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Introduction to CakePHP Log

CakePHP frameworks provide different types of functionality to the developer and are open-source tools. For example, logging is very important from the development perspective; using a log can easily find the problem in terms of errors, exceptions, different user activities, user actions during the operation, and any background activities. Normally implementation of logging is a very easy and time-saving activity. In CakePHP, we have a log() function to log the different activities, errors, and exceptions. For Log implementation, we need to configure the different parameters per our requirements.

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How to Create CakePHP log?

Now let’s see how we can create log-in CakePHP as follows.

Log stream overseers can be essential for your application or part of modules. On the off chance that, for instance, you had an information base lumberjack called DatabaseLog as a component of your application; it would be set in

application/Lib/Log/Engine/DatabaseLog.php.

Assuming you had an information base lumberjack as a module component, it would be put in application/Plugin/LoggingPack/Lib/Log/Engine/DatabaseLog.php. When arranged, CakeLog will endeavor to stack Configuring log streams, which is finished by calling CakeLog::config(). Arranging our DatabaseLog would resemble:

App::uses('BaseLog', 'Log/Engine'); class DatabaseLog extends BaseLog { public function __construct($options = array()) { parent::__construct($options); } public function write($specified type, $required message) { } }

It consequently handles the degree and type contention projecting. Finally, it executes the config() technique expected to make perused logging work.

Every logger’s compose technique should accept two boundaries: $type and $message (in a specific order). $type is the string sort of the logged message; basic beliefs are blunder, cautioning, information, and troubleshooting. Moreover, you can characterize your kinds by utilizing them when you call CakeLog::write.

How to Configure Log in CakePHP?

Now let’s see how we can configure log-in CakePHP as follows.

First, we need to configure the chúng tôi file; we can configure the log section with different options.

], ], },

Explanation

In the above code, we can see by default; we have two log levels: an error and debug that we already configured, and it handles the different levels of the message. So basically, CakePHP supports the different levels of logging as follows.

Emergency: It is used to show the system is unusable.

Alert: It shows what action we need to take immediately.

Critical: It is used for critical conditions.

Error: It is used to show error conditions.

Warning: It is used to show warning conditions.

Notice: It is used to show the significant condition of execution.

Info: It is used to show informational messages as per requirement.

Debug: It is used to show debug level of all messages.

CakePHP Log file

Now let’s see what the log file in CakePHP is as follows.

We can write in a Log record in two different ways.

Syntax:

Parameters:

The seriousness level of the message being composed. The worth should be a whole number or string matching a known level.

Message content to log.

Extra information to be utilized for logging the message. The unique extension key can be passed to be utilized for additional separating of the log motors. If a string or a mathematical record exhibit is passed, it will be treated as the degree key. See CakeLogLog::config() for more data on logging degrees.

It Returns: boolean

Description: Composes the given message and type to all of the designed log connectors. Arranged connectors are passed both the $level and $message factors. $level is one of the accompanying strings/values. The second is to utilize the log() easy route work accessible on any utilizing the LogTrait Calling log() will inside call Log::write().

CakePHP Log Example

Now let’s see an example of a log file as follows.

<?php use CakeHttpMiddlewareCsrfProtectionMiddleware; use CakeRoutingRouteDashedRoute; use CakeRoutingRouteBuilder; ])); });

Now we need to create chúng tôi and write the following code as follows.

<?php namespace AppController; use AppControllerAppController; use CakeLogLog; class LogexsController extends AppController{ public function index(){ /*First way to write log file.*/ Log::write('debug', "Something went wrong during execution."); /* Second way to write log file.*/ } }

Create an chúng tôi file under the view directory and write the following code.

Something went wrong during execution. Need to check log filedebug.log

Now we need to execute this file in localhost, and after execution, we will do some output that we illustrated by using the following screenshot.

After execution debug log was added to the chúng tôi file, as shown in the following screenshot.

Conclusion

We hope from this article you learn more about the CakePHP log. From the above article, we have taken in the essential idea of the CakePHP log and see the representation and example of the CakePHP log. Furthermore, this article taught us how and when to use the CakePHP log.

