Computer implemented method and system for analysing financial data

Abstract

Disclosed is a computer implemented method for analysing financial data, the method comprising: receiving the financial data comprising a plurality of financial transactions, wherein each of the plurality of financial transactions comprises transaction details; generating a visual representation (200, 300, 400, 402, 500, 600) using the transaction details of the plurality of financial transactions, wherein the visual representation comprises a plurality of visual entities; and analysing the financial data for determining correctness of each of the plurality of financial transactions based on an association of each of the visual entities with a plurality of credit or debit accounts.

Description

[0001] COMPUTER. IMPLEMENTED METHOD AND SYSTEM FOR ANALYSING

[0002] FINANCIAL DATA

[0003] TECHNICAL FIELD

[0004] The present disclosure relates to computer implemented methods for analysing financial data and systems for analysing financial data.

[0005] BACKGROUND

[0006] Bookkeeping is a practice of keeping accurate and organized financial records of a given company or individual. It involves recording, classifying, and summarizing financial data in a systematic and organized manner. Understanding bookkeeping practice of the given company is a time-consuming pre-requisite to many accounting-related assurance services. During an audit process, audit teams analyse the given company's financial statements and accounting related company processes to identify and assess risks of material misstatement and generate audit evidence. Therefore, auditors need to obtain an understanding of the underlying accounting and bookkeeping system.

[0007] Conventionally, analysis of the financial data is performed manually using semi-automated tools. Auditors usually apply data analytics based on spreadsheets and pivot tables in order to understand the given company's general ledger and bookkeeping practice using the semi-automated tools. However, conventionally used tools, especially spreadsheet software, have some limitations, for example, in terms of handling huge amount of the financial data. Moreover, analysis of the booking patterns using the conventional tools is performed by manually filtering and / or pivoting the financial data, which is a tedious, time-consuming task and is prone to errors. These limitations further lead to inefficiencies when it comes to documentation requirements. Furthermore, it is crucial to ensure quality of the bookkeeping system by ensuring that the bookkeeping system of the given company complies with Generally Accepted Accounting Principles (GAAP). However, conventional techniques such as internal controls over financial reporting (ICFR) are sub-optimal in determining quality of the bookkeeping system.

[0008] Therefore, in light of the foregoing discussion, there exists a need to overcome the aforementioned drawbacks associated with conventional solutions available for analysing the financial data.

[0009] SUMMARY

[0010] The present disclosure seeks to provide a computer implemented method for (namely, a method of) analysing financial data. The present disclosure also seeks to provide a system for analysing financial data. An aim of the present disclosure is to provide a solution that overcomes at least partially the problems encountered in prior art.

[0011] In one aspect, the present disclosure provides a computer implemented method for analysing financial data, the method comprising : receiving the financial data that includes a plurality of financial transactions, wherein each of the plurality of financial transactions includes transaction details; generating a visual representation based on the transaction details, wherein the visual representation comprises a plurality of visual entities; and analysing the financial data for determining correctness of each of the plurality of financial transactions based on an association of each of the visual entities with a plurality of credit or debit accounts.

[0012] In another aspect, the present disclosure provides a system for analysing financial data, wherein the system comprises a processor configured to: receive the financial data that includes a plurality of financial transactions, wherein each of the plurality of financial transactions includes transaction details; generate a visual representation based on the transaction details, wherein the visual representation comprises a plurality of visual entities,; and analyse the financial data by determining correctness of each of the plurality of financial transactions based on an association of each of the visual entities with a plurality of credit or debit accounts.

[0013] Embodiments of the present disclosure substantially eliminate or at least partially address the aforementioned problems in the prior art, and enable direct, time-effective and error free analysis of the financial data. Additional aspects, advantages, features and objects of the present disclosure would be made apparent from the drawings and the detailed description of the illustrative embodiments construed in conjunction with the appended claims that follow.

[0014] It will be appreciated that features of the present disclosure are susceptible to being combined in various combinations without departing from the scope of the present disclosure as defined by the appended claims.

