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Definition of Accrued Interest

Accrued interest (Acc. Int) refers to the amount of interest that has been accrued on investments or borrowings but the same has not been yet. It is treated as financial gain or obligation depending upon whether it is accrued on the investments made or the amount borrowed from debentures or bonds. It is recorded in the accounts to follow the accrual accounting system.

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Explanation

As per the accrual accounting system, the income that is incurred but not yet received or expense that is incurred but not yet paid is to be recorded in the accounts to reflect the accurate and fair view for the period mentioned. Acc. Int is the interest received on the investment, like fixed deposits, loans given, interest on bonds, etc., whereas Acc. Int can also be a liability, like interest on the amount borrowed from debentures or bonds. It follows the guidelines of generally accepted accounting principles like revenue recognition and the matching accounting principle. It refers to the accumulated interest due for receipt of payment but not received or paid, as the case may be. It is recorded at the end of the accounting period, i.e., on the balance sheet date, to reflect the accurate and fair view of the accounting.

Formula for Acc. Int

For borrowings like debentures and bonds, the formula for Acc. Int is as under:

Accrued Interest = Borrowed Amount * Yearly Interest Rate / 365 * Period for Which Interest Is Accrued.

The formula for Acc. Int on investment

Accrued Interest = Investment Amount * Yearly Interest Rate / 365 * Period for Which Interest Is Accrued.

Acc. Int as on the last day of the financial year or as on the balance sheet date is calculated for the period it is due. For example, the interest for each quarter will be received on the 10th of the next quarter. So, the interest of the last quarter, which accrued on 31st March, will be accepted on 10th April. Hence Acc. Int for the previous quarter, i.e., Jan – March, is due and will be recorded in the accounts as Acc. Int.

Examples

Different examples are mentioned below:

Example #1

The company borrows $ 70,000 from the bank, and the annual interest rate is 5%. The amount was borrowed on 15-12-2024, where the interest payment is monthly. The financial year of the company closes on 31st December. Calculate the Acc. Int to be recognized in the books of accounts at the closing of the financial year?

Solution:

The period from 15th December to 31st December = 16 days

Accrued Interest = Borrowed Amount * Yearly Interest Rate / 365 * Period for Which Interest is Accrued

Accrued Interest = $70,000 * 5% / 365 * 16

Accrued Interest = $70,000 * 0.05 / 365 * 16

Accrued Interest = $153 (appx)

Particulars

Value

Borrowed Amount  $70,000

Yearly Interest rate 5%

Number of days in a year 365

Period for which interest is accrued 16

Accrued Interest  $153.42

Example #2

Company A Ltd deposits in fixed deposits amounting to $ 50,000. The interest rate on fixed deposits is 6%. A fixed deposit was made on 01-02-2024 and matured on 31-03-2024. The company closes the books on 31st March every year. Calculate the Acc. Int on the fixed deposit?

Solution:

Acc. Int is calculated as

Accrued Interest = Investment Amount * Yearly Interest Rate / 365 * Period for Which Interest is Accrued.

Acc. Int = $50,000 * 6% / 365 * 59 days

Acc. Int = $50,000 * 0.06 / 365 * 59

Acc. Int = $485 (Appx)

Particulars

Value

Borrowed Amount  $50,000

Yearly Interest rate 6%

Number of days in a year 365

Period for which interest is accrued 59

Acc. Int  $484.93

Accrued Interest on Bonds

A bond is a debt obligation for the borrower and is an asset for the lender. Hence the lender is entitled to receive the interest on bonds. The interest on bonds is generally known as coupons and is paid yearly, half-yearly, quarterly, or as decided at the bond issuance. The bond is a negotiable instrument, i.e., it can be transferred from one person to another person very quickly, but there is a problem concerning the interest at the time of sale, i.e., when the bond is transferred, the interest accrued can also be paid to the seller by the buyer of the bonds. So, interest is calculated at the time of sale of such a bond. For example, there is a bond in which interest accrued from April to September will be received in October by the buyer. The seller wants to sell the bond in July. Hence apart from the bond’s market price, the buyer also has to pay the interest for three months to the seller, which he will receive from the organization in October.