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How To Implement Queue In Swift With Example

Introduction to Swift Queue

The Swift queue is the same as any other programming language. The queue is a data structure used to store element; in the queue, we can store data from one end and delete it using another end. Queue works and follows FIFO, which means first in, first out. We have so many examples where we do this thing like when we buy tickets from any station etc. Queue in swift support operation, which is used to handle the data or elements.

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As we know, queue in swift is used to store the data. To store any data, we require predefined methods from the queue and to delete data, there are some methods from the queue, but first, we will see the syntax of how we can define a queue in swift while doing programming.

var variable_name:[Type] = []

As you can see in the above line of syntax we it is very simple to define a queue just like any other collection. First, we have to give the variable name followed by the type it is going to store, and we can initialize it if we want.

Example:

Code:

var myqueue :[Int] = []

Here we will see how we can add elements and remove elements from the queue in swift.

How to Implement Queue in Swift?

As we already know, that queue is a data structure that is used to store elements. To perform any operation on queue, it provides us with a different method for this. It is predefined, or we can say in build in swift, so we do not require to include any library for this. We can perform different operations like an insertion in the queue and delete an element from the queue.

Here we will see both these methods available in a queue in detail.

1. Enqueue

This is the method available in the queue. This method is used to add elements to the queue. We can simply call this method on the queue or array we created.

syntax:

var myqueue : [Int] = [] myqueue.append(your element here ) 2. Dequeue / Remove

This method is used to remove an element from the queue. This is also a predefined method available in a queue data structure of swift.

Syntax:

var myqueue : [Int] = [] myqueue.remove(your element here )

As you can see in the above syntax for the dequeue method, we are calling this method on the queue variable we have created in the first line of code. We can remove as many elements as we want to the queue variable. To perform the dequeue operation, we have to call the remove() method on it.

Now we will see one example to use both the method in the program to know it internal working in detail.

Example:

Code:

import Foundation import Glibc import Foundation struct Queue{ var myqueue:[Int] = [] mutating func enqueue(element: Int) { myqueue.append(element) } } var obj = Queue() obj.enqueue(element : 200) print(obj)

As you can see in the above lines of code, we are creating a struct Queue to use the queue functionality. Inside the struct, we are carpeting our object named as ‘myqueue’, which takes up only the Integer value as the data to store in the queue. After this, we are trying to use the ‘enqueue’ function from the queue in swift. This function will add a new element to the queue object we have created. To add the object, we have the append method available. We just have to call the append method on the queue object; inside this method, we can pass our element to the object.

How to remove an element from the queue in swift? import Foundation import Glibc import Foundation struct Queue{ var myqueue:[Int] = [] mutating func enqueue(element: Int) { myqueue.append(element) } { if myqueue.isEmpty { return nil } else{ myqueue.remove(at: 0) return 0 } } } var obj = Queue() obj.enqueue(element : 200) print(obj) obj.dequeue() print(obj)

As you can see from the above lines of code, we are creating a queue. All the things are the same, but now we have added one new function to our queue and is that it removes the element from the queue. If our queue object is empty, then it will return NIL; otherwise, we will call the remove() method to remove the particular element from the queue. To call this method, we can create the object and remove them from the queue.

Example of Swift Queue

In this example, we are trying to create a queue in swift and adding elements to it. We are creating several queue objects and adding the same object to show how we can use this while programming.

Code:

import Foundation import Glibc import Foundation struct Queue{ var myqueue1 :[Int] = [] var myqueue2 :[Int] = [] var myqueue3 :[Int] = [] mutating func enqueue(element: Int) { myqueue1.append(element) myqueue2.append(element) myqueue3.append(element) } } print("Demo to show the queue ceration in swift !!") var obj = Queue() obj.enqueue(element : 200) obj.enqueue(element : 200) obj.enqueue(element : 200) obj.enqueue(element : 200) obj.enqueue(element : 200) print("prinitng result of queue !!") print(obj)

Output:

Conclusion

A queue is used to store element as we know. It comes up with two methods that can be used to perform operations on the queue element named as ‘enqueue’ and ‘dequeue’. They are very easy to implement, readable, and convenient to handle by the developers.

