $15,000.

[0082] However, continuing to refer to the above example involving Tom Smith, the system would also identify and notify Tom that if he were to instead buy a newer car (specifically one less than three years old) he would then also likely qualify for Product D.2, which has an even lower interest rate at 7.5%. This option would be even more preferable than the option discussed in the previous paragraph, so this option is shown above (i.e. further up the list) than Products A.2, B, C.2 and E mentioned in the previous paragraph. Note, however, that although the system would notify Tom of the possible availability of this option (Product D.2) if he were to do the above (buy a car that is less than three years old), the fact remains that Tom would not be eligible for Product D.2 if he continues with his current plan to purchase a car that is 5 years (and therefore more than 3 years) old. This is why a "*"and a message reading "changed asset age required - see details" are given next to the likelihood of this option in Figure 4(ii)b. This would prompt Tom to click on the drop down button for this option in order to obtain further information about this suggestion provided by the system (i.e. about what Tom could do in order to be able to access Product D.2, i.e. look to buy a newer car).

[0083] Turning next to Figure 4(iii)a, as mentioned above, the hypothetical borrower that will now be described with reference to Figure 4(iii)a is referred to as "Rob Smith". In this example described with reference to Figure 4(iii)a, Rob is currently renting a unit (Property Type = Renting), and he has been in full-time employment (Employment Type = FT) with the same company for 2 years (Tenure = 2Y). Rob Smith is 24 years old (he turns 25 in 10 months), and he wishes to buy a boat that he can use to have fun with his friends. The boat he intends to purchase is priced at $20,000 and is five years old. The amount of Rob's income which is "disposable" is 13% of his total income (which equates to $500). Rob has engaged in gambling throughout the past year. Rob has no other savings, but also no other current loans.

[0084] In this third example scenario, when Rob provides the above information to the system, the system's lender model(s) determine that he will likely be eligible for Products B and C.2. This is mainly due to the fact that he has only been employed (albeit full-time) for two years, the fact that he is renting, and also the fact that he has recently engaged in gambling. Out of Products B and C.2, the preferable product is Product C.2 because the interest rate is better. This is why Product C.2 is presented above (i.e. further up the list than) Product B in the screenshot in Figure 4(iii)b, which is what would be presented to Rob by the system on the smartphone 115. Thus, the system indicates to Rob Smith that he would likely (83% chance) be able to obtain a loan of $20,000 under Product C.2 (at interest rate of 9.9%), and this would enable him to buy the boat priced at $20,000.

[0085] However, continuing to refer to the above example involving Rob Smith, the system would also identify and notify Rob that if he were to either stop gambling (for at least 6 months) or wait until he turns 25, he would then be able to access more preferable loan products, namely Products D.2 and A.2 (of which Product D.2 is the more preferable due to its lower interest rate). However, unfortunately, this means that Rob will need to wait for at least 6 months (and not gamble in that time) in order to be eligible for Product A.2, or he will need to wait for 10 months in order to be eligible for Product D.2. Note that (similar to above) although the system would notify Rob of the possible availability of these options (Products A.2 and D.2) if he were to wait, as just described, the fact remains that Rob would not be eligible for the either of these products at this time. This is why a "*"and an indicative message is given next to the likelihoods of both of these options in Figure 4(iii)b. This would prompt Rob to click on the drop down button for each of these options in order to obtain further information about these suggestions provided by the system (i.e. about what Rob might be able to do in order to be able to access Product A.2 or D.2).

[0086] Turning to Figure 4(iv)a, as mentioned above, the hypothetical borrower that will now be described with reference to Figure 4(iv)a is referred to as "Ben Smith". In this example described with reference to Figure 4(iv)a, Ben Smith owns his own home (Property Type = Owner), and he has been in part-time employment (Employment Type = PT) with the same company for 2 years (Tenure =2Y). Ben is 39 years old and is trying to obtain a loan of $10,000 in cash to celebrate his 4 0th birthday in Europe. Ben has only a small amount (around $5) of his income that can be considered "disposable", and he has no savings. On the other hand, he does not gamble and has no other loans. Unfortunately, he does have a car loan for which he is in default in the amount of $21,000. His explanation for this is that he became upset because the car he purchased was not in good condition and he consequently crashed it. He therefore decided that he was not going to pay for that car. He has, however, paid his home mortgage and other car loans and personal loans without any problems.