Accrued Interest vs Regular Interest

Acc. Int is the interest that gets due but has not been paid yet, whereas regular interest is the interest that is paid or received and recorded in the books of accounts.

Acc. Int is recognized in the accounts before the payment is made, whereas regular interest is recorded only after the receipt.

The payment or receipt cycle of Acc. Int is constant and decided before the investment or borrowing, and it cannot be changed. In contrast, the payment or receipt cycle of common interest is flexible and can be changed at any time per mutual decision.

Acc. Int is recorded per the accrual accounting system, i.e., on a due basis, whereas the regular interest is recorded on a receipt basis.

Conclusion

Acc. Int is the interest that gets due or accumulated but is not received or paid. Example of Acc. Int includes interest on fixed deposits, interest on bonds, interest on debentures, etc. The payment or receipt cycle of Acc. Int is pre-decided, and it is constant. Bond being the negotiable instrument, can be transferred at any time, so in that case, the seller is entitled to receive the interest apart from sale proceeds. Acc. Int is different from a regular interest in terms of flexibility as the receipt or payment cycle of regular interest is customized and changed with mutual consultation. Acc. Int is recorded as per the matching concept and as per the accrual system of accounting. The calculation of Acc. Int is to be done up to the last day of the financial year.

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Learn Various Tools Of Burp Suite With Explanation

Introduction to Burp Suite

Burp, also known as Burp Suite, is a collection of tools for web application penetration testing. The Portswigger company creates it. Burp Suite aims to be an all-in-one toolkit, and its features can be increased by installing BApps, i.e. its add-ons. Professional web application security researchers and bug bounty hunters use it the most. It is a better choice than free alternatives such as OWASP ZAP because of its ease of use.

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Tools of Burp Suite

Burp Suite offers various tools, which are given as follows:

1. Spider

It’s a web crawler or spider that maps the target web application. The mapping aims to create a list of endpoints that can be examined for functionality and potential vulnerabilities. The spidering is useful because the more endpoints you collect during your recon phase, the more attack surfaces you’ll have during your actual research.

2. Proxy

Burp Suite features an intercepting proxy that helps the user access and change request and response contents while in transit. It also allows the user to submit the under-monitored request/response to another appropriate Burp Suite tool, eliminating the need for copy-paste. The proxy server may be programmed to use a particular loop-back address and port. Unique forms of request-response pairs may be filtered out using the proxy.

3. Intruder

iii. On the web app, rate limiting is being tested and attacked.

4. Repeater

Repeater allows a person to submit requests continuously when making manual changes. It is employed for the following purposes:

i. Checking to see how the user-supplied values are being verified.

ii. How well is it being achieved user-supplied attributes are being verified?

iv. What happens if the server encounters unpredictable values?

v. Is the server doing input sanitation?

vi. How well the server filter and checks the data provided by the user?

vii. Whose validating system does the server employ?

viii. Which of the cookies on a computer is the session cookie?

5. Sequencer

The sequencer is an entropy checker that ensures that tokens created by the webserver are random. anti-CSRF and Cookies tokens are examples of these tokens, which are often used for authentication of sensitive operations. These tokens should preferably be generated in a truly random way, with the likelihood of each potential character occurring at each position shared uniformly. This can be accomplished both in terms of bits and characters. An entropy analyzer verifies that this concept is valid. It functions like this: the tokens are considered to be random at first. The tokens are then placed into a series of checks to see whether they follow those requirements. A significant point is a minimum value of probability that a token would exhibit for an attribute, such that if the token’s characteristics probability is less than the significance level, the argument that the token is random is dismissed. This method can be used to identify and count vulnerable tokens.

6. Decoder 7. Extender

External modules can be implemented into Burp Suite to expand the tool suite’s capability. external modules are named as BApps. This function in the same manner as browser extensions do. In the Extender pane, these can be accessed, updated, mounted, and uninstalled. Some of them can be used for the free community version, while others include the paid technical version.

8. Scanner

The group version does not have a scanner. It automatically searches the website for several typical vulnerabilities and lists them, along with details about the level of trust in each discovery and the difficulty of exploitation. It’s revised on a daily basis to include recent and lesser-known flaws.

Conclusion

In this article, we have seen what Burp Suite and its various modules is. I hope you will find this article helpful.

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Functional Preview And Examples Of Python Reduce

Introduction to Python Reduce

Reduce() function returns a map object. A function that is to be passed to all the elements of the list is applied in its arguments. Lambda functions are used to make the code more readable and other operator functions. In this topic, we are going to learn about Python Reduce.

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Syntax of Python Reduce reduce (function, iterable)

Function obligation to be executed for each item.

Iterable is a sequence, a collection. It returns an iterator object as many iterables as one desire can be sent.

Function consists of one parameter for each iterable.

Engineers today, are predominantly busy working and dealing with lists. Let’s say:

You work in Wall Street- you are analyzing lists of stock prices.

Writing software for a drone delivery service- you’re processing lists of orders.

You work at friendface- you’re profiling lists of users with your mountain of personal data.

A lot of code is spent analyzing, filtering, and combining the items in a list.

Map, Filter and Reduce functions are built-in high order functions in Python.

Often, using a generator expression over a reduced function is preferred. User preference is involved. Defining a function inline using lambda, the preferential expression is the generator and will be clean over the reduce function.

Functions usage in general – Python:

What are Lambda Expressions?

Lambda functions are quite useful when you require a short, throwaway anonymous function. Simplicity is that it can be used only once. Applied explicitly near the sorting and filtering of the data.

lambda arguments: expression

Just like functions, it is perfectly acceptable to have anonymous functions with no inputs.

Next, type a colon. Then finally you enter a single expression. This expression is a return value. Multi-line functionality or more than a single line is not possible using such functions.

A Functional Preview Of Reduce Data: a1, a2, a3,..,an Function: f reduce (f, data) :

Suppose you have a list/tuple /other iterable collection of data, (consider Data: a1, a2, a3…..,an. as it for time being)

Each piece of data is applied with the function: f.

With the reduce function(reduce (f, Data):), you first specify the function and then the data to iterate over.

The reduce function will iterate over the collection (f(a1), f(a2,),…., f(an)) of f applied to each piece of data.

The result is obtained by picking the first two elements of a sequence.

The previously attained result is applied with the same function and the number next to the second element, the result is cached.

Till container is left with no more elements, the process continues.

The console returns the end result.

Examples of Python Reduce

First consider importing the tool functools and reducing function from within it.

Now, for performing the multiplication, give a list of desired values.

Lambda function is used as discussed above, why and how it is used.

If you simply print the multiplier, it returns the reduce object.

We need to Convert the reduce object into a return result of which we are looking for.

from functools import reduce #Multiplication of all the numbers in the list data = [2, 3, 5, 7, 9, 11, 17, 19, 23, 29] multiplier = lambda x, y : x*y print(reduce (multiplier, data))

Output:

import functools def multiply(a,b): print("a=",a," b=",b) return a*b factorial=functools.reduce(multiply, range(1, 6)) print ('Factorial of 5 is: ', factorial)

Output:

3. Sum of given numbers is performed in the below example using reduce function.

from functools import reduce def do_sum(x1, x2): return x1 + x2 print(reduce(do_sum, [1, 2, 3, 4]))

Output: 

Conclusion

The map, filter and reduce functions greatly simplifies the process of working with lists and other iterable collections of data, In fact, if you use lambda expressions, your work can often be done in a single line. After you master these functions, you will realize Python should be a comedian because it is full of one-liners.

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Working And Examples Of Numpy Zeros_Like Function

Introduction to NumPy zeros_like

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Syntax

The syntax for NumPy zeros_like function in Python is as follows:

numpy.zeros_like(arrayname, datatype, memoryorder, subok)

where arrayname is the name of the array whose values must be replaced with zeros without a change in the size and shape of the array,

The data type is the data type of the values stored in the array. The default datatype for the given values in the array is float. This parameter is optional.

Memoryorder represents the order in the memory. The subok represents a Boolean value that is true if the array returned by using zeros like function is a subclass of the input array and false if the returned array is the same as the original array. This parameter is optional.

Working of NumPy zeros_like function

Whenever we have an array whose values must be replaced with all zeroes and the array size and shape must be retained as the original array, we make use of a function called zeros like function in numpy.

The zeros like functions take four parameters arrayname, datatype, memoryorder, and subok, among which the datatype and subok parameters are optional.

datatype represents the data type of the value stored in the array whose name is represented by the first parameter arrayname.

memoryorder represents the order in the memory.

subok represents a Boolean value which is true if the array returned by using zeros like function is a subclass of the input array and false if the returned array is the same as the original array.

Examples of NumPy zeros_like

Different examples are mentioned below:

Example #1

Python program to demonstrate NumPy zeros like function to create an array using array function in numpy and then using zeros like function to replace the elements of the array with zeros:

#importing the package numpy import numpy as n #Creating an array by making use of array function in NumPy and storing it in a variable called orgarray orgarray = n.array([[1,2],[3,4]]) #Displaying the elements of orgarray followed by one line space by making use of n print ("The elements of the given array are:") print (orgarray) print ("n") #using zeros like function of NumPy and passing the created array as the parameter to that function to replace all the elements of the array with zeros and store it in a variable called zerosarray zerosarray = n.zeros_like(orgarray, float) #Displaying the array consisting of all zero elements print ("The array with all its elements zero after using zeros like function is as follow:") print (zerosarray)

Output:

In the above program, we are importing the package numpy, which allows us to make use of the functions array and zeros_like. Then we are creating an array called orgarray by making use of the array function in numpy. Then the elements of the array orgarray are displayed on the screen. Then we are making using zeros_like function, and the newly created array orgarray is passed as a parameter to the function to convert all the elements of the array to zeros without changing the size and shape of the array, and the resulting array is stored in a variable called zerosarray. Finally, the elements of the zerosarray are displayed on the screen.

Example #2

Python program to demonstrate NumPy zeros like function to create an array using array function in numpy and then using zeros like function to replace the elements of the array with zeros:

#importing the package numpy import numpy as n #Creating an array by making use of array function in NumPy and storing it in a variable called orgarray orgarray = n.array([[5,6],[7,8]]) #Displaying the elements of orgarray followed by one line space by making use of n print ("The elements of the given array are:") print (orgarray) print ("n") #using zeros like function of NumPy and passing the created array as the parameter to that function to replace all the elements of the array with zeros and store it in a variable called zerosarray zerosarray = n.zeros_like(orgarray, int) #Displaying the array consisting of all zero elements print ("The array with all its elements zero after using zeros like function is as follow:") print (zerosarray)

Output:

In the above program, we are importing the package numpy, which allows us to make use of the functions array and zeros_like. Then we are creating an array called orgarray by making use of the array function in numpy. Then the elements of the array orgarray are displayed on the screen. Then we are making using the zeros_like function. The newly created array orgarray is passed as a parameter to the function to convert all the elements of the array to zeros without changing the size and shape of the array. The datatype int is also passed as the parameter, which displays the zeros in the resulting array as integer values. Then the resulting array is stored in a variable called zerosarray. Finally, the elements of zerosarray are displayed on the screen.

Conclusion

In this tutorial, we understand the concept of NumPy zeros like function in Python through definition, the syntax of zeros like function, and the working of zeros like functions through programming examples and their outputs.

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Introduction, Syntax, And Different Examples Of Matlab Fit

Introduction to Matlab fit

MATLAB fit method can be used to fit a curve or a surface to a data set. Fitting a curve to data is a common technique used in Artificial intelligence and Machine learning models to predict the values of various attributes.

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For example, if we compare the weight of an item like rice with its price; ideally, it should increase linearly (Price will increase as the weight of rice will increase). If we fit a curve to this data of weight and price, we will get mostly a linear curve. Now someone looking at this linear curve can easily interpret the relation between the 2 attributes (weight and price in our example), without looking at the data.

Syntax:

fitobject = fit (a, b, fitType) is used to fit a curve to the data represented by the attributes ‘a’ and ‘b’. The type of model or curve to be fit is given by the argument ‘fitType’

Various values which the argument ‘fitType’ can take are given in the table below:

Model Name Description

‘poly1’

A polynomial curve with linear nature

‘poly11’

A polynomial surface with linear nature

‘poly2’

A polynomial curve with quadratic nature

‘linearinterp’

Linear piecewise interpolation

‘cubicinterp’

Cubic piecewise interpolation

‘smoothingspline’

A curve of the nature smoothing spline

Table 1

Let us now understand how to fit a curve or a surface to data in MATLAB:

We will need some data to which we will fit the curve, for our examples, we will use some inbuilt data sets provided by MATLAB like ‘carsmall’ and ‘census’.

Examples of Matlab fit

Let us discuss examples of Matlab fit.

Example #1

In this example, we will use the ‘carsmall’ data provided by MATLAB. The data is of various attributes of cars manufactured over the years 1970, 1976, and 1982. It has attributes like ‘Acceleration’, ‘Cylinders’, ‘Horsepower’ etc. which represent various features of a car. We will load this data to our workspace and will fit a curve to its attributes ‘Acceleration’ and ‘Displacement’. The steps to be followed for this example are:

Load the ‘carsmall’ data to the workspace

View the file loaded above to understand its attributes

Use the ‘fit’ function to fit a curve to the loaded data

Plot the model created in above step

1. load carsmall

[Using the ‘load’ command to load the ‘carsmall’ data set to our workspace]

[Using the ‘load’ command to load the ‘carsmall’ data set to our workspace]

2. whos -file carsmall

[Using ‘whos’ command to view the file loaded above]

[Using ‘whos’ command to view the file loaded above]

3. C = fit(Acceleration, Displacement, ‘poly2’)

[Using the ‘fit’ command to fit a curve to the data. The first 2 parameters represent the attributes to which we want to fit the curve and the 3rd parameter represents the type of curve which we want to fit (please refer to Table 1 for this)]

[Using the ‘fit’ command to fit a curve to the data. The first 2 parameters represent the attributes to which we want to fit the curve and the 3parameter represents the type of curve which we want to fit (please refer to Table 1 for this)]

4. plot(C, Acceleration, Displacement)

[Using ‘plot’ command to plot the model created in above step]

[Using ‘plot’ command to plot the model created in above step]

This is how our input and output will look like in MATLAB command window:

Input 1:

Loading the carsmall data set:

Input 2:

Fitting the curve to the data:

Input 3:

Plotting the model created above:

Output 1:

Output 2:

Output 3:

As we can see in Output 3, we have obtained a curve that fits our data. Output 1 and Output 2 represent the data attributes and the model respectively.

In the same example, we can also fit a different type of curve as per our requirement. Let us try to fit ‘smoothingspline’ curve to the above data.

The code will be similar as in the above example with a change in line 3

Code:

 1. load carsmall

[Using the ‘load’ command to load the ‘carsmall’ file to our workspace]

[Using the ‘load’ command to load the ‘carsmall’ file to our workspace]

2. whos -file carsmall

[Using ‘whos’ command to view the file loaded above]

[Using ‘whos’ command to view the file loaded above]

 3. C = fit(Acceleration, Displacement, ‘smoothingspline’)

[Please note that the 3rd argument is now ‘smoothingspline’]

[Please note that the 3argument is now ‘smoothingspline’]

4. plot(C, Acceleration, Displacement)

[Using ‘plot’ command to plot the model created in above step]

Input 1:

Loading the carsmall data set:

Input 2:

Fitting the curve to the data:

Input 3:

Plotting the model created above:

Output 1:

Output 2:

Output 3:

As we can see in Output 3, we have obtained a smoothing spline curve that fits our data.

Example #2

In this example, we will use the ‘census’ data provided by MATLAB. The data is of the US and gives the population of the country in a particular year. It has 2 attributes ‘cdate’ and ‘pop’ representing ‘census date’ and ‘population’. We will load this data to our workspace and will fit a curve to it. The steps to be followed for this example are:

Load the census data to the workspace

View the file loaded above to understand its attributes

Use the ‘fit’ function to fit a curve to the loaded data

Plot the model created in above step

Code:

load census

[Using the ‘load’ command to load the census file to our workspace]

[Using ‘whos’ command to view the file loaded above]

[Using ‘whos’ command to view the file loaded above]

C = fit(cdate, pop, 'poly2')

[Using the ‘fit’ command to fit a curve to the data. The first 2 parameters represent the attributes to which we want to fit the curve and the 3rd parameter represents the type of curve which we want to fit (please refer to Table 1 for this)]

[Using the ‘fit’ command to fit a curve to the data. The first 2 parameters represent the attributes to which we want to fit the curve and the 3parameter represents the type of curve which we want to fit (please refer to Table 1 for this)]

plot(C, cdate, pop)

[Using ‘plot’ command to plot the model created in above step]

[Using ‘plot’ command to plot the model created in above step]

This is how our input and output will look like in MATLAB command window:

Input 1:

Loading the census data set:

Input 2:

Fitting the curve to the data:

Input 3:

Plotting the model created above:

Output 1:

Output 2:

Output 3:

As we can see in Output 3, we have obtained a curve that fits our data. Output 1 and Output 2 represent the data attributes and the model respectively.

Conclusion

We use ‘fit’ function in MATLAB to fit a curve to our data set

Fitting a curve is very useful technique used in Machine learning

We can control the type of curve that we want to fit to our data by using the ‘fitType’ argument.

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Account Payable Vs Accrued Expense

Difference Between Account Payable vs Accrued Expense

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Head To Head Comparison Between Account Payable vs Accrued Expense (Infographics)

Below is the top 5 difference between Account Payable vs Accrued Expense:

Key Differences Between Account Payable vs Accrued Expense

Account payables are basic financial obligations of a business classified as current liabilities. They generally do not involve any written agreement of a payment to be made within a specified period. On the other hand, accrued expenses are already accrued by the company and have been mentioned or written in the books of accounts. Still, the company has not yet incurred the cash outflow of that respective expense item as in the case of accounts payable.

Accounts payables are generally due to suppliers or subcontractors; therefore, there is no formal interest on the instrument and no fixed obligation to pay. On the other hand, the accrued expense comes in the category where the supplier or the vendor has not raised any invoice or there is no fixed payment cycle due to the supplier as the payment has not yet been furnished.

Account payables are always a short-term obligation and are a current liability; On the other hand, an accrued expense is only an estimate of how much money the company owes to its suppliers or vendors; there is no fixed credit payment cycle related to it. Accrued expense works on the accrual method of accounting; as a result, the accrued expense is likely to be different from the actual invoice, which is to be paid to the vendor.

Accounts payables are an informal channel due to the vendors and suppliers, which makes the payment more flexible and without formal or written agreement. On the contrary, an accrued expense can take on formal or informal forms. It describes as a cost for which the client has not issued an invoice or for which no invoice has been received. Whereas accounts payable, the company has already received the bill.

Account Payable vs Accrued Expense Comparison Table

Let’s look at the top 5 Comparison between Account Payable vs Accrued Expenses

Accounts Payable

Accrued Expense

Accounts payable is the total debt the company has to pay its creditors for goods or services bought on credit. Accrued expenses represent the total liability for goods and services the company has received but has not yet been billed for.

Account Payable is a balance sheet item. Accrued Expense appears as an item on the income statement but can also be presented on the company’s balance sheet.

Accounts payable is not an estimate as it is the actual liability that needs to be paid off. An accrued expense is merely an estimate as the company needs to determine the amount of cash outflow required for that specific cost to be incurred.

Supplier Invoice

Raw Material

Examples of Accrued Expenses are:

Interest on debt

Salaries to be paid to employees

A company recognizes accounts payable every day as every day the company purchases goods on credit. Accrued expenses are not an item for which the company recognizes daily expenses.

Conclusion

Accounting recognition is an important aspect of every company, and each company should follow the various accounting principles which are globally recognized, such as the US Generally Accepted Accounting Principles and International Financial Reporting Standards. Companies should prepare books by these two methods, whichever applies to them. Furthermore, an external auditor should check and thoroughly audit the books and provide a sign-off at the end of the audit. It enhances the credibility of the company and reassures its shareholders.

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