by Kurt Cagle
In my previous posting (Imports and Tunnelling in XSLT2) I started down a path that I've been planning on covering for a while: presenting a solid business case for migrating to XSLT2. When I first encountered XSLT, after an initial period of attempting to understand the paradigm, I found myself both impressed and disappointed. XSLT is an often underrated technology, in great part because it doesn't fit cleanly into the Algol-based model that is most commonly used today (C, C++, C#, Java, etc.).
I consider XSLT something of a jujitsu language - it is most effective when used sparingly, letting the XML itself do the heavy lifting with the XSLT providing just enough of the pivotal support to do incredible things. That's why it has quietly become the silent partner on any number of different platforms as XML becomes more pervasive on those platforms. It is used within any number of Java and .NET applications, just another piece of the infrastructure, though one that does a disproportionate amount of the real work in applications that are increasingly driven by dynamic GUIs and web services.
Yet what disappointed me about XSLT, especially the more that I had a chance to play with it, was the fact that it was deliberately shackled by its conception as an XML translator to HTML. You couldn't manipulate non-XML text with it, could only do a fairly limited number of strong manipulations (in a language that was, fundamentally, parsing text), you couldn't create intermediate nodes for processing, and things that should have been fundamental - the ability to create an indexed for-loop, for instance - necessitated some very ugly recursion that added considerable complexity to the language without a lot of reward.
I wasn't the only one who found this to be the case, by the way. Indeed, many developers have come to XSLT for its potential capabilities but found themselves so bogged down with the verbosity and complexity of XPath manipulations that they would soon beg to find some other, easier solution. This has, in turn, created something of a backlash to the language, and more than a few projects built around XSLT have consequently become management nightmares, because few developers wanted to develop the expertise to debug seemingly incomprehensible stylesheets, especially given that it fell into the "declarative ghetto" where salaries were often lower than for procedural programmers because of the bias to see XML expertise (and consequently XSLT) as being simply an extension of HTML expertise.
This motivated me to follow the development of the "next generation" of XSLT, with the hope that it might prove an improvement over what currently existed. XSLT 1.0 was not so much broken as incomplete, though there were some fundamental changes that needed to be made to the data model in irder to accomodate the additional changes. Thus began an arduous trek following the development of XSLT 2.0.
By the time that XSLT 1.0 came out, James Clark, the iconoclastic genius who created XSLT in the first place, had shifted his attention away from transformations and into schemas, eventually laying the groundwork for Relax NG. Meanwhile, Michael Kay, the author of the authoritative XSLT books for Wrox and the creator of the Saxon XSLT processor, took over the editorship of the XSLT working group, working in conjunction with people such as Jeni Tennison and Dimitre Novatchev to establish both a set of extensions to XSLT 1.0 under the EXSLT.org banner and ultimately a proposed XSLT 1.1 Working Draft by mid 2002.
However, a number of realizations about the depth of the problem with the data model (and consequently of XPath, which relies heavily upon this model) forced the withdrawal of the XSLT 1.1 Working Draft from the W3C and the formal establishiment of an XSLT 2.0 working group. The goal of this group was simple -- to do XSLT right, to fix some of the biggest problems of XSLT that came from being based upon certain intrinsic assumptions and to revise XPath so that it would be robust enough to handle a much wider range of problems.
Not Your Father's XSLT
The language that is emerging bears a number of broad similarities with XSLT 1.0, but underneath it is a considerably more sophisticated vehicle. Perhaps the biggest change has come in the introduction of sequences. A sequence is a linear list - a set of XML objects, numbers, text strings, and other objects that can be ordered and otherwise manipulated. In XSLT 1.0 (and more specifically within XPath 1.0), you could only work with node lists, and even though such lists could hold text content (what are called text nodes) these were still containers for content rather than the content itself. By generalizing the node-set into a sequence, several things were made to happen:
- Sequences could hold references to multiple distinct XML trees, something which was included as function in XSLT 1.0 (the document() function) but not in XPath 1.0.
- You could create temporary trees of XML from other XML operations, using this intermediate XML as a way to perform other transformations. Most XSLT implementations had implemented a "fiat" way of doing this (a node-set() function, typically) but the implementations varied and the underlying model was incompatible with this.
- Sequences made it much easier to eliminate duplicates and perform other logical operations on XML data, such as grouping (something that can be fiendishly difficult with XSLT 1.0).
- Sequences made it possible to create iterative loops (something analogous to for(i=0;i!=n;i++){do something with i;}). The to operator in XPath 2.0 let's you create constructs such as (1 to 5), which generates the sequence (1,2,3,4,5).
- Sequences also lay at the heart of another critical requirement for XSLT - the ability to parse strings into constituent pieces.
Once this foundational step was laid, the next stage in the process was to build up from that, adding new capabilities while still trying to retain as much of the power of the old standard as possible. This came about through the introduction of other innovations into the XSLT and XPath standards:
- Regular Expressions. Regexes (as they are often called) provide a powerful tool for both searching and manipulating patterns within text. XPath 2 now incorporates the Perl regular expression engine (with some minor additions), making it possible to convert text files into sequences and from there into XML documents. This key capability makes XSLT a particularly noteworthy candidate for handling compiling, something that will be discussed later.