[0087] In this fourth example scenario, when Ben provides the above information to the system, the system's lender model(s) determine that he will likely only be eligible for Product B. This is due to the amount of the default on his previous (unpaid) car loan. Thus, the system indicates to Ben that he would likely (90% chance) be able to obtain a loan of $10,000 under Product B (at an interest rate of 25%), and this would enable him to borrow the $10,000 cash he is seeking.

[0088] However, continuing to refer to the above example involving Ben Smith, the system would also identify and notify Ben that if he were to rectify the $21,000 default situation with his previous (unpaid) car loan, he may then also be able to access a more preferable product once that has been resolved. In this instance, however, the only other (and the only more preferable) available product is Product E, due to Ben's limited disposable income. Note that (similar to above) although the system would notify Ben of the possible availability of Products E if he were to resolve his previous $21,000 default, the fact remains that Ben would not be eligible for Product E at this time (while his default remains unresolved). This is why a and "*" a message stating "changed circumstances required-see details" are given next to the likelihood of this option in Figure 4(iv)b. This would prompt Ben to click on the drop down button for this option in order to obtain further information about this suggestion provided by the system (i.e. that Ben may be able to access a more preferable product (Product E) if his $21,000 default were resolved).

[0089] Returning to the system 100 generally, in addition to analysing information (e.g. as just described), the server 105 may employ a variety of authentication and anti-fraud mechanisms, including cross checking of information provided by the prospective borrower 110, the checking of identification, checking the place of residence and employment by the prospective borrower 110, serviceability testing (i.e. the ability of a borrower 110 to meet loan repayments, based upon the loan amount, the borrower's income, expenses and other commitments), as well any other eligibility testing.

[0090] If any information is deemed potentially erroneous, or requiring of further verification, a message may be automatically provided to the prospective borrower 110 indicating this, and inviting the prospective borrower 110 to either correct the information or provide further information.

[0091] If the information is not deemed potentially erroneous, or requiring of further verification, the plurality of loan options that are available to the prospective borrower are then provided to the borrower in a manner that enables comparison of one or more characteristics of each of the plurality of suitable loans (e.g. as shown in Figures 4(i)b, 4(ii)b, 4(iii)b and 4(iv)b). These characteristics can include loan term, interest rate, repayment amount (e.g. monthly repayment amount), other terms including balloon, or any suitable characteristics. The system may present multiple loan options with different outcomes, including multiple options from a single lender.

[0092] Figures 4(i)b, 4(ii)b, 4(iii)b and 4(iv)b (already described) are screenshots 400 of a loan options screen of the system 100, provided on the smartphone 115.

[0093] With reference to Figure 4(i)b, the loan options screen includes a plurality of loan option elements 405, each loan option element 405 relating to a loan option that is considered to be available (or potentially available) to the prospective borrower 110 (as discussed above).

[0094] The loan option elements 405 include characteristics 410 of each loan, including lenders details, term, interest rate, and repayment amount, etc, presented in fixed layout to enable simple comparison of the options. Each loan element also includes a drop-down button 415, which enables the prospective borrower 100 to obtain further information about the loan in each element 405.

[0095] It will be appreciated that the particular loan characteristics 410 of the loan options displayed in each of the elements 405 in Figures 4(i)b, 4(ii)b, 4(iii)b and 4(iv)b are examples for illustrative purposes only , and any suitable characteristics (or combination of characteristics) may be included.

[0096] The prospective borrower 110 may choose an option through selection of a loan option element 405, and in some embodiments, upon the selection of an option by the user, a loan application is automatically prepared and provided to the lender 125 which offers that option. The prospective borrower 110 may then be prompted to confirm details and/or also confirm that he or she wishes to apply for the loan (so that an actual loan application is not submitted to the lender inadvertently or by accident).

[0097] The server 105 may generate documents for the loan to finalise the loan application based upon the data input by the prospective borrower 110 and requirements of the lender 125 associated with the selected loan. As such, each lender may be provided with loan documents that fit well with their system, but also in a manner that is transparent to the prospective borrower.

[0098] The loan application may be generated according to a template associated with the particular lender 125, and each lender may have a different template (or some lenders may use a different template to others). Similarly, the loan application may be generated according to one or more other requirements of the lender 125.