[0015] BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The summary above, as well as the following detailed description of illustrative embodiments, is better understood when read in conjunction with the appended drawings. For the purpose of illustrating the present disclosure, exemplary constructions of the disclosure are shown in the drawings. However, the present disclosure is not limited to specific methods and instrumentalities disclosed herein. Moreover, those skilled in the art will understand that the drawings are not to scale. Wherever possible, similar elements have been indicated by identical numbers. Embodiments of the present disclosure will now be described, by way of example only, with reference to the following diagrams wherein:

[0017] FIG. 1 is an illustration of steps of a computer implemented method for analysing financial data, in accordance with an embodiment of the present disclosure;

[0018] FIG. 2 is a visual representation, in accordance with an embodiment of the present disclosure;

[0019] FIG. 3 is a visual representation in which a thickness of a plurality of edges is different, in accordance with an embodiment of the present disclosure;

[0020] FIGs. 4A and 4B are visual representations in which one of a plurality of edges is selected, in accordance with different embodiments of the present disclosure;

[0021] FIG. 5 is a visual representation, in accordance with still another embodiment of the present disclosure;

[0022] FIG. 6 is a visual representation which is generated upon clustering an entirety of financial transactions based on account classes, in accordance with embodiment of the present disclosure; and

[0023] FIG. 7 is a block diagram of an architecture of a system for analysing financial data, in accordance with an embodiment of the present disclosure.

[0024] In the accompanying drawings, an underlined number is used to represent an item over which the underlined number is positioned or an item to which the underlined number is adjacent. A non-underlined number relates to an item identified by a line linking the non-underlined number to the item. When a number is non-underlined and accompanied by an associated arrow, the non-underlined number is used to identify a general item at which the arrow is pointing.

[0025] DETAILED DESCRIPTION OF EMBODIMENTS The following detailed description illustrates embodiments of the present disclosure and ways in which they may be implemented. Although some modes of carrying out the present disclosure have been disclosed, those skilled in the art would recognize that other embodiments for carrying out or practising the present disclosure are also possible.

[0026] In one aspect, the present disclosure provides a computer implemented method for analysing financial data, the method comprising : receiving the financial data that includes a plurality of financial transactions, wherein each of the plurality of financial transactions includes transaction details; generating a visual representation based on the transaction details, wherein the visual representation comprises a plurality of visual entities; and analysing the financial data by determining correctness of each of the plurality of financial transactions based on an association of each of the visual entities with a plurality of credit or debit accounts.

[0027] In another aspect, the present disclosure provides a system for analysing financial data, wherein the system comprises a processor configured to: receive the financial data that includes a plurality of financial transactions, wherein each of the plurality of financial transactions includes transaction details; generate a visual representation based on the transaction details, wherein the visual representation comprises a plurality of visual entities; and analyse the financial data by determining correctness of each of the plurality of financial transactions based on an association of each of the visual entities with a plurality of credit or debit accounts.

[0028] The present disclosure provides the computer implemented method for analysing the financial data and the system for analysing the financial data. Advantageously, the computer implemented method of the present disclosure is able to generate efficiently a visual representation of the plurality of financial transactions in a time-efficient manner, thereby leading to an accurate determination of correctness of each financial transaction of the plurality of financial transactions and significant classes of transactions (SCOTs) in the financial data. The correctness of each financial transaction may be determined based on determination of association of the financial transaction with multiple credit and debit accounts. The association may indicate ambiguities with transaction flow associated with account classes represented by the visual entities. Moreover, the visual representation of the financial transactions comprises all necessary structural information of the financial data which significantly reduces complexity associated with analysis of the financial data. This is because, the financial data is recorded in the visual representation in a form of complete accounting chains which are not required to be constructed manually through individual queries as in conventional audit procedures. Hence, the method significantly reduces the time required for analysis of the financial data, wherein the burden on computing resources required is also significantly reduced. Moreover, the system is inexpensive, reliable and may be implemented and used with ease.

[0029] The term "financial data" refers to information of the plurality of financial transactions associated with a given company or individual. The plurality of financial transactions include, but are not limited to: revenue, expenses, profits, assets, liabilities. The financial data is received from a bookkeeping system. The bookkeeping system is optionally a cloud-based accounting software tool or the financial data is optionally stored in a data repository of a computing device on which the computer implemented method is used. The financial data is extracted from the bookkeeping system in a tabular format or may be extracted from one of a journal entry of the plurality of financial transactions or a ledger entry of the plurality of financial transactions. Herein, each of the journal entry and the ledger entry may consist of at least one debit item and at least one credit item. The financial data comprising the plurality of financial transactions is obtained on at least one of a daily basis, a weekly basis, a monthly basis or a yearly basis.

[0030] The transaction details are associated with ledger entries comprising at least an account class, debit and credit account, a transaction date, a transaction amount and an unique transaction identifier. The "ledger entry" refers to a record of a financial transaction in a general ledger. The ledger entries may be made utilizing the double entry system, where debit and credit amounts of every corresponding account is consistently balance.