- User Defined XPath Functions. The XPath Working Group established a formal mechanism for binding external functions into XPath, providing a clean, consisten means to build new functions XPath that could be written in C++, C#, Javascript, Java, Perl ... and XSLT. This dramatically reduces the amount of code necessary to invoke XSLT named templates (often by an order of magnitude or more) and also makes it possible to migrate XSLT from a Java based system to a C# based one without needing to change any XSLT - you'd just rewrite the external functions but keep the same function signatures.
- Conditional Expressions. With XPath 2.0, you can now write if/then/else and for() statements within XPath, making it possible to create much richer logic into the language. Not only does this also reduce the amount of verbosity in the language significantly, it also makes it possible to solve what was typically not even possible in XPath - such as adding taxes and discounts into item costs in an invoice before finding a total.
- Date/Time Manipulation. Date and time manipulation was something of a nightmare in XSLT 1.0, yet because of the importance of such information in transformations, there was a thriving industry in building work-arounds. Now such capability, including finding the difference between two dates or times, is built into the language.
- Complex Grouping. The data model in XSLT 1.0 made it very difficult to handle certain kinds of groupings, such as mapping the relatively flat structure of HTML to the group and section model of XSL-FO or DocBook. With sequences and regular expressions, generating such groups is now possible, especially in conjunction with certain additional XSLT 2.0 elements.
- Multiple Outputs. XSLT 1.0 was assymetric -- it was possible to pass in multiple XML documents through parameters, but it was not possible to produce more than one formal output. That's changed with XSLT 2.0. Now, you can write transformations that will generate any number of XML or text output formats, either to be saved to local storage or to be sent to external web addresses, depending upon security restrictions.
- Type Awareness. Perhaps one of the most contoversial aspects of XSLT 2.0 and XPath 2.0 is the introduction of schema-aware tranformations which were capable of validating and manipulating typed XML content from external XML objects. This is not an intrinsic part of the specification, however, so it is less likely that all XSLT 2.0 processors will be schema aware.
This combination of features fills most of the holes left from the XSLT 1.0 implementation and makes it possible to start thinking about XSLT sitting not just along the periphery of your operation, but right in the middle handling the processing of business logic.
XSLT For Businessmen
In a typical business, you buy or implement business software in response to your changing business needs. Much of this software is anticipatory in nature - the designers of the applications attempt to model ahead of time the scenarios that are most likely to occur in your business, and then build the business logic for these scenarios into the code itself.
Anticipatory design has a number of side-effects, few of them positive. For starters, the applicability of the software becomes a measure of the degree to which the application designers were successfully able to model the business processes that occur. When the modelling is close, the application integrates well into the work flow of the company. When the modelling isn't so close, the company is all too often forced to adapt to the workflow of the software, which introduces inefficiencies.
Moreover, over time, a company's business requirements change as the business itself changes. However, the software has almost certainly been written by someone who is no longer writing that particular piece of software -- best case scenario is that they are working on some other part, and consequently have to stop what they're doing to change the code. Worst case scenario is that your lead programmer is India (unless you are in India, in which case your lead programmer is in London), has long since left the company, and likely didn't document the code terribly well. Thus, over time, the software decays, until it is no longer useful to the company, forcing another massive expenditure into the whole in your business called IT Expenditures.
Finally, many such solutions are intimately tied not just to a particular operating system but a particular machine, and should something happen to that machine, your company could be left with a major problem.
All of these situations point out the limitations of anticipatory design, but such design is still the most prevalent because it 1) keeps software vendors in business, 2) keeps consultants in business, and 3) ultimately forces hardware upgrades, keeping hardware vendors in business. Of course, unless your business is specifically dedicated to keeping these three groups in business, such design often becomes a hidden tax on computer usage, a constant drain on expenditures that becomes very easy to accept as unavoidable. However, that cost really isn't as necessary as it may seem.
One of the great benefits of XML is the fact that it's use tends to encourage adaptive rather than anticipatory design. With adaptive design, the business logic of a company can be readily encoded in an easy to manipulate bundle of information which can work across any platform. Your code can generate your user interfaces in response to changes in data requirements, passing that information into transformations that can readily encode the business logic. Moreover, even the transformations themselves can be transformed, can be designed to change as business parameters change. In short, such systems, adapt to the changing requirements of the business.
XSLT 1.0 was an interesting first step in this process, but all of the points mentioned above - the complexity of the language, the verbosity of the code, and the often counterintuitive techniques necessary to handle frequent operations made it less than idea for this particular process. However, XSLT 2.0 is considerably simpler to follow, write, and maintain, can more reliably integrate with external processes and objects, and is able to handle multiple possible input and output forms at once.
As tools such as XForms (or some equivalent XML centric forms technology) becomes more prevalent, this also means that interface tools (and not necessarily just "web tools") will increasingly generate and send XML content directly rather than the more limited name/value pairs of HTTP (in essence what SOAP does via the agency of web services), and in general XSLT is a better tool for manipulating and extracting information form XML sources than DOM tools are ... if that extracted information is itself in XML format. In that respect, DOM can be thought of as being a binding mechanism that connects XML with other object representations (that is, other programming language data structures).