[0099] In addition to the above, the server 105 also captures and records information for compliance purposes, including information regarding a) completion of income and expenses validation; b) completion of serviceability validation; c) completion of lender eligibility validation; d) completion of assessment of serviceability including new lend and max. lend; e) confirming financial data; and f) validating the legitimacy of a vehicle (or other asset) against which the loan is being secured (if any). This information, and any other suitable information, may be saved for compliance purposes, and provided to the lender 125 associated with the selected loan, e.g. together with the loan documents.

[00100] The server 105 also includes a bi-directional application program interface (API), which enables the bidirectional sharing of information relating to the selected option between the server 105 and the lender 125 associated with the selected option.

[00101] As an illustrative example, the lender 125 may update a status associated with the selected option (e.g. whether the loan is approved), or request further information from the prospective borrower 110. This may be provided to the borrower through the smartphone 115.

[00102] If the loan of the selected option is approved, the server 105 may generate documents for the loan to be signed by the prospective borrower 110 to finalise the loan. The server 105 may provide the documents to the prospective borrower 110 using the smartphone 115 or another computing device (e.g. a computer by email), upon which the documents may be electronically signed. Once signed, the signed documents are uploaded to the server 105, and provided to the lender 125.

[00103] In alternative embodiments, the documents may be provided by the lender 125 to the server 105, rather than generated at the server 105. Similarly, the server 105 may be configured to receive scanned or photographed images of the signed documents, rather than electronically signed documents.

[00104] Thus, the system 100 initially assesses the prospective borrower in a manner that "models" (or mimics) an actual assessment of the lenders 125, but without any such actual assessment by the lender, and without having full details of such assessment. This is particularly useful, as it enables the server 105 to make a judgement based upon what a lender is likely to do, rather than what a lender advertises they do (which can be quite different).

[00105] This assessment process is automated by the server 105, which enables the prospective borrower 110 to quickly get an indication of the options that are available to them, without having to actually apply for any loan, or otherwise be bound by delays with each of the lenders 125. While only two lenders 125 are actually shown in Figure 1, nevertheless Figure 1 is intended to represent a number of lenders (i.e. Lender 1, Lender 2,... Lender n), and in practice a large number of lenders will often be considered (e.g. typically tens of lenders, such as 40 or 50 lenders), which could not be practically considered through separate loan applications, and an ordinary broker could not be expected to be familiar with all of the various products offered by this many lenders.

[00106] Thus, the system allows the prospective borrower 105 to have transparency over a potentially large number of loan offerings (from a potentially large number of lenders) nearly or effectively instantaneously, based on actual circumstantial data (of the prospective borrower) and empirical data (incorporated as part of the lender model(s)). This in turn enables the prospective borrower 110 to make betterfinancial decision based on their situation, in an efficient manner.

[00107] Figure 5 is a schematic of the server 105 in Figure 1.

[00108] The server 105 includes a data acquisition module 505, which is used to acquire customer data from the prospective borrower 110. The data acquisition module 505 is configured to generate user interfaces, and receive data input from the prospective borrower 110 therethrough.

[00109] A data analysis module 510 is coupled to the data acquisition module 505, and receives the customer data from the prospective borrower 110 for analysis. The data analysis module 510 is also coupled to one or more lender models 515, which are used (together with external factors) to perform the analysis. The way in which the models may be created is discussed above.

[00110] The server 105 further includes a document generation module 520, which is configured to generate customer forms for the prospective borrower 110, and forms for the lender 125 based upon data from the data acquisition module. The document generation module 520 also generates national consumer code protection (NCCP) documents, as required by the Australian Securities and Investments Commission (ASIC).

[00111] Finally, the server 105 includes a compliance module 525, which is configured to monitor interaction with the prospective borrower 110, and document such interaction for compliance purposes. The compliance module 525 is coupled to the data acquisition module 505, to enable the server 105 to specifically query the prospective borrower 110 in compliance related matters.

[00112] It will be readily appreciated that the schematic in Figure 5 may be complemented with a variety of other modules to perform one or more other functions, as desired.

[00113] While not illustrated, a broker may act as an intermediary between the prospective borrower and the system, or use the system on behalf of the prospective borrower. In some embodiments, many brokers may interact with the server, each offering services using the system.