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Correlation In Loadrunner With Web_Reg_Save_Param Example

What is Correlation?

Correlation, as the name suggests, is a mechanism of defining a relationship between two variables or entities. A Dictionary defines it as “statistical relation between two or more variables such that systematic changes in the other accompany systematic changes in the value of one variable”.

In this tutorial, we will learn about

Why do we need Correlation?

Let’s understand co-relation with the following scenario.

Consider you are recording a script using LoadRunner.

Client-Server Communication

During Record,the client sends a request to the server to start a session

A Server receives the request and allocates a new session ID ABC

Client stores the session id ABC in the script.

Client start the session with ID ABC and send a request to a server to allow it to record

The Server recognizes the ID ABC and allows the client to record the script

Now, let’s study the client-server communication during replay

During Replay, a client sends a request to the server to start a session

A Server receives the request and allocates a new session ID XYZ

A Client start the session with previously recorded session ID ABC and send request to server to allow it to record

A Server is unable to identify the ID ABC as it was expecting ID XYZ that it has allocated and session fails.

We need a solution, which to capture parse the dynamic value sent at run-time and return this value back to server. Here is how the client-server communication will look like with this solution

During Replay, a client sends a request to the server to start a session

A Server receives the request, and allocates a new session ID ZZZ

A Client parses this new session id ZZZ from the request.

A Client sends a request to start session with id ZZZ

A Server recognizes the ID ZZZ and allows client to replay the script

This is nothing but correlation.

In case of VUGen, correlation is a binding relationship between a response and any preceding request.

There are various situations when a request is based on a previously received response from the server, such as, a Session ID, server date/time which is fetched from server. These values are different every time you run an application or record a script. Obviously, if the execution of script depends upon a value returned by the server, it means you need to find a mechanism where you can “catch” the server response and attach to those requests which server expects. This is typically called Correlation in LoadRunner.

In simple words, the solution by using Correlation is:

Capture output value from a step

Use above captured value to serve as input to all subsequent steps

Correlation is classified into 2 categories in VUGen/LoadRunner:

Automatic correlation

Manual correlation

Automatic Correlation

LoadRunner provides a mechanism to easily perform correlation in automatic fashion.

VUGen will require you to run a recorded script at least two times so it can internally compare the varying values in the server response.

Automatic correlation can be classified into 3 categories:

Auto-Detect Correlation

Rule-Based Correlation

Correlating All Statements

Rule Name When to Use

Auto-detect Correlation Detect and correlate dynamic data for application servers supported by HP LoadRunner

Rule-Based Used when working with a non-supported application server for which the context is known.

Correlate All Helps correlate all dynamic data in blind fashion.

To configure automatic correlation at the time of recording, perform below configuration in Record Time Setting after a script has been recorded.

Below window will open:

from menu and VUGen will regenerate script (without having to record) with new configurations. VUGen will automatically add a required piece of code to handle correlation. We will look at the sample in more detail in Manual Correlation.

Please note, if you perform correlation manually or use automatic correlation, the piece of code will contain exactly same syntax and function.

Steps to auto-correlate a script:

Record a script

Replay script

Identify the values to be correlated

Verify the script by running again. A successful run means successful correlation.

Tip:

Correlation helps run your script with different values

Correlation also reduces the size of your script

Manual Correlation

Manual correlation is about writing code directly into your script to cater for ever-changing values. We can split it into below steps:

Determine the value to capture

Find the right and left text boundaries of the value to capture (WEB)

Find which occurrence of the text boundaries should be used

Add a web_reg_save_param function to the script, above the piece of code which requests the page with the value to capture

Add a parameter name, left boundary, the right boundary, and occurrence to the function