This use of XSLT within XML millieus is an important concept, with very broad implications. XSLT is not sexy. There are no marketing teams out there who put out multimillion dollar ad campaigns featuring well-coifed executives staring raptly at XSLT code on their laptops. Instead, XSLT is an infrastructure sort of thing, found deep within (a surprising number of) applications, increasingly taking over the task of document and object conversions that for years had been the domain of heavily sequestered filter writers. The application I'm writing this on right now, an HTML editor which I wrote, uses XSLT to convert between an editor component's internal representation and one of several XML formats -- including docBook, XHTML, Microsoft Word 2003's XML format and others. Yet without knowing that, you'd never even be aware of how critical that technology is, because it does exist so quietly.
Code Building Code
XSLT 2.0 will likely become much more pervasive, because it's domain of applicability is so much broader and because much of the design of the second version of the language is deliberately built around the manipulation of any textually represented object -- including other programming languages. Most programming languages have a very well-defined programming structure, independent of the commands themselves -- packages, classes, constructors, destructors, methods, properties, event handlers -- in most cases there are relatively few variations off of these basic entities, in great part because programming languages are process descriptions (at least imperative languages are).
XML in turn is a good language for the description of descriptions, and as a consequence, it can very readily incorporate larger functional blocks of code in a descriptive matrix. Once in that format, generating code in other languages becomes much easier using a language such as XSLT2, especially with the addition of regular expression tokenizing parsers. On the flip side, XSLT2 is also remarkably good at the inverse process -- parsing program language blocks and converting them into an XML representation. In short, XSLT2 could find itself becoming what amounts to a universal compiler/decompiler, at first into intermediate forms such as Java or C#, and then with increasing frequency, directly into bytecode or intermediate language (IL) generators (this is especially significant of C#, which already maps many of its languages into a common IL format).
From an application standpoint, this raises the real possibility that this next generation of XSLT2 could in fact not only handle the processing of business logic, but actually generate just-in-time compiled code to more quickly execute such logic, and could perforce route it to the locations where such JIT code would be needed. User interfaces could be built on the fly, something especially critical in business applications where a significant portion of the programming work (and hence cost) that takes place is oriented to developing the screens whereby people interact with the data. The combination of XSLT2 and web services can also abstract connections into SQL and LDAP repositories, meaning both that such data sources become more interchangeable and that the way of accessing something as different as a relational database and an LDAP directory becomes irrelevant.
Finally, XSLT2 simplifies the way that information moves within your enterprise, ironically by moving away from what had been the cornerstone of programming in the 1990s - the object-oriented-programming paradigm. One of the difficulties that has emerged from OOP principles has been in determining the decomposition of a problem space into distinct classes. Programmers new to OOP (and in all too many cases not so new) have a tendency to want to model everything as a class, and as a consequence their application code begins to resemble the Harry Potter series -- full of wonder and magic, but with entirely too many pages for what is, fundamentally, a children's story. The problem with this is that each class has to be written and tested, not only in isolation but also in tandem, and a seemingly trivial change in a base class can have profound consequences for other classes built upon it.
XSLT 2.0, on the other hand, shifts the approach taken from building up this complex zoo of class critters and pushes it back towards an approach which is coming back into vogue with the advent of Linux: streams and pipes. A stream can be thought of as data moving between two processes, whether those processes be a file reader, a web server, a program, a database, a web client, or the interface to some piece of hardware. A pipe on the other hand, is the conduit which carries the stream. The OOP revolution placed a huge amount of significance on the node where pipes met, and tended to relegate the pipes and streams to secondary status, at best.
However, XML and the web is changing this. One effect of XML web services is to envision programs as being the transmission of streams of data to distinct end-points, URLs, without necessarily caring about what happens within that end-point. An object orientation gives many more points of access into an object, but typically at a cost of dealing with that object's specific data restrictions. With a web service, I can send a stream of information to a URL, and the process at that end will choose (if it is well designed) to either determine that it is valid and usable (there are processes that are designed to work with that stream at that node), that it is valid but not immediately usable (it is sent off to a different process which will attempt to rectify it into something of significance to the first process) or that it is invalid (whereupon notification of this lack of validity is sent back to the sender).
XSLT2 can handle all three potential conditions (though the case where the data is not well-formed XML gets a little complicated). Well formed XML has an associated namespace, and this namespace can actually be used by the XSLT itself to determine the proper handling of XML content, perhaps with the concept that such an XSLT could pass on the parameters acting upon the transformation into part of a SOAP message and then routing that message to the appropriate final transformation. in a purely asynchronous model (one where each node can act both as a transmitted of XML and a receiver of XML under separate processes), the routing XSLT does not have to be the XSLT that handles the final processing of the associated data -- or the one that communicates back to the client. While this model doesn't quite work in the fairly strongly synchronous browser model that most people connected to the web currently use, contemporary web clients are in fact shifting to an asynchronous model where it will work just fine.