[00114] Figure 6 illustrates a system 600 for use in brokering of loans or enabling assessment of or comparison of loans, according to an embodiment of the present invention. The system 600 is similar to the system 100, but adapted to be used by a plurality of brokers.

[00115] The system 600 includes a central server 605, much like the central server 105 of the system 100. The central server 605 is, however, not configured to engage directly with customers through customer devices, such as smartphones, but instead through brokers, and in particular broker servers 610.

[00116] In use, prospective borrowers interact with broker servers 610, using customer devices 615, such as smartphones, in a similar manner to how prospective borrowers interact with the server 105 in the system 100 of Figure 1. The broker servers 610 function, however, much like gateways, where information is relayed back and forward between the customer devices 615 and the central server 605. Such configuration enables the brokers to apply their branding and look to the pages that are provided to the customer devices.

[00117] Each broker will generally work with a plurality of different prospective borrowers, and the brokers may work in competition to each other, and for different organisations.

[00118] The broker servers 610 may also enable the broker to review material, such as loan paperwork or the like, prior to it being submitted to the lender servers 620. As a result, the system 600 is able to utilise the speed of automation, in combination with the experience of a broker.

[00119] Similarly, brokers may use the system 600 to screen loan candidates to avoid spending time on candidates with little chance of loan approval.

[00120] In some embodiments, as already discussed to some extent above, in addition to obtaining loan and personal information from the prospective borrower 110, the systems 100, 600 may also obtain loan objective/purpose information, such as whether the prospective borrower 110 is interested in a loan for a particular type of vehicle, or other type of asset. The systems 100, 600 may also obtain data associated with the client objective or purpose, such as trade information. The system may obtain such information using the server 105, 605, and the smartphone 115 or customer devices 615, in a similar manner to the other information obtaining from the client, as outlined above.

[00121] In such embodiments, in addition to providing details of suitable loans, the systems 100, 600 may present suitable assets (e.g. vehicles) that meet the criteria set by the prospective borrower (e.g. relating to the type of vehicle), as well as criteria set by the lender (e.g. relating to the age of the vehicle). In the case of a vehicle, if a vehicle is to be traded as part of the offer, the system 100, 600 may also present an offer on the trade- in.

[00122] The customer may select an offer independently of a vehicle (or other asset), or select a vehicle (or other asset) in association with a loan offer. This enables dealerships (e.g. car dealerships or other asset vendors/dealers) to provide offers relating to particular types of vehicles (or other asset) purchased from them, such as vehicles of a particular brand, and offer vehicles that are eligible for the potential buyer's unique circumstances.

[00123] Figure 7 illustrates a method 700 for use in brokering of loans or enabling assessment of or comparison of loans, according to an embodiment of the present invention. The method 700 may be similar or identical to the methods used by the systems 100, 600, outlined above.

[00124] At step 705, loan information is received on a data interface and from a prospective borrower. The loan information includes information of (or about) a desired loan (i.e. information about a loan being sought by the prospective borrower including e.g. how much and for what) and financial and/or other information of (or about) the prospective borrower.

[00125] At step 710, one or more potentially suitable loans (if there are any) from one or more lenders are determined on a processor. The suitable loans are representative of loans that are actually likely to be available to the prospective borrower. The one or more potentially suitable loans are determined based upon the loan information and financial and/or other information of the prospective borrower (received at step 705) and also upon one or more lender models. As explained above, the one or more lender models are formed using knowledge of the one or more lenders' requirements and also knowledge and/or experience of actual lending by the respective lenders.

[00126] At step 715, a user interface is provided on the data interface and to the prospective borrower. The user interface includes the one or more potentially suitable loans (if there are any), and it is configured to enable a comparison of one or more characteristics of each of the potentially suitable loans to be made (if there is more than one potentially suitable loan).

[00127] At optional step 720, the user interface is used to provide to the prospective borrower, for each potentially suitable loan, an indication (e.g. a percentage chance) of the likelihood that the borrower would be successful in obtaining the loan.

[00128] At optional step 725, a loan application is automatically generated based upon a selection from among the one or more loans.

[00129] While terms like "loan" and "loan product" and the like have mostly been used above, it will be readily appreciated that the present invention may also be used for a variety of credit based offerings, including credit cards and personal loans.

[00130] Advantageously, embodiments of the invention provide prospective borrowers with a transparent and near (or effectively) instantaneous comparison of loan offerings that are tailored to the prospective borrower based on actual data that is available from a combination of sources. This in turn allows for a clear and objective offering to the consumer, so a consumer can make the best financial decision based on their own individual situation.