Parameterize the dynamic value in the script every time it occurs

Verify correct execution

web_reg_save_param (" OracleAppJSESSIONID3", "LB/IC=JSESSIONID=", "RB/IC=;", "Ord=l", "Search=headers", "RelFrameId=l", LAST); web_reg_save_param("Siebel_Analytic_ViewState2", "LB/IC=ViewState" value="", "RB/IC="", "Ord=1", "Search=Body", "RelFrameId=l", LAST);

Manual correlation can be done by VUser Comparison. Steps in VUser Comparison method of Correlation can be split as below:

Identify Dynamic values that need to be correlated

Find Servers response containing the Dynamic value

Capture the Dynamic value in a parameter

Replace every occurrence of the Dynamic value with the parameter

Verify Changes

Understanding Web_reg_save_param function

VUGen provides multiple functions or APIs to correlate candidates, including:

web_reg_save_param

web_reg_save_param_ex

web_reg_save_param_regexp

web_reg_save_param_xpath

Here we go with the function details:

web_reg_save_param(Parameter Name , Left Boundary , Right Boundary )

List of Attributes

Convert: The possible values are:

HTML_TO_URL: convert HTML-encoded data to a URL-encoded data format

HTML_TO_TEXT: convert HTML-encoded data to plain text format; this attribute is optional.

Ignore Redirections: If “Ignore Redirections=Yes” is specified and the server response is redirection information (HTTP status code 300-303, 307), the response is not searched. Instead, after receiving a redirection response, the GET request is sent to the redirected location, and the search is performed on the response from that location.

This attribute is optional. The default is “Ignore Redirections=No”.

LB: The left boundary of the parameter or the dynamic data. If you do not specify an LB value, it uses all of the characters from the beginning of the data as a boundary. Boundary parameters are case-sensitive. To further customize the search text, use one or more text flags. This attribute is required. See the Boundary Arguments section.

NOTFOUND: The handling option when a boundary is not found, and an empty string is generated.

“Not found=error”, the default value, causes an error to be raised when a boundary is not found.

“Not found=warning” (“Not found=empty” in earlier versions), does not issue an error. If the boundary is not found, it sets the parameter count to 0 and continues executing the script. The “warning” option is ideal if you want to see if the string was found, but you do not want the script to fail.

Note: If Continue on Error is enabled for the script, then even when NOTFOUND is set to “error”, the script continues when the boundary is not found, but an error message is written to the extended log file.

This attribute is optional as well.

ORD: Indicates the ordinal position or instance of the match. The default instance is 1. If you specify “All,” it saves the parameter values in an array. This attribute is optional.

Note: The use of Instance instead of ORD is supported for backward compatibility, but deprecated.

RB: The right boundary of the parameter or the dynamic data. If you do not specify an RB value, it uses all of the characters until the end of the data as a boundary. Boundary parameters are case-sensitive. To further customize the search text, use one or more text flags. This attribute is required. See the Boundary Arguments section.

Note: RelFrameID is not supported in GUI level scripts.

SaveLen: The length of a sub-string of the found value, from the specified offset, to save to the parameter. This attribute is optional. The default is -1, indicating to save to the end of the string.

SaveOffset: The offset of a sub-string of the found value, to save to the parameter. The offset value must be non-negative. The default is 0. This attribute is optional.

Search: The scope of the search-where to search for the delimited data. The possible values are Headers (Search only the headers), Body (search only body data, not headers), No resource (search only the HTML body, excluding all headers and resources), or ALL (search body, headers, and resources). The default value is ALL. This attribute is optional but generally preferred.

How To Create Django Signals With Uses And Example?

Introduction to Django Signals

The following article provides an outline for Django Signals. Django offers different features to the user, and that signal is one of the features that Django provides. The single strategy allows us to decouple applications to get notifications when an event occurs. For example, sometimes we need to invalidate the webpage every time with the help of a model instance, but there are several places where we need to update the code, so at that time, we can use singles to handle that situation. In another case, when we have extended custom Django users by one-to-one relationships, we usually use a single dispatcher to listen to the user.

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What are Django Signals?

In certain special-use scenarios, the business requirement of an application may necessitate specific processing to be performed shortly before or after saving the information to a dataset. This implies there ought to be a method for knowing when the information will be saved or has recently been saved in the data set by the Django model strategy save().