[0031] The "account class" refers to a group of accounts that share similar characteristics. Accounts are typically organized into classes based on their purpose or function within the given company. Examples of account classes include, trade receivables within the Asset account type, trade payables within the Liability account type, retained earnings within the Equity account class, sales within the Revenue account type, cost of material within the Expense account type. Asset related account classes may represent resources controlled by the company. Liability related account classes may represent debts and / or obligations of the company. Equity related account classes may represent residual interest of the company's owners. Revenue related account classes may represent income earned by the company. Expense related account classes may represent costs incurred by the company. Optionally, the transaction details are associated with journal entries of the plurality of financial transactions.

[0032] The "debit account" is an account that is debited when a financial transaction occurs. Examples of accounts usually debited within a journal entry include, asset accounts such as cash, accounts receivable and inventory, expense accounts such as cost of goods sold, salaries expense, and rent expense, dividend Payable account or similar. The "credit account" is an account that is credited when the financial transaction occurs. Examples of accounts usually credited within a journal entry include, liability accounts such as accounts payable, loans, mortgages, equity accounts such as common stock and retained earnings, revenue accounts such as sales, service revenue, and interest income, or similar.

[0033] The "transaction date" refers to the date on which the financial transaction, such as the purchase or sale of a product or service, takes place. The "transaction amount" refers to a monetary value of the financial transaction.

[0034] The unique transaction identifier (UTI) is a unique identifier assigned to the financial transaction. Optionally, the UTI is included to uniquely identify the financial transaction and to track the financial transaction. The UTI is typically generated by the system that processes the financial transaction, such as a point-of-sale terminal, online payment gateway, or similar. The UTI may include a combination of letters, numbers, and / or special characters. Examples of the UTI include a transaction number, reference number, order number, or similar. Advantageously, the technical benefit of using the aforesaid transaction details is that the visual representation is obtained accurately in a time effective manner by utilizing the aforesaid transaction details without overburdening the computing resources on which the method is implemented.

[0035] The term "visual representation" refers to a simplified representation of the transaction details of the plurality of financial transactions in a graphical format. The visual representation is obtained by reperforming the ledger entries. The term "reperform" refers to analysing the ledger entries comprising at least the account class, the debit and the credit account, the transaction date, the transaction amount and the UTI. Optionally, the visual representation is a directed graph that includes the plurality of visual entities. Each visual entity of the plurality of visual entities is a node of the directed graph or an edge that connects a pair of nodes of the directed graph. The node of the directed graph represents the account class, and the edge represents a transaction flow between debit and credit accounts associated with the pair of nodes. Thus, the plurality of visual entities comprises a plurality of nodes and a plurality of edges connecting the plurality of nodes. Each of the plurality of nodes represents the account class and each of the plurality of edges represents a transaction flow between debit and credit accounts associated with connected account classes. In this regard, the plurality of nodes represent account classes belonging to various account types. As an example, the graphical view may include ten nodes, herein, three nodes may represent account classes belonging to the liability account type, two nodes may represent account classes belonging to the expense account type, three nodes may represent account classes belonging to the revenue account type and two nodes may represent account classes belonging to the asset account type. Two nodes are joined with each other via at least one edge. Herein, the at least one edge connecting two nodes represents the transaction flow between two account classes, i.e., the debit and the credit account classes associated with connected account types. Optionally, the plurality of nodes represent accounts belonging to various account types.

[0036] The visual representation further depicts the debit and credit accounts for a selected account class and associated transaction flows. The term "transaction flow" refers to a way the plurality of financial transactions are recorded in the ledger entry which includes the debit and credit accounts affected and the amounts involved. In this regard, optionally, a direction of the at least one edge connecting the two nodes may follow a direction of debit to credit as recorded in the bookkeeping system. Optionally, a size of the plurality of edges represents one of: a number of transactions between a plurality of accounts represented as the plurality of nodes or transaction volume. Advantageously, the technical benefit of depicting the debit and credit accounts for a selected account class and associated transaction flows is that the visual representation is obtained accurately in a detailed manner and can be analysed by user in a significantly less time.

[0037] Optionally, the plurality of nodes represents a plurality of incoming account classes, a plurality of outgoing account classes and the accounts belonging to the plurality of incoming account classes and the plurality of outgoing account classes. The "incoming account class" refers to an account class that is credited when financial transactions occur. The "outgoing account class" refers to an account class that is debited when financial transactions occur. As an example, the revenue account class may be the outgoing account class when giving discount.