[00131] The systems and methods do not require full information about each of the lenders algorithms, or feedback from the lenders to provide the near instantaneous comparison. Instead, the methods enable use of empirical data, which enables the methods to operate independently of the lenders.

[00132] Previously, brokers presented prospective borrowers with multiple options based upon their personal judgement and assessment of the situation, which was both time consuming and prone to bias and error. The systems and methods enable near instantaneous options to be provided, without the risk of bias or error, as the options generated will not be limited to the brokers experiences.

[00133] Furthermore, the system enables expenses, such as cost of living, to be considered in a more accurate manner, reducing risk associated with lending, and ensuring compliance with responsible lending rules and standards.

[00134] In certain embodiments, Al analysis of human payment and demographic behaviour may be used to predict likelihood of defaults.

[00135] In the present specification and claims (if any), the word 'comprising' and its derivatives including 'comprises' and 'comprise' include each of the stated integers but does not exclude the inclusion of one or more further integers.

[00136] Reference throughout this specification to 'one embodiment' or 'an embodiment' means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the present invention. Thus, the appearance of the phrases 'in one embodiment' or 'in an embodiment' in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more combinations.

[00137] In compliance with the statute, the invention has been described in language more or less specific to structural or methodical features. It is to be understood that the invention is not limited to specific features shown or described since the means herein described comprises preferred forms of putting the invention into effect. The invention is, therefore, claimed in any of its forms or modifications within the proper scope of the appended claims (if any) appropriately interpreted by those skilled in the art.

Claims (20)

1. A method for use in brokering of loans or enabling assessment of or comparison of loans, the method including: receiving, on a data interface and from a prospective borrower, loan information including information of a desired loan and financial and/or other information of the prospective borrower; determining, on a processor, one or more potentially suitable loans from one or more lenders, the one or more potentially suitable loans representative of loans that are likely to be available to the prospective borrower, the one or more potentially suitable loans determined based upon the loan information and/or other information of the prospective borrower and also upon one or more lender models, the one or more lender models formed using knowledge of the one or more lenders' requirements and also knowledge and/or experience of actual lending by the respective lenders; and providing, to the prospective borrower, a user interface including the one or more potentially suitable loans, the user interface configured to enable a comparison of one or more characteristics of each of the potentially suitable loans to be made.

2. The method as claimed in claim 1 further including providing, on the user interface, for each potentially suitable loan, an indication of the likelihood that the prospective borrower would be successful in obtaining the loan, wherein the likelihood is determined based upon the loan information and/or other information of the prospective borrower and the one or more lender models.

3. The method as claimed in claim 1 or 2 further including determining, on the processor, based on the loan information and financial and/or other information of the prospective borrower and also on one or more lender models, one or more possible further loans from one or more lenders, the one or more possible further loans representative of loans that are not likely to be available to the prospective borrower, but which would likely be available to the prospective borrower if changes were made to the prospective borrower's circumstances, and providing, on the user interface, for each possible further loan, information about the changes to the prospective borrower's circumstances required for eligibility for the loan.

4. The method as claimed in any one of the preceding claims, further including automatically generating a loan application based upon a selection from among the one or more potentially suitable loans.

5. The method as claimed in any one of the preceding claims, wherein the one or more potentially suitable loans are provided nearly instantaneously after receiving the loan information.

6. The method as claimed in any one of the preceding claims, wherein the one or more lender models each include a plurality of parameters relating to consumer information and lender guidelines.

7. The method as claimed in any one of the preceding claims, wherein each of the one or more lender models is generated from data from a plurality of sources.

8. The method as claimed in any one of the preceding claims, wherein each of the one or more lender models is generated at least in part through the use of machine learning and/or artificial intelligence based on gathered and/or empirical data.

9. The method as claimed in any one of the preceding claims, wherein one or more of the lender models are updated over time.

10. The method as claimed in any one of the preceding claims further including providing a user interface from which the loan information is captured.

11. The method as claimed in claim 10, wherein the user interface includes a plurality of data entry elements, such as drop-down menus and free text fields.

12. The method as claimed in claim 10 or 11, wherein the loan information includes supporting documentation, and the user interface is configured to provide or enable the provision or acquisition of such supporting documentation.