How to Create Django Signals?

Let’s see how we can create Django signals as follows:

Signals are utilized to play out any activity on the change of a model case. The signs are utilities that assist us with interfacing occasions with activities. For example, we can foster a capability that will run when a sign calls it. As such, Signals are utilized to play out some activity on change/making of a specific passage in the Database. For instance, one would need to make a profile case when another client occasion is made in the Database.

There are three types of signals as follows:

preserve and postsave: These signals execute before and after the save () method.

predelete and postdelete: These signals execute before and after the delete () method.

preinit and postinit: These signals execute before and after instantiating the model.

On the off chance that you know about the observer design pattern, this is fairly how django executes it. Or if nothing else fills a similar need.

The signs machinery has two vital components: the shippers and the collectors. As the name proposes, the shipper is the one liable to dispatch a sign, and the recipient is the person who will get this sign and afterward follow through with something. A collector should be a capability or an occurrence technique to get signals. A shipper should either be a Python item or none to get occasions from any source. “Signal dispatchers” establish the connection between shippers and recipients by utilizing the interface technique to transmit signals.

The Django framework also defines a ModelSignal, which is a subclass of signal that enables the source to be lazily specified as a string in the app_label.ModelName format. Be that as it may, taking everything into account, we will continuously need to utilize the Signal class to make custom signs. So to get a sign, you want to enroll a collector capability that gets called when the symbol is sent by utilizing the signal.connect() technique.

First, we need to create a project and a model; let’s assume we have already begun a model and other details, so add the code below.

Code:

from chúng tôi import AppConfig class StudentConfig(AppConfig): name = 'student' def ready(self): import student.signals

Explanation:

Now signals are live; we can see in the below screenshot as follow:

At the same time, we can check the admin view, as shown in the below screenshot.

Uses of Django Signals

1. A Signal is an item relating to a specific occasion. For instance, we could characterize the accompanying sign to address a pizza has finished cooking.

Code:

from django.dispatch import Signal coffee = Signal(providing_args=["type", "size"])

Signs can send messages. To achieve this, you call the send() method on the signal instance, passing in a sender argument along with any pre-defined arguments.

2. Beneficiaries are callables that are associated with a specific sign. When the sign sends its message, each associated beneficiary gets called. Therefore, recipients’ capability marks should match what the sign’s send () technique utilizes.

Code:

from django.dispatch import receiver from coffee import signals @receiver(signals.coffee_done) def off_when_coffee_done(sender, type, size, ****): Example of Django Signals

Let’s see an example if you want to create a profile of a user using postsave signals as follows:

First, we must create a project per our requirement or create a separate environment that depends on the user. After creating the project inside the model, add the code below.

from chúng tôi import models from django.contrib.auth.models import Student class Profile(models.Model): student = models.OneToOneField(User, on_delete=models.CASCADE) studphoto = models.ImageField(default='extension of photo', uploadto='studentprofilepics') def __str__(self): return f'{self.student.studname} Profile'

Now inside the view file, add the below code.

Code:

from django.shortcuts import render, redirect from django.contrib import msg from django.contrib.auth.decorators import login from .forms import StudRegiForm, StudUpdateForm, def studregister(request): if request.method == 'POST': form = StudRegiForm(request.POST) if form.is_valid(): form.save() studname = form.claear_data.get('studname') msg.success(request, f'student added successfully') return redirect('studlogin') else: form = StudRegiForm() return render(request, 'student/studregi.html', {'form': form}) def profile(request): if request.method == 'POST': formu = StudUpdateForm(request.POST, instance=request.student) formp = ProfileUpdateForm(request.POST, request.FILES, instance=request.user.profile) if formu.is_validu() and formu.is_valid(): formu.save() formp.save() msg.success(request, f'Update done') return redirect('profile') } return render(request, 'student/profile.html', context)

Now create a form as per our requirement; after completing the form, we need to add a single; here, we use the receiver method as follows.

Code:

from django.db.models.signals import saves, delete from django.contrib.auth.models import Student from django.dispatch import receiver from .models import StudProfile @receiver(postsave, sender=Student) def create_profile(sender, instance, created,): if created: StudentProfile.objects.create(student=instance) @receiver(postsave, sender=Student) def saveprofile(sender, instance,): instance.studprofile.save()

Now we need to write code for signal connection as below.

Code:

from chúng tôi import AppConfig class StudentConfig(AppConfig): name = 'student' def ready(self): import student.signals

Output:

Conclusion

With the help of the above article, we saw about the Django signals. From this article, we saw basic things about the Django signals and the features and installation of the Django signals, and how we use them in the Django signals.

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How Does Credit Limit Work With Example?

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Introduction to Credit Limit

When a lender offers you a credit card or line of credit, it specifies the maximum amount of credit that can be drawn by availing the credit card or line of credit. This maximum amount of credit is known as the Credit Limit (CL).

Typically, the lending institutions decide the CL based on the information provided by you as an applicant. A CL is a significant factor for personal liquidity as it can influence your credit score and, in turn, impact your ability to access future credit.

How Does Credit Limit Work? Example

Let us take the example of David, who has recently acquired a credit card facility from a bank ABC Inc. The CL of the credit card is $5,000, which means that David can spend up to $5,000 with this credit card. Let us assume that David spent $ 3,000 at the start of the current month. Determine the available CL if

David paid $1,500 at the end of the current month

David didn’t pay anything

Solution:

Therefore, if David paid $1,500 at the end of the month, we can calculate the available credit limit.

Available Credit Limit = Credit Limit – Expense During the Month + Payment During the Month

Available CL = $5,000 – $3,000 + $1,500

= $3,500

On the other hand, if David didn’t pay anything, then the available CL can be calculated as,

Available Credit Limit = Credit Limit – Expense During the Month + Payment During the Month

Available CL = $5,000 – $3,000 + $0

= $2,000

How to Increase Credit Limit?

Use the credit facility: If you use the credit facility frequently and make the bill payments in full and on time, then it is likely that the bank may increase your CL.

Provide updated income statement: If your income increases, you should provide the updated income statement (latest payslips) to the bank and request to enhance the existing limit. The bank will be willing to increase the CL in such a scenario.

Apply for a new credit facility: If your existing bank is unwilling to increase your CL and you have a healthy credit history, you can also apply for a new credit facility, which might come with a higher CL.

Make all the bill payments on time: If you make all the bill payments regularly and on time, your credit score will be healthy, and any lender will see you as a low-risk borrower. So, you must be patient and wait, as the bank may automatically offer you a higher CL.

How is Credit Limit Calculated?

Typically, lending institutions take into account the following factors while calculating the CL:

Credit History: Your credit score is one of the most critical factors in calculating your CL. If you can maintain a clean credit history (no defaults or delayed payments), you can retain a good credit score, resulting in a higher CL and lower borrowing rate. On the other hand, if you have several defaults indicating reckless credit behavior, likely, banks may even reduce the existing credit limit. [Note: No credit history can also harm a prospective borrower as the lenders end up with no credit track record to rely on.]

Debt-To-Income Ratio: The lenders also evaluate your income to assess the amount of debt that you can afford to repay. However, a higher income doesn’t guarantee a higher CL, as the banks are more interested in your debt-to-income ratio. The banks also look at the number of debts and your debt servicing history. Effectively, a higher debt-to-income ratio results in a lower CL and vice versa.

Credit Limit Offered By Other Lenders: At times, the banks also take cognizance of the CL offered by the other banks while calculating the CL of their facility. So, the limit of your other facilities can also be one of the factors in deciding the credit limit.

What is a Good Credit Limit?

In the UK, the average CL lies in the £3,000 to £4,000, while some higher-income earners with a healthy credit history enjoy a credit limit of more than £10,000. On the other hand, the average credit limit in the US is around $22,750. It can be inferred that the definition of a reasonable credit limit varies across locations, and there cannot be any single correct answer to this question.

Conclusion

A CL is the maximum credit a lender extends to a borrower.