[0038] Optionally, a thickness of an edge of the directed graph is indicative of a number of transactions or a transaction volume associated with account classes, i.e., a pair of nodes of the directed graph that are connected by the edge. The thickness of the edge is adjusted based on selection of a filter amongst a set of filters. The selection of the filter may enable modification of the visual representation, i.e., the directed graph. In this regard, the "number of transactions" refers to a count of individual transactions that occur within a given period of time. The "transaction volume" refers to a total value of the transactions. For example, there may be ten transactions made, having value of $100 each, the number of transactions may be 10, and the transaction volume may be $1,000. Herein, more the number of transactions or a value of the transaction volume, more is the thickness of the plurality of edges. As an example, the transaction volume between a first account named cost of services and a second account named payables may be $100,000 and the transaction volume between the second account i.e., payables and a third account named cash and cash equivalents may be $200,000, therefore, the edge connecting the first account and the second account may be thinner and the edge connecting the second account and the third account may be thicker.

[0039] The thickness of the edges may be adjusted by selectors. The selectors include one of: a binning selector, a Lin selector or a Log selector.

[0040] The term "binning" refers to a process of grouping a set of numerical data into a smaller number of discrete "bins" or intervals. Binning may be useful for visualizing data and identifying patterns or trends that might not be immediately apparent in the financial data.

[0041] "Lin" is a continuous, strictly monotonous mathematical transformation described by the formula:

[0042] + thicknesmin

[0043] Where each value is normed to a range between thicknes_min and thickness_max. The Log function works in the same manner, but the old values are logarithmized with the base Euler number (2.718...) in advance.

[0044] Advantageously, the technical effect of adjusting the thickness of the plurality of edges is that the financial data can be understood and / or adjusted by a user with significant ease in a time-effective manner.

[0045] The financial transactions are analysed by selecting one or more filters. The financial transactions may be adjusted with: a materiality filter, a user type filter, a source filter, a company unit filter, a segment filter. The visual representation is analysed as it is generated i.e., without applying the one or more filters. Optionally, analysing the financial data comprises identifying significant classes of transactions (SCOTs) from the transaction details by applying a Materiality Threshold on the visual representation using the materiality filter. In this regard, the SCOTs refer to specific types of transactions that are considered to be important or material to the company's financial statements. Examples of the SCOTs include, but are not limited to, sales and revenue transactions, purchases and inventory transactions, cash and bank transactions, payroll and employee-related transactions, fixed assets transactions, loan and financing transactions. The term "Materiality Threshold" refers to a level of significance at which an item or disclosure is considered to be material to financial statements of the company, i.e., may influence the economic decisions of the stakeholders of the financial statements. The materiality threshold is determined as a predefined percentage of accounting variables. Examples of the accounting variables include, net income, revenue, total assets and total debt / equity, or similar. As an example, the materiality threshold may lie in a range of range of 5% to 10% of the net income. Herein, an amount less than 5% may be considered immaterial and an amount greater than 10% may be considered material. Optionally, the materiality threshold is set by selecting the materiality filter. Optionally, the user may enter the materiality threshold manually. Optionally, employing the materiality threshold results in the plurality of nodes and / or the plurality of edges in the visual representation depicting the plurality of financial transaction below the materiality threshold get filtered, leaving only those financial transactions which are above the materiality threshold. Advantageously, the technical effect of applying the materiality threshold is that analysis of the financial data becomes easy and may be performed in a timeeffective manner.

[0046] Analysing the financial data comprises determining correctness of each of the plurality of financial transactions based on an association of each of the visual entities with a plurality of credit or debit accounts. The visual entities associated with the plurality of credit or debit accounts are nodes of the directed graph. A financial transaction may be determined as correct if it is determined, from the visual representation (i.e., the directed graph), that the financial transaction is unambiguous or legitimate. The financial transaction may be associated with a pair of nodes that represent account classes and are connected by an edge that is represented by a transaction flow. Optionally, the method includes determining that each node of the pair of nodes of the directed graph, i.e., each visual entity in the visual representation, may be associated with a single debit account and a single credit account. The transaction flow represented by the edge connecting the pair of nodes corresponds to a verifiable transaction amount that may be exchanged between the debit account and the credit account. The correctness of the financial transaction of the plurality of financial transactions associated with the transaction flow may be determined based on the correspondence of the transaction flow with the verifiable transaction amount. Optionally, the financial transaction may be determined as being legitimate based on the determination of association of each node of the pair of nodes with the debit account and the credit account, which are involved in transfer of the verifiable transaction amount.