13. The method as claimed in claim 12, wherein the user interface is configured to capture imagery of the supporting documentation using a camera.

14. The method as claimed in claim 13, further including automatically verifying that a captured image is suitable as supporting documentation.

15. The method as claimed in claim 13 or 14, further including automatically recognising data from the image data, and including such data in the loan information.

16. The method as claimed in any one of the preceding claims, further including obtaining, from the prospective borrower, authorisation to provide access to the prospective borrower's data to third parties.

17. The method as claimed in claim 4, or the method as claimed in any one of claims 5-16 when dependent on claim 4, the method further including providing a bi-directional application program interface (API) to enable sharing of information to the lender (from the prospective borrower) and receiving information from the lender (to the prospective borrower).

18. A system for use in brokering of loans or enabling assessment of or comparison of loans, the system including: a central server, and a user device, the user device operable by a prospective borrower and able to communicate with the central server; the central server including a processor, a data interface, and a memory; the user device also including a processor, a data interface, and a memory; the memory of the central server including instruction code executable by the processor of the central server, and the memory of the user device including instruction code executable by the processor of the user device, such that together the central server and user device enable: receiving, on the data interface of the central server and from a prospective borrower via the user device, loan information of a desired loan and financial and/or other information of the prospective borrower; determining, on the processor of the central server, one or more potentially suitable loans from one or more lenders, the one or more potentially suitable loans representative of loans that are likely to be available to the prospective borrower, the one or more potentially suitable loans determined based upon the loan information and financial and/or other information of the prospective borrower and also upon one or more lender models, the one or more lender models formed using knowledge of the one or more lenders' requirements and also knowledge and/or experience of actual lending by the respective lenders; providing, on the data interface of the user device and to the prospective borrower, a user interface including the one or more potentially suitable loans, the user interface of the user device configured to enable a comparison of one or more characteristics of each of the potentially suitable loans to be made.

19. The system as claimed in claim 18 wherein together the central server and user device enable the provision, on the user interface of the user device to the prospective borrower, for each potentially suitable loan, an indication of the likelihood that the prospective borrower would be successful in obtaining the loan, the likelihood determined based upon the loan information and financial and/or other information of the prospective borrower and the one or more lender models.

20. The system as claimed in claim 18 or 19 wherein together the central server and user device enable the automatic generation of a loan application based upon a selection, made by the prospective borrower on the user interface of the user device, from among the one or more potentially suitable loans provided to the prospective borrower on the data interface of the user device.

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Market Products Assessment Criteria Min Max Employment Type Unpaid Gambling Max Interest Ternure (Y= years, Asset Age Disposable Lender Product Loan Loan Property Type (Full Time, Casual, Age Asset Type Financial (last 6 Ongoing Rate M = months) (years) Income Amount Amount Part Time) Defaults months) Loans Product A.1 10000 100000 6.90% Owner, Mortgaged FT >2 Y >18 and <50 Car, Boat, Cash < 10 0 No 5% of income 2 Lender A Product A.2 5000 30000 8.90% Renting, Boarding FT,PT, C C and PT > 12 M >18 and <65 Car, Boat < 25 < 3000 No 100 aud 2 Lender B Product B 5000 20000 25% Any Any 1 day >18 and <65 Cash, Car any < 10000 yes 1 aud any Product C.1 5000 50000 7.90% Owner, Mortgaged FT >1 M >18 and <65 Car < 5 0 yes 1 aud 1 Lender C Product C.2 3000 30000 9.90% Renting C and PT >12 M >18 and <65 Car > 5 and < 10< 5000 yes 1 aud 1 Product C.3 3000 20000 12% Boarding C and PT <12 M >18 and <65 Car < 25 < 10000 yes 1 aud 1 Product D.1 20000 100000 5.50% Owner, Mortgaged FT >5 Y >25 and <50 Car, Boat, Cash < 10 0 No 10% of income 2 Lender D Product D.2 10000 50000 7.50% Renting, Boarding FT <5 Y >25 and <50 Car, Boat Cash < 15 < 5000 yes 500 aud 1 Lender E Product E 5000 70000 20% Any any > 3 M >18 and <65 Cash, Car < 25 < 20000 yes 1 aud 3