Lenders calculate the credit limit based on the borrower’s credit history, debt-to-income ratio, and existing credit limits.

Low-risk borrowers are offered higher credit limits and vice versa.

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How Does Loan Syndication Work With Example?

What is Loan Syndication?

The term “loan syndication” refers to the lending process in which a group of lenders funds a loan for a single borrower. This arrangement often occurs when the loan amount is too large for a single lender or the risk associated with the loan exceeds the risk appetite of any single lender. Thus, multiple lenders join hands to form a syndicate and provide the requested capital to the borrower.

Key Takeaways

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It refers to the arrangement in which a group of lenders joins hands to fund the loan requirement of a single borrower.

It usually occurs when the loan amount is too large for a single bank or exceeds a bank’s risk appetite.

In this arrangement, the lead bank takes on the role of the coordinating entity, while the remaining lenders, known as participating banks, collectively share the risk.

There are three major types – underwritten deal, best-effort deal, and club deal.

Features of Loan Syndication

Some of the main features of loan syndication are as follows:

The need for large loan amounts primarily drives the loan syndication arrangement, making it a key motivation behind such arrangements.

The borrower and the group of lenders establish a single comprehensive agreement, eliminating the necessity for separate agreements between the individual banks and the borrower.

The agreement explicitly outlines and pre-determines the loan amount allocated to each participating bank, ensuring transparency and avoiding confusion regarding their financing obligations. 

Loan syndication typically involves reputed corporate entities with strong creditworthiness, reflecting their ability to access substantial funds through this mechanism. 

The loan syndication tenure generally spans 3 to 15 years, depending on the loan’s nature and the agreement between the borrower and lenders. 

In loan syndication, all participating lenders actively share the credit risk. They ensure that in the case of borrower default, the losses are collectively distributed among them.

How Does Loan Syndication Work?

Now let us look at how loan syndication works in the real world:

In the pre-mandate stage, the borrower approaches a lender or invites competitive bids from multiple lenders.

Based on rounds of discussions, the borrower appoints the arranging bank or lead bank.

The lead bank prepares the Information Memorandum for the loan, which typically includes the executive summary, terms & conditions, industry overview, detailed assessment, investment considerations, financial structure, and other key information about the loan.

The lead bank then invites other banks to participate in the loan syndication.

After finalizing the participating banks, the participants sign the confidentiality agreement.

After completion of the loan documentation, the contract is prepared while the loan amount is disbursed.

Finally, the loan must be monitored regularly through an escrow account in which the borrower must deposit the revenue. The escrow account serves the purpose of repaying the loans and fulfilling other statutory dues.

Example of Loan Syndication Types of Loan Syndication

There are three major types. They are:

Underwritten deal: In this type of loan syndication, the lead bank guarantees to arrange for the entire loan. The lead bank must finance the funding shortfall if the loan isn’t fully subscribed. Given the risk the lead bank assumes, it charges a higher service fee.

Best-effort deal: In this type of loan syndication, the lead bank doesn’t commit to arranging the full loan amount and underwrites it on a best-effort basis. If the loan remains under-subscribed despite multiple attempts by the lead bank, the borrower is compelled to accept a lower loan amount.

Club Deal: In this type, the loan amount is smaller (up to $150 million), and all the participants have an equal share.

Advantages of Loan Syndication

Given that it lowers the lending risk, the alliance of lenders can provide the loan at competitive terms, such as prepayment facilities, without the standard penalty.

Borrowers benefit in terms of flexible loan structure and reduced effort to disbursement.

When a group of lenders agrees to fund a company’s business growth, it gives a facelift to the company’s reputation and boosts its market credibility.

First, forming a loan syndicate requires much time as the lenders must go through extensive documentation.

The management of multiple lenders is an arduous task for a borrower. Even a small issue with a single bank can complicate things and impact the credit lines unfavorably.

Conclusion

Loan syndication benefits both lenders and borrowers. Lenders can share the risk, reducing their exposure, while borrowers benefit from a streamlined process that saves them time and effort.

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