[0047] On the other hand, the financial transaction is determined as being incorrect or fraudulent if the financial transaction is determined to be ambiguous. In the visual representation, a transaction flow (i.e., a financial transaction) may be represented by an edge. The transaction flow may be identified as ambiguous if two account classes, which may be represented by a pair of nodes connected by the edge, is associated with at least two debit accounts and at least two credit accounts. Optionally, the method comprises determining that each node of a pair of nodes of the directed graph is associated with at least two debit accounts and at least two credit accounts. Based on the above determination, it may be detected that the transaction flow represented by the edge connecting the pair of nodes is ambiguous. The correctness of the financial transaction (i.e., the transaction flow) of the plurality of financial transactions associated with the transaction flow is determined based on the ambiguity associated with the transaction flow (i.e., edge).

[0048] Optionally, the financial transaction may be determined as being fraudulent based on the determination of association of each node of the pair of nodes with the at least two debit accounts and the at least two credit accounts. An ambiguous journal entry may include a plurality of debit accounts and a plurality of credit accounts, which prevent determination of an exact flow of transactions between the debit and credit accounts. For storage of such transactions involving the debit and credit accounts, especially when several business transactions are posted via one accounting record, compound accounting records may be utilized. In this regard, flow of transaction amounts between the at least two debit accounts and the at least two credit accounts may not be traced. In other words, a correlation between at least two debit and credit account may not be clearly assigned.

[0049] Optionally, the method is configured to analyse the financial data by determining a compliance of each of the plurality of financial transactions with Generally Accepted Accounting Principles (GAAP). The ambiguous transactions do not comply with the GAAP. The ambiguous transactions exist when multiple financial transactions are recorded within one entry of a journal or the general ledger. The ambiguous transactions may be included in the visual representation. The ambiguous transactions are filtered out of the visual representation for further analysis. Identification of the ambiguous transactions results in accurate identification of erroneous booking patters in the financial data without manually searching and filtering the financial data. Therefore, the financial data is analysed accurately, in a time-effective manner without overburdening the computing resources.

[0050] In an embodiment, detecting ambiguous transactions may involve identifying transactions involving multiple debit and credit accounts within a specified entry. Thereafter, correlation between the amounts associated with the multiple credit and debit accounts may be determined. The financial data may be parsed and entries with at least two debit and two credit accounts may be extracted. Subsequently, the amounts associated with the multiple credit and debit accounts may be compared to evaluate whether or not a clear correlation is susceptible to being established. This may enhance performance of statistical analyses or pattern recognition for identification of irregularities. In an embodiment, machine learning models may be leveraged to group transactions based on similarity in their characteristics such as account classes, transaction amounts, and other relevant features. Transactions that do not conform to GAAP may be flagged as ambiguous.

[0051] In some embodiments, a rule-based technique may be used in which a predefined criteria may be set for identifying ambiguity in transactions. For example, the algorithm may flag transactions where a sum of debit amounts does not match a sum of credit amounts within a given entry. Setting the predefined criteria may involve formulating and applying rules systematically across the received financial data.

[0052] Optionally, the method further comprises clustering the entirety of financial transactions based on the account classes and providing an identification number to clusters. The term "clustering" refers to grouping of the plurality of financial transactions. The plurality of financial transactions having similar characteristics may be grouped together. As an example, the financial transactions involving the same account classes may be clustered together. Clustering financial transactions is crucial for financial analysis and budgeting, as it allows to identify patterns and trends within the financial data.

[0053] The method further comprises depicting the clusters, in one of a tabular view and a graphical view, when selected by a user, for example an auditor. In this regard, clustering of the financial transactions results in generating a tabular view depicting the clusters. The tabular view lists accounts, account classes, cluster IDs, absolute amount (by account class), absolute amount (by account), number of journal entries, estimated journal entries, largest debit entry and largest credit entry.

[0054] Analysing the financial data comprises drawing conclusion on compliance of the financial data with Generally Accepted Accounting Principles (GAAP). In this regard, the term "GAAP" refers to a set of accounting standards and principles that companies use to prepare their financial statements. The specific GAAP used may vary by country. For example, in the United States, GAAP is set by the Financial Accounting Standards Board (FASB). The FASB issues accounting standards in the form of Statements of Financial Accounting Standards (SFAS) and Interpretations of the FASB Accounting Standards Codification (ASC). In the United Kingdom, GAAP is set by the Financial Reporting Council (FRC). The FRC issues financial reporting standards in the form of Financial Reporting Standards (FRSs) and Financial Reporting Guidance (FRGs). Compliance with the GAAP may be evaluated by analysing positions of the plurality of nodes and a number of the edges amongst the plurality of nodes. As an example, the visual representation is said to be compliant with the GAAP when a node indicating the cash account class is present in a centre of the visual representation. Advantageously, the technical effect of this visual representation is that compliance of the financial data with the GAAP may be determined easily and, in a time-effective manner without overburdening computing resources. Analysing the financial data comprises validating the financial data used in the visual representation by reconciling the transaction details from the modified summary with the financial data used as input. In this regard, correctness of the financial data as represented in the visual representation is measured by comparing the financial data as recorded in the bookkeeping system with the transaction details as depicted in the visual representation.