John Smith Owner Full Time 4 years, 10 months 45 Car new 0 No 15% 3

Figure 4(i)a 415 LENDER: D INTEREST: 5.5% LOAN AMOUNT: $45000 3/9

PRODUCT: D.1 TERM: 60M REPAYMENT: $859/M LIKELIHOOD: *83% (*changed circumstances required – see details) 410 405 LENDER: A INTEREST: 6.9% LOAN AMOUNT: $45000 PRODUCT: A.1 TERM: 60M REPAYMENT: $889/M LIKELIHOOD: *80% (*changed circumstances required – see details)

LENDER: E INTEREST: 20% LOAN AMOUNT: $40000 PRODUCT: E TERM: 60M REPAYMENT: $1192/M LIKELIHOOD: 89%

LENDER: B INTEREST: 25% LOAN AMOUNT: $40000 PRODUCT: B TERM: 60M REPAYMENT: $1321/M LIKELIHOOD: 90%

Figure 4(i)b

Market Products Assessment Criteria Min Max Employment Type Unpaid Gambling Max Interest Ternure (Y= years, Asset Age Disposable Lender Product Loan Loan Property Type (Full Time, Casual, Age Asset Type Financial (last 6 Ongoing Rate M = months) (years) Income Amount Amount Part Time) Defaults months) Loans Product A.1 10000 100000 6.90% Owner, Mortgaged FT >2 Y >18 and <50 Car, Boat, Cash < 10 0 No 5% of income 2 Lender A Product A.2 5000 30000 8.90% Renting, Boarding FT,PT, C C and PT > 12 M >18 and <65 Car, Boat < 25 < 3000 No 100 aud 2 Lender B Product B 5000 20000 25% Any Any 1 day >18 and <65 Cash, Car any < 10000 yes 1 aud any Product C.1 5000 50000 7.90% Owner, Mortgaged FT >1 M >18 and <65 Car < 5 0 yes 1 aud 1 Lender C Product C.2 3000 30000 9.90% Renting C and PT >12 M >18 and <65 Car > 5 and < 10 < 5000 yes 1 aud 1 Product C.3 3000 20000 12% Boarding C and PT <12 M >18 and <65 Car < 25 < 10000 yes 1 aud 1 Product D.1 20000 100000 5.50% Owner, Mortgaged FT >5 Y >25 and <50 Car, Boat, Cash < 10 0 No 10% of income 2 Lender D Product D.2 10000 50000 7.50% Renting, Boarding FT, C <5 Y >25 and <50 Car, Boat Cash < 3 < 5000 yes 500 aud 1 Lender E Product E 5000 70000 20% Any any > 3 M >18 and <65 Cash, Car < 25 < 20000 yes 1 aud 3

Tom John Smith Renting Casual 2 years 25 Car 5 0 No 5% 15% 0 4/9

Figure 4(ii)a LENDER: D INTEREST: 7.5% LOAN AMOUNT: $15000 PRODUCT: D.2 TERM: 60M REPAYMENT: $301/M LIKELIHOOD: *78% (*changed asset age required – see details)

LENDER: A INTEREST: 8.9% LOAN AMOUNT: $15000 PRODUCT: A.2 TERM: 60M REPAYMENT: $310/M LIKELIHOOD: 81%

LENDER: C INTEREST: 9.9% LOAN AMOUNT: $15000 PRODUCT: C.2 TERM: 60M REPAYMENT: $318/M LIKELIHOOD: 83%

LENDER: B INTEREST: 25% LOAN AMOUNT: $15000 PRODUCT: B TERM: 60M REPAYMENT: $440/M LIKELIHOOD: 90%

Figure 4(ii)b

Market Products Assessment Criteria Min Max Employment Type Unpaid Gambling Max Interest Ternure (Y= years, Asset Age Disposable Lender Product Loan Loan Property Type (Full Time, Casual, Age Asset Type Financial (last 6 Ongoing Rate M = months) (years) Income Amount Amount Part Time) Defaults months) Loans Product A.1 10000 100000 6.90% Owner, Mortgaged FT >2 Y >18 and <50 Car, Boat, Cash < 10 0 No 5% of income 2 Lender A Product A.2 5000 30000 8.90% Renting, Boarding FT,PT, C C and PT > 12 M >18 and <65 Car, Boat < 25 < 3000 No 100 aud 2 Lender B Product B 5000 20000 25% Any Any 1 day >18 and <65 Cash, Car, Boat any < 10000 yes 1 aud any Product C.1 5000 50000 7.90% Owner, Mortgaged FT >1 M >18 and <65 Car < 5 0 yes 1 aud 1 Lender C Product C.2 3000 30000 9.90% Renting C and PT >12 M >18 and <65 Car, Boat > 5 and < 10 < 5000 yes 1 aud 1 Product C.3 3000 20000 12% Boarding C and PT <12 M >18 and <65 Car < 25 < 10000 yes 1 aud 1 Product D.1 20000 100000 5.50% Owner, Mortgaged FT >5 Y >25 and <50 Car, Boat, Cash < 10 0 No 10% of income 2 Lender D Product D.2 10000 50000 7.50% Renting, Boarding FT, C <5 Y >25 and <50 Car, Boat Cash < 10 < 5000 yes 500 aud 1 Lender E Product E 5000 70000 20% Any any > 3 M >18 and <65 Cash, Car < 25 < 20000 yes 1 aud 3

Rob John Smith Renting FT 2 years 24 Boat 5 0 Yes 15% 13% 0

Figure 4(iii)a LENDER: D INTEREST: 7.5% LOAN AMOUNT: $20000 5/9

PRODUCT: D.2 TERM: 60M REPAYMENT: $401/M LIKELIHOOD: *78% (*changed to age required – see details)

LENDER: A INTEREST: 8.9% LOAN AMOUNT: $20000 PRODUCT: A.2 TERM: 60M REPAYMENT: $414/M LIKELIHOOD: *81% (*changed circumstances required – see details)

LENDER: C INTEREST: 9.9% LOAN AMOUNT: $20000 PRODUCT: C.2 TERM: 60M REPAYMENT: $424/M LIKELIHOOD: 83%

LENDER: B INTEREST: 25% LOAN AMOUNT: $20000 PRODUCT: B TERM: 60M REPAYMENT: $587/M LIKELIHOOD: 90%

Figure 4(iii)b

Market Products Assessment Criteria Min Max Employment Type Unpaid Gambling Max Interest Ternure (Y= years, Asset Age Disposable Lender Product Loan Loan Property Type (Full Time, Casual, Age Asset Type Financial (last 6 Ongoing Rate M = months) (years) Income Amount Amount Part Time) Defaults months) Loans Product A.1 10000 100000 6.90% Owner, Mortgaged FT >2 Y >18 and <50 Car, Boat, Cash < 10 0 No 5% of income 2 Lender A Product A.2 5000 30000 8.90% Renting, Boarding FT,PT, C C and PT > 12 M >18 and <65 Car, Boat < 25 < 3000 No 100 aud 2 Lender B Product B 5000 20000 25% Any Any 1 day >18 and <65 Cash, Car, Boat any < 25000 yes 1 aud any Product C.1 5000 50000 7.90% Owner, Mortgaged FT >1 M >18 and <65 Car < 5 0 yes 1 aud 1 Lender C Product C.2 3000 30000 9.90% Renting C and PT >12 M >18 and <65 Car, Boat > 5 and < 10 < 5000 yes 1 aud 1 Product C.3 3000 20000 12% Boarding C and PT <12 M >18 and <65 Car < 25 < 10000 yes 1 aud 1 Product D.1 20000 100000 5.50% Owner, Mortgaged FT >5 Y >25 and <50 Car, Boat, Cash < 10 0 No 10% of income 2 Lender D Product D.2 10000 50000 7.50% Renting, Boarding FT, C <5 Y >25 and <50 Car, Boat Cash < 10 < 5000 yes 500 aud 1 Lender E Product E 5000 70000 20% Any any > 3 M >18 and <65 Cash, Car < 25 < 20000 yes 1 aud 3

Ben John Smith Owner PT 2 years 3940 Cash 0 21000 No 15% 0

Figure 4(iv)a LENDER: E INTEREST: 20% LOAN AMOUNT: $10000 6/9

PRODUCT: E TERM: 60M REPAYMENT: $265/M LIKELIHOOD: *89% (*changed circumstances required – see details)

LENDER: B INTEREST: 25% LOAN AMOUNT: $10000 PRODUCT: B TERM: 60M REPAYMENT: $294/M LIKELIHOOD: 90%

Figure 4(iv)b

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Figure 6