An Open Letter
If XSLT2 is such a superior technology, why has it raised the ire of a few of the largest software vendors (most notably Microsoft)? This is in fact a case of the question providing its own answer. XSLT 2.0 provides an answer to many (perhaps most) of the complaints of XSLT 1.0, including the most damning ... that it is too conceptually difficult and verbose for programmers to learn. XSLT2 is more functionally oriented than XSLT1, making it easier for programmers more comfortable with languages such as Java or C++ to use.
XSLT2 also binds to external classes much more transparently, making it much easier to communicate with external processes within the environment, regardless of what that environment is (or what kind of box that environment is running on). It doesn't require an expensive suite of tools, compilers, and libraries of objects to work with it, and it is fundamentally oriented to manipulating XML data (though not exclusively) without the strong-typing limitations that come with Algol based languages.
XSLT is also considerably more secure, based upon what I'd call the potency argument. In essence, most binary objects contain not only their own state but also the mechanisms by which that state gets expressed to the outside world. In essence, these objects are potent - they have the ability to create side-effects that may not be obvious from their interfaces, as they have to have a certain level of interaction with the system in order to be able to function. In effect, the level of trust that these objects require of the system simply in order to operate is too high, forcing the creation of human trust authorities.
With XSLT, on the other hand, the streams of XML information coming in are pre-potent. They provide a description of state, but are reliant upon the XSLT that is resident within the server to handle the manipulation of that state, and correspondingly to specifically provide exceptions for handling things outside of the boundaries of safe behavior. It is consequently incumbent upon the maintainer of the system to choose the interpreters of that data, rather than placing the security demands upon the (non-technical) users of the applications.
Given all this, XSLT2 enabled systems could serve to signficantly erode the requirements for complex components that sit at the heart of most operating systems, a potential boon to open source systems such as Linux but one that could dramatically impede the ability to effectively sell subsequent implementations of Windows (or so at least one line of reasoning goes that I've seen bandied about). It makes code generation a just-in-time process and so effectively blurs the distinction between data and code, a distinction that Microsoft still makes even as it defines its own XML user interface language (XAML, which requires a healthy dose of C# "code-behind" in order to do more than trivial applications).
Microsoft has chosen to include XQuery 1.0 (a data-binding language that builds on XPath) but not XSLT 2.0 in Longhorn, citing everything from lack of customer interest to complexity in implementation to insufficient maturity on the part of the specification. They have even gone so far as to try to develop an alternative language, C Omega, which is supposed to provide a C# oriented approach to manipulating XML.
I've played with C Omega some - it is a reasonably good way to avoid some of the tedium of working with the W3C DOM, and it is certainly possible to use it for some of the same purposes that you'd use XSLT2, though it lacks the powerful recursive templating capability that I think gives XSLT most of its power. It presupposes that the appetite for XQuery will be strong enough that they can essentially build a hybrid language around it, though after having written two books on XQuery that have between them garnered less than the production costs for the books in question I'm much less inclined to agree, especially as XPath2/XSLT2 becomes much more functionally oriented.
At the last Sells Brothers XML Conference (which I would heartily recommend, by the way) I gave a talk on Saxon.NET, an open source project in which M. David Peterson has converted Michael Kay's superb Saxon 8.0 XSLT 2 implementation over to .NET, with Dr. Kay's approval. I'm using it now for a content management system, and it has performed far better than I had even hoped. At any rate, when the Microsoft representatives at the conference later asked at the crowd whether they would rather have work on XQuery or XSLT2, the number of people (in many cases customers of Microsoft) who wanted to see a new XSLT outnumbered those of XQuery by a considerable margin.
While I strongly support Mr. Peterson's efforts, I also would like to make a plea to Microsoft to reconsider your stance on this. I believe that the demand for a more powerful version of XSLT is out there, and that it is being driven by application developers who are building applications for Windows as well as elsewhere. It will become the de-facto standard within your competitors' business productivity suites, web clients, home entertainment applications and operating systems, because if you choose not to develop such a processor, others will provide .NET versions that will be used in place of your own offerings. You will have already done most of the hard work in implementing it, as the major portion of the changes that occur in XSLT 2 is due to the revision of XPath 2.0, which you are already developing to support XQuery.
To business decision makers reading this, chances are really good that you will likely never actually have to sit and look at a screen of XSLT 2. However, as with XML six years ago, XSLT 2 is a technology that will likely end up shouldering much of the day to day processing within your organizations over the course of the next five years -- it is a natural complement to XML, which has, like kudzu, pretty much taken over the data infrastructure of most applications it comes in contact with.
There's another factor that comes into play here from a business perspective. In 1993-4, an independent consultant could earn $250 an hour writing HTML content. Today, HTML is considered a basic skill that every graphic designer needs to learn as part of his or her doing their job, and HTML generation is mostly handled via automation mechanisms. XSLT serves many of the same purposes that tools such PHP, ASP.NET, Perl, and JSP serve today, but as the world continues its adoption of XML as the standard for conveying structured content, XSLT is becoming something of a lingua franca - a common tongue - that developers in this space are learning, and are finding in that learning that by intelligent application of that XSLT that particular skill is cleanly transferable from a Linux box running Apache using PHP and a Windows box running IIS and ASP.NET.
XSLT 2 is not a new language - it is XSLT cleaned up to handle the areas it should have been capable of handling before, with much less verbosity, more integration, more power and a considerably easier development and maintenance path. This means that the learning curve for those developers going from XSLT to XSLT 2 will be much less extreme than having to learn another language in toto. This in turn means that within a space of a couple of years, if not less, XSLT2 will likely be just another core skill that a developer should have, yet one that helps them write platform and language neutral code for dealing with all of the XML that is even now circulating through your business. With skilled programmers in any area once again beginning to demand a premium, the coming ubiquity of XSLT2 skills should help keep your labor costs down not just in your web development department, but throughout your organization.
/EndTag
There's a tendency of late for writers in the XML space to want to play down some of the more recent standards from the W3C, a tendency to go "ho-hum, it's just the sequel". I think this attitude can blind people to what is actually happening. XSLT 1.0 was a uniquely different and powerful solution, and after having worked with it on an almost daily basis for nearly the last decade my respect for its innovation has only grown. However, even four years ago I felt that it wasn't powerful enough, and the amount of customization on the part of XSLT processor vendors over the last several years to me is testament to that. XSLT 2.0 is not profoundly different from XSLT 1.0 - it's in fact almost completely backwards compatible.
It does, however, rectify the shortcomings that emerged from the first iteration of the language, and does so in a way to make it an astonishingly powerful language. History is full of such standards, such as SQL, where it took one or two iterations to handle the inevitable discovery process that is part of any great human endeavor. This tool, XSLT, is already becoming one of the core work-horses in most contemporary applications, even given that it was never originally conceived to do what it is called for. To move forward to a version improved by half a decade of insight and exploration is not only logical, it's good business.
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Debt1consolidation.com entails taking out one loan to pay off many others. This is often done to secure a lower interest rate secure a fixed interest rate or for the convenience of servicing only one loan.
Debt consolidation can simply be from a number of unsecured loans into another unsecured loan, but more often it involves a secured loan against an asset that serves as collateral, which is most commonly a house (in this case a mortgage is secured against the house.) The collateralization of the loan allows a lower interest rate than without it, because by collateralizing, the asset owner agrees to allow the forced sale (foreclosure) of the asset to pay back the loan. The risk to the lender is reduced so the interest rate offered is lower.
Sometimes, debt consolidation companies can discount the amount of the loan. When the debtor is in danger of bankruptcy, the debt consolidator will buy the loan at a discount. A prudent debtor can shop around for consolidators who will pass along some of the savings. Consolidation can affect the ability of the debtor to discharge debts in bankruptcy, so the decision to consolidate must be weighed carefully.
Debt consolidation is often advisable in theory when someone is paying credit card debt. Credit cards can carry a much larger interest rate than even an unsecured loan from a bank. Debtors with property such as a home or car may get a lower rate through a secured loan using their property as collateral Then the total interest and the total cash flow paid towards the debt is lower allowing the debt to be paid off sooner, incurring less interest. In practice, many people are in credit card debt because they spend more than their income. If that habit continues, the consolidation will not benefit them much because they will simply increase their credit card balances again.
Because of the theoretical advantage that debt consolidation offers a consumer that has high interest debt balances, companies can take advantage of that benefit of refinancing to charge very high fees in the debt consolidation loan. Sometimes these fees are near the state maximum for mortgage fees. In addition, some unscrupulous companies will knowingly wait until a client has backed themselves into a corner and must refinance in order to consolidate and pay off bills that they are behind on the payments. If the client does not refinance they may lose their house, so they are willing to pay any allowable fee to complete the debt consolidation. In some cases the situation is that the client does not have enough time to shop for another lender with lower fees and may not even be fully aware of them. This practice is known as predatory lending Certainly many, if not most, debt consolidation transactions do not involve predatory lending.
In the United States, federal student loans are consolidated somewhat differently, as federal student loans are guaranteed by the U.S. government. In a federal student loan consolidation, existing loans are purchased and closed by a loan consolidation company or by the Department of Education (depending on what type of federal student loan the borrower holds). Interest rates for the consolidation are based on that year's student loan rate, which is in turn based on the 91-day Treasury bill rate at the last auction in May of each calendar year.
Student loan rates can fluctuate from the current low of 4.70% to a maximum of 8.25% for federal Stafford loans 9% for PLUS loans. The current consolidation program allows students to consolidate once with a private lender, and reconsolidate again only with the Department of Education. Upon consolidation, a fixed interest rate is set based on the then-current interest rate. Reconsolidating does not change that rate. If the student combines loans of different types and rates into one new consolidation loan, a weighted average calculation will establish the appropriate rate based on the then-current interest rates of the different loans being consolidated together.
Federal student loan consolidation is often referred to as refinancing, which is incorrect because the loan rates are not changed, merely locked in. Unlike private sector debt consolidation, student loan consolidation does not incur any fees for the borrower; private companies make money on student loan consolidation by reaping subsidies from the federal government.
Student loan consolidation can be beneficial to students' credit rating, but it's important to note that not all federal student loan consolidation companies report their loans to all credit bureaus; SLM Corporation (formerly Sallie Mae) does not report to Experian or Transunion which means that students will have differing credit scores at Equifax Transunion, and Experian.
Credit as a financial term, used in such terms as credit card refers to the granting of a loan and the creation of debt. Any movement of financial capital is normally quite dependent on credit, which in turn is dependent on the reputation or creditworthiness of the entity which takes responsibility for the funds.
A similar usage is in commercial trade where credit is used to refer to the approval for delayed payments for goods purchased. Sometimes if a person has financial instability or difficulty, credit is not granted. Companies frequently offer credit to their customers as part of the terms of a purchase agreement. Organizations that offer credit to their customers frequently employ a credit manager
Credit is denominated by a unit of account Unlike money (by a strict definition), credit itself cannot act as a unit of account. However, many forms of credit can readily act as a medium of exchange As such, various forms of credit are frequently referred to as money and are included in estimates of the money supply
Credit is also traded in the market The purest form is the "Credit Default Swap" market, which is essentially a traded market in credit insurance. A credit default swap represents the price at which two counterparties will exchange this risk — the protection "seller" takes the risk of default of the credit in return for a payment, commonly denoted in basis points (one basis point being 1/100 of a percent) of the notional amount to be referenced, while the protection "buyer" pays this premium and in the case of default of the underlying (a loan, bond or other receivable), delivers this receivable to the protection seller and receives from the seller the par amount ( i.e., is made whole).
Credit Education is the practice of providing consumers with information analyzing their credit behavior. Credit education is usually practiced by trained professionals knowledgeable in the analytics of the credit score and how consumer credit behavior effects both positive and negative credit eligibility. Credit education is usually assisted by sophisticated credit scoring models that mathematically assists the consumer, or counselor, in determining a credit improvement outcome.
Credit Education has become an increasingly practiced discipline due to sweeping increases in the use of the credit score and its affect on the prices consumers pay for loans, insurance, housing and utilities. It is also the major factor in loan eligibility.
Not to be confused with credit counseling credit education does not focus on debt counseling, nor involves the practice of collecting debt from consumers. Credit counseling and credit repair have consistently received negative publicity for its fee and management practices.
The largest suppliers for credit education data are Fair Isaac Corporation, CreditXpert and the three credit bureaus ( Experian, TransUnion and Equifax who deliver credit reports and credit scores. Among the largest providers of credit education services is Community Empower who, through the use of its own scoring models and national network of credit education counselors, provides consumers hands-on guidance using highly-trained local professionals.
Credit education has also received attention as a new discipline at the Community College level where new courses on the subject are being taught. Usually aligned with Mortgage Finance programs that teach college undergraduates principles of lending and underwriting credit education and credit recovery programs are giving students more extensive backgrounds in credit early in their careers. Among the early college level adoptors of credit education is the Los Angeles Community College District and Los Angeles Trade Technical College.
FICO is an acronym for Fair Isaac Corporation (traded publicly under the symbol FIC) and refers to the best-known credit score model in the United States, which is calculated using mathematical formulae developed by this company. The FICO score is primarily used in the consumer banking and credit industry. Banks and other institutions that use scores as a factor in their lending decisions may deny credit, charge higher interest rates or require more extensive income and asset verification if the applicants credit score is low.
FICO scores are designed to indicate the likelihood of a borrower being delinquent within the next 24 months. No public information is available to determine what the scores mean in terms of statistics. A separate score, BNI, is used to indicate likelihood of bankruptcy.
The three major credit reporting agencies (also often, but inaccurately referred to as credit bureaus) in the United States, Equifax, Experianand TransUnion calculate their own credit scores, which go by different trademark names as well as many different versions of the score (often differing because of what they are meant to predict and when they were written): Beacon, Beacon 96, and Pinnacle are all available only from Equifax; Empirica, Empirica Auto 95, Precision Score, and Precision 03 at TransUnion; and Fair Isaac Risk Score at Experian. These versions, while all developed for the agencies by Fair Isaac, differ and are periodically updated to reflect current consumer repayment behavior. The NextGen Scores are the most recent scores, but creditors vary in which version they prefer to use.
The scores use a multiple scorecard design. Each version uses 10 or more individual scorecards, and an individual is typically compared with similar others. (For example, a borrower with two 30-day late payments will be scored against a population with some minor delinquencies.) An individual is then graded according to what variables seem to indicate a repayment risk in that group. This feature may cause a borrower with delinquencies to score in the same range as a borrower without delinquencies.
Nearly all large banks also build and use their own proprietary statistical models for credit scoring purposes, often in conjunction with the FICO score or other outside scores.
The statistical models that generate credit scores are subject to federal regulations. The Federal Reserve Board's Regulation B, which implements the Equal Credit Opportunity Act, expressly prohibits a credit scoring model from considering any prohibited basis such as race, color, religion, national origin, sex, or marital status. Regulation B also stipulates that credit scoring models must be empirically derived and statistically sound. Furthermore, if an adverse action is taken as a result of the credit score ( e.g. an individual's application for credit is denied) then specific reasons for the denial must be provided to the individual. A statement that the individual "failed to score high enough" is insufficient; the reasons must be specific.
There exist several generally accepted algorithms for extracting the primary contributing factors to a low credit score. One or more of these algorithms is typically used to supply a list of reasons when a loan applicant has been denied credit, in order to satisfy the Regulation B requirement that specific reasons are disclosed. Some consumers feel these adverse action reasons are somewhat disingenuous, as the only determining factor for credit denials is a numeric score — the "reasons" are summed up only for the consumer.
Each of the credit reporting agencies has developed its own version of the credit score intended to compete with Fair Isaac's score. Although not as widely used, these scores (for example Trans Union's "TransRisk" score or Experian's "ScoreX" and "PLUS" scores) are less expensive than the FICO score. These scores are often derisively referred to by consumers and lenders as "FAKO" scores, for they do not use official Fair Isaac methodologies. The cost savings of a non-FICO score are tempting to some banks and credit card companies, who need an accurate risk assessment on millions of accounts every year. For ease of use, these scores tend to be mathematically scaled so that they fall in the same general range as the FICO score. Fair Isaac offers scoring models for the U.S ., Canada, and South Africa. It also offers a "Global FICO" for many other countries.
Credit scores are designed to measure the risk of default by taking into account various factors in a person's financial history. Although the exact formulae for calculating credit scores are closely guarded secrets, Fair Isaac has disclosed the following components and the approximate weighted contribution of each:
35% punctuality of payment in the past (only includes payments later than 30 days past due)
30% capacity used: the ratio of current revolving debt (credit card balances, etc.) to total available revolving credit (credit limits)
15% length of credit history
10% types of credit used (installment revolving consumer finance
10% recent search for credit and/or amount of credit obtained recently
The above percentages provide very limited guidance in understanding a credit score. For example, the 10% of the score allocated to "types of credit used" is undefined, leaving consumers unaware what type of credit mix to pursue. "Length of credit history" is also a murky concept; it consists of multiple factors - two being the oldest account open and the average length of time an account has been open. Although only 35% is attributed to punctuality, if a consumer is substantially late on numerous accounts, his score will fall far more than 35%. Bankruptcies, foreclosures, and judgments affect scores substantially, but are not included in the simplistic pie chart provided by Fair Isaac.
Further, Fair Isaac does not use the same "scorecard" for everyone. The scorecards are segmented so that there are over 100 different actual scoring models that are applied to different individuals based on different ranges of input values (some scorecard segmentations include: age, depth of credit history, etc.) The implications of this segmentation are that while the approximate weighted contribution above may be an average across all scorecards, individuals will receive different scores or weightings based on the scorecard segmentation that they fall into. Some consumers have noticed their scores decreasing by small amounts for no apparent reason.
Current income and employment history do not influence the FICO score, but they are weighed when applying for credit. For instance, an unemployed individual with no other sources of income will not usually be approved for a home mortgage, regardless of his or her FICO score.
There are other special factors which can weigh on the FICO score.
Any monies owed because of a court judgment, tax lien, or similar carry an additional negative penalty, especially when recent.
Having above a certain number of consumer finance company credit accounts also carries a negative weight (critics say that this causes a vicious cycle, locking people into continuing to use consumer finance companies).
The number of recent credit checks also can weigh down the score, although the credit agencies claim to allow for credit checks made within a certain window of time to not aggregate, so as to allow the consumer to shop around for rates.
A FICO score generally ranges from 300 to 850. It exhibits a left-skewed distribution with a US median around 725. 660 is generally regarded as potentially subprime and represents an important break point for credit worthiness. The performance of the scores is monitored and the scores are periodically aligned so that a credit grantor normally does not need to be concerned about which score card was employed.
Each individual actually has three credit scores for any given scoring model because the three credit agencies hold their own, independent databases. These databases are independent of each other and may contain entirely different data. Many lenders will check an applicant's score from each bureau and use the median score to determine the applicant's credit worthiness.
A new Vantage score has been offered by all three credit bureaus to creditors since spring 2006. It will soon be available to debtors. Its range is from 501 to 990. It is graded A (901-990), B (801-900), C (701-800), D (601-700), and F (501-600). It remains to be seen whether the Vantage Score will replace the FICO score or even be accepted by many creditors.
Debt1consolidation.com entails taking out one loan to pay off many others. This is often done to secure a lower interest rate secure a fixed interest rate or for the convenience of servicing only one loan.
Debt consolidation can simply be from a number of unsecured loans into another unsecured loan, but more often it involves a secured loan against an asset that serves as collateral, which is most commonly a house (in this case a mortgage is secured against the house.) The collateralization of the loan allows a lower interest rate than without it, because by collateralizing, the asset owner agrees to allow the forced sale (foreclosure) of the asset to pay back the loan. The risk to the lender is reduced so the interest rate offered is lower.
Sometimes, debt consolidation companies can discount the amount of the loan. When the debtor is in danger of bankruptcy, the debt consolidator will buy the loan at a discount. A prudent debtor can shop around for consolidators who will pass along some of the savings. Consolidation can affect the ability of the debtor to discharge debts in bankruptcy, so the decision to consolidate must be weighed carefully.
Debt consolidation is often advisable in theory when someone is paying credit card debt. Credit cards can carry a much larger interest rate than even an unsecured loan from a bank. Debtors with property such as a home or car may get a lower rate through a secured loan using their property as collateral Then the total interest and the total cash flow paid towards the debt is lower allowing the debt to be paid off sooner, incurring less interest. In practice, many people are in credit card debt because they spend more than their income. If that habit continues, the consolidation will not benefit them much because they will simply increase their credit card balances again.
Because of the theoretical advantage that debt consolidation offers a consumer that has high interest debt balances, companies can take advantage of that benefit of refinancing to charge very high fees in the debt consolidation loan. Sometimes these fees are near the state maximum for mortgage fees. In addition, some unscrupulous companies will knowingly wait until a client has backed themselves into a corner and must refinance in order to consolidate and pay off bills that they are behind on the payments. If the client does not refinance they may lose their house, so they are willing to pay any allowable fee to complete the debt consolidation. In some cases the situation is that the client does not have enough time to shop for another lender with lower fees and may not even be fully aware of them. This practice is known as predatory lending Certainly many, if not most, debt consolidation transactions do not involve predatory lending.
In the United States, federal student loans are consolidated somewhat differently, as federal student loans are guaranteed by the U.S. government. In a federal student loan consolidation, existing loans are purchased and closed by a loan consolidation company or by the Department of Education (depending on what type of federal student loan the borrower holds). Interest rates for the consolidation are based on that year's student loan rate, which is in turn based on the 91-day Treasury bill rate at the last auction in May of each calendar year.
Student loan rates can fluctuate from the current low of 4.70% to a maximum of 8.25% for federal Stafford loans 9% for PLUS loans. The current consolidation program allows students to consolidate once with a private lender, and reconsolidate again only with the Department of Education. Upon consolidation, a fixed interest rate is set based on the then-current interest rate. Reconsolidating does not change that rate. If the student combines loans of different types and rates into one new consolidation loan, a weighted average calculation will establish the appropriate rate based on the then-current interest rates of the different loans being consolidated together.
Federal student loan consolidation is often referred to as refinancing, which is incorrect because the loan rates are not changed, merely locked in. Unlike private sector debt consolidation, student loan consolidation does not incur any fees for the borrower; private companies make money on student loan consolidation by reaping subsidies from the federal government.
Student loan consolidation can be beneficial to students' credit rating, but it's important to note that not all federal student loan consolidation companies report their loans to all credit bureaus; SLM Corporation (formerly Sallie Mae) does not report to Experian or Transunion which means that students will have differing credit scores at Equifax Transunion, and Experian.
Credit as a financial term, used in such terms as credit card refers to the granting of a loan and the creation of debt. Any movement of financial capital is normally quite dependent on credit, which in turn is dependent on the reputation or creditworthiness of the entity which takes responsibility for the funds.
A similar usage is in commercial trade where credit is used to refer to the approval for delayed payments for goods purchased. Sometimes if a person has financial instability or difficulty, credit is not granted. Companies frequently offer credit to their customers as part of the terms of a purchase agreement. Organizations that offer credit to their customers frequently employ a credit manager
Credit is denominated by a unit of account Unlike money (by a strict definition), credit itself cannot act as a unit of account. However, many forms of credit can readily act as a medium of exchange As such, various forms of credit are frequently referred to as money and are included in estimates of the money supply
Credit is also traded in the market The purest form is the "Credit Default Swap" market, which is essentially a traded market in credit insurance. A credit default swap represents the price at which two counterparties will exchange this risk — the protection "seller" takes the risk of default of the credit in return for a payment, commonly denoted in basis points (one basis point being 1/100 of a percent) of the notional amount to be referenced, while the protection "buyer" pays this premium and in the case of default of the underlying (a loan, bond or other receivable), delivers this receivable to the protection seller and receives from the seller the par amount ( i.e., is made whole).
Credit Education is the practice of providing consumers with information analyzing their credit behavior. Credit education is usually practiced by trained professionals knowledgeable in the analytics of the credit score and how consumer credit behavior effects both positive and negative credit eligibility. Credit education is usually assisted by sophisticated credit scoring models that mathematically assists the consumer, or counselor, in determining a credit improvement outcome.
Credit Education has become an increasingly practiced discipline due to sweeping increases in the use of the credit score and its affect on the prices consumers pay for loans, insurance, housing and utilities. It is also the major factor in loan eligibility.
Not to be confused with credit counseling credit education does not focus on debt counseling, nor involves the practice of collecting debt from consumers. Credit counseling and credit repair have consistently received negative publicity for its fee and management practices.
The largest suppliers for credit education data are Fair Isaac Corporation, CreditXpert and the three credit bureaus ( Experian, TransUnion and Equifax who deliver credit reports and credit scores. Among the largest providers of credit education services is Community Empower who, through the use of its own scoring models and national network of credit education counselors, provides consumers hands-on guidance using highly-trained local professionals.
Credit education has also received attention as a new discipline at the Community College level where new courses on the subject are being taught. Usually aligned with Mortgage Finance programs that teach college undergraduates principles of lending and underwriting credit education and credit recovery programs are giving students more extensive backgrounds in credit early in their careers. Among the early college level adoptors of credit education is the Los Angeles Community