[0055] Optionally, the financial data is considered to be validated when a difference between transaction amounts of the accounts as recorded in the bookkeeping system and the transaction amounts as depicted by the plurality of edges connecting the plurality of nodes is zero. Validating the transaction details comprises identifying key performance indicators associated with the transaction details of the financial transactions. In this regard, the key performance indicators include at least one of: an absolute number of distinct journal entries, absolute cumulated value of bookings, fraction of unique journal entries, fraction of unique journal entries on account class level, fraction of ambiguous journal entries. The key performance indicators are identified to accurately determine correctness of the financial data as depicted by the visual representation.

[0056] The method allows selecting a given node or an edge from the entirety of nodes and edges, respectively, to present a tabular view corresponding to the selected node or edge. In this regard, the graphical view is beneficially user interactable. The graphical view allows a user to interact with the nodes and edges in some way. This may include features such as ability to zoom in or out, hover over the visualization to see more information or select at least one edge amongst the entirety of edges and at least one node amongst all nodes to highlight. As an example, upon hovering one node and one edge, the user may obtain information on a number of related ledger entries and the transaction volume. The tabular view depicts the transaction details of the financial transactions at an account class level, an account level or a journal entry level. Upon interacting with the graphical view, the tabular view is generated. As an example, the user may hover over one of the edges connecting a node to get information of different accounts associated in the financial transaction and the transaction volume. The tabular view may give information of the plurality of accounts, the financial transactions or similar.

[0057] The present disclosure also relates to the system for analysing financial data as described above. Various embodiments and variants disclosed above, with respect to the aforementioned first aspect, apply mutatis mutandis to the system for analysing financial data.

[0058] The term "processor" refers to a computational element that is operable to respond to and process instructions. Furthermore, the term "processor" may refer to one or more individual processors, processing devices and various elements associated with a processing device that may be shared by other processing devices. Such processors, processing devices and elements may be arranged in various architectures for responding to and executing processing steps.

[0059] Optionally, the transaction details are associated with an account class, a debit account, a credit account, a transaction date, a transaction amount, and a unique transaction identifier.

[0060] Optionally, the visual representation is a directed graph that includes the plurality of visual entities, wherein each visual entity of the plurality of visual entities is a node of the directed graph or an edge that connects a pair of nodes of the directed graph, and wherein the node of the directed graph represents the account class and the edge represents a transaction flow between debit and credit accounts associated with the pair of nodes. Optionally, the processor is configured to determine that each node of the pair of nodes of the directed graph is associated with at least two debit accounts and at least two credit accounts, and the transaction flow represented by the edge connecting the pair of nodes is ambiguous, wherein the correctness of a financial transaction of the plurality of financial transactions associated with the transaction flow is determined based on the ambiguity.

[0061] Optionally, the financial transaction is determined as being fraudulent based on the determination of association of each node of the pair of nodes with the at least two debit accounts and the at least two credit accounts .

[0062] Optionally, the processor is configured to determine that each node of the pair of nodes of the directed graph is associated with a debit account and a credit account, and the transaction flow represented by the edge connecting the pair of nodes corresponds to a verifiable transaction amount, wherein the correctness of a financial transaction of the plurality of financial transactions associated with the transaction flow is determined based on the correspondence of the transaction flow with the verifiable transaction amount.

[0063] Optionally, the financial transaction is determined as being legitimate based on the determination of association of each node of the pair of nodes with the debit account and the credit account.

[0064] Optionally, the processor is configured to analyse the financial data based on a determination of a compliance of each of the plurality of financial transactions with Generally Accepted Accounting Principles (GAAP).

[0065] Optionally, the visual representation further depicts the debit and credit accounts for account classes represented by the pair of nodes. DETAILED DESCRIPTION OF THE DRAWINGS

[0066] Referring to FIG. 1, there are shown therein steps of a computer implemented method for analysing financial data, in accordance with an embodiment of the present disclosure. At a step 102, financial data comprising a plurality of financial transactions is received, wherein each of the plurality of financial transactions comprises transaction details. At a step 104, a visual representation is generated using the transaction details of the plurality of financial transactions, wherein the visual representation comprises a plurality of visual entities, for depicting the transaction details of the plurality of financial transactions in a summarized manner, and one or more filters selectable to alter a summary depicted by the plurality of visual entities. At a step 106, the financial data is analysed by determining correctness of the transaction detail from the modified summary.

[0067] The aforementioned steps are only illustrative and other alternatives can also be provided where one or more steps are added, one or more steps are removed, or one or more steps are provided in a different sequence without departing from the scope of the claims herein.

[0068] Referring next to FIG. 2, there is shown a visual representation 200, in accordance with an embodiment of the present disclosure. The visual representation 200 comprises a plurality of visual entities. The plurality of visual entities comprises a plurality of nodes (depicted for example, as multiple circular nodes) and a plurality of edges (depicted for example, as arrows) connecting the plurality of nodes. The plurality of nodes represents the account class, and each of the plurality of edges represents a transaction flow between debit and credit accounts associated with connected account classes. As an example, the plurality of nodes may represent five account classes depicted with five different types of hatched nodes. Referring next to FIG. 3, there is shown a visual representation 300, in which thicknesses of a plurality of edges is different, in accordance with an embodiment of the present disclosure. The visual representation 300 comprises the plurality of edges (depicted for example as a plurality of arrows) connecting the plurality of nodes (depicted for example as circular nodes). The plurality of edges has varying thickness. As an example, edges connecting two nodes comprising a large transaction volume are represented by thick arrows and the edges connecting two nodes comprising a small transaction volume are represented by thin arrows.

[0069] Referring next to FIGs. 4A and 4B, there are shown visual representations 400 and 402, respectively, in which one of a plurality of edges is selected, in accordance with different embodiments of the present disclosure. In FIG. 4A, an edge (depicted for example as a dotted arrow) in the visual representation 400 is selected to present a tabular view corresponding to the plurality of financial transactions between accounts belonging to asset account class. In FIG. 4B, an edge (depicted for example as a dotted arrow) in the visual representation 402 is selected to present a tabular view corresponding to financial transaction between accounts belonging to asset account class and revenue account class.

[0070] In FIG. 5, there is shown a visual representation 500, in accordance with still another embodiment of the present disclosure. The visual representation 500 comprises the plurality of visual entities. The plurality of visual entities comprises a plurality of nodes representing a plurality of incoming account classes, a plurality of outgoing account classes and the accounts belonging to the plurality of incoming account classes and the plurality of outgoing account classes.

[0071] In FIG. 6, there is shown a visual representation 600 which is generated upon clustering entirety of financial transactions based on account classes, in accordance with embodiment of the present disclosure. As an example, the plurality of transactions between account classes within liability account type, asset account type, expense account type and revenue account type are shown to clustered with each other in the visual representation 600.

[0072] Referring to FIG. 7, there is shown a block diagram of architecture of a system 700 for analysing financial data, in accordance with an embodiment of the present disclosure. The system 700 comprises a processor 702.

[0073] FIGs. 2, 3, 4A, 4B, 5, 6 and 7 are merely examples, which should not unduly limit the scope of the claims herein. A person skilled in the art will recognize many variations, alternatives, and modifications of embodiments of the present disclosure.

[0074] Modifications to embodiments of the present disclosure described in the foregoing are possible without departing from the scope of the present disclosure as defined by the accompanying claims. Expressions such as "including", "comprising", "incorporating", "have", "is" used to describe and claim the present disclosure are intended to be construed in a nonexclusive manner, namely allowing for items, components or elements not explicitly described also to be present. Reference to the singular is also to be construed to relate to the plural.

Claims

CLAIMS1. A computer implemented method for analysing financial data, the method comprising: receiving the financial data that includes a plurality of financial transactions, wherein each of the plurality of financial transactions includes transaction details; generating a visual representation (200, 300, 400, 402, 500, 600) based on the transaction details, wherein the visual representation comprises a plurality of visual entities; and analysing the visual representation for determining correctness of each of the plurality of financial transactions based on an association of each of the visual entities with a plurality of credit or debit accounts.

2. The method according to claim 1, wherein the transaction details are associated with an account class, a debit account, a credit account, a transaction date, a transaction amount, and a unique transaction identifier.

3. The method according to claim 2, wherein the visual representation (200, 300, 400, 402, 500, 600) is a directed graph that includes the plurality of visual entities, wherein each visual entity of the plurality of visual entities is a node of the directed graph or an edge that connects a pair of nodes of the directed graph, and wherein the node of the directed graph represents the account class and the edge represents a transaction flow between debit and credit accounts associated with the pair of nodes.

4. The method according to claim 3, wherein a thickness of the edge is indicative of a number of transactions or a transaction volume associated with the pair or nodes connected by the edge.

5. The method according to claim 1, wherein analysing the financial data comprises identifying significant classes of transactions from thetransaction details by applying a materiality threshold on the visual representation.

6. The method according to claim 3, wherein the method further comprises determining that each node of the pair of nodes of the directed graph is associated with at least two debit accounts and at least two credit accounts, and the transaction flow represented by the edge connecting the pair of nodes is ambiguous, wherein the correctness of a financial transaction of the plurality of financial transactions associated with the transaction flow is determined based on the ambiguity of the transaction flow.

7. The method according to claim 6, wherein the financial transaction is determined as being fraudulent based on the determination of association of each node of the pair of nodes with the at least two debit accounts and the at least two credit accounts.

8. The method according to claim 3, wherein the method further comprises determining that each node of the pair of nodes of the directed graph is associated with a debit account and a credit account, and the transaction flow represented by the edge connecting the pair of nodes corresponds to a verifiable transaction amount, wherein the correctness of a financial transaction of the plurality of financial transactions associated with the transaction flow is determined based on the correspondence of the transaction flow with the verifiable transaction amount.

9. The method according to claim 8, wherein the financial transaction is determined as being legitimate based on the determination of association of each node of the pair of nodes with the debit account and the credit account.

10. The method according to claim 1, wherein analysing the financial data comprises determining a compliance of each of the plurality of financial transactions with Generally Accepted Accounting Principles (GAAP).

11. The method according to claim 3, wherein the visual representation (200, 300, 400, 402, 500, 600) further depicts the debit and credit accounts for account classes represented by the pair of nodes.

12. A system (700) for analysing financial data, wherein the system comprises a processor (702) configured to: receive the financial data that includes a plurality of financial transactions, wherein each of the plurality of financial transactions includes transaction details; generate a visual representation (200, 300, 400, 402, 500, 600) based on the transaction details, wherein the visual representation comprises a plurality of visual entities; and analyse the financial data to determine correctness of each of the plurality of financial transactions based on an association of each of the visual entities with a plurality of credit or debit accounts.

13. The system (700) according to claim 12, wherein the transaction details are associated with an account class, a debit account, a credit account, a transaction date, a transaction amount, and a unique transaction identifier.

14. The system (700) according to claim 13, wherein the visual representation (200, 300, 400, 402, 500, 600) is a directed graph that includes the plurality of visual entities, wherein each visual entity of the plurality of visual entities is a node of the directed graph or an edge that connects a pair of nodes of the directed graph, and wherein the node of the directed graph represents the account class and the edge representsa transaction flow between debit and credit accounts associated with the pair of nodes.

15. The system (700) according to claim 14, wherein the processor (702) is further configured to determine that each node of the pair of nodes of the directed graph is associated with at least two debit accounts and at least two credit accounts, and the transaction flow represented by the edge connecting the pair of nodes is ambiguous, wherein the correctness of a financial transaction of the plurality of financial transactions associated with the transaction flow is determined based on the ambiguity of the transaction flow.

16. The system (700) according to claim 15, wherein the financial transaction is determined as being fraudulent based on the determination of association of each node of the pair of nodes with the at least two debit accounts and the at least two credit accounts.

17. The system (700) according to claim 14, wherein the processor (702) is further configured to determine that each node of the pair of nodes of the directed graph is associated with a debit account and a credit account, and the transaction flow represented by the edge connecting the pair of nodes corresponds to a verifiable transaction amount, wherein the correctness of a financial transaction of the plurality of financial transactions associated with the transaction flow is determined based on the correspondence of the transaction flow with the verifiable transaction amount.

18. The system (700) according to claim 17, wherein the financial transaction is determined as being legitimate based on the determination of association of each node of the pair of nodes with the debit account and the credit account.

19. The system (700) according to claim 12, wherein the processor (702) is configured to analyse the financial data based on a determination of a compliance of each of the plurality of financial transactions with Generally Accepted Accounting Principles (GAAP).

20. The system (700) according to claim 14, wherein the visual representation (200, 300, 400, 402, 500, 600) further depicts the debit and credit accounts for account classes represented by the pair of nodes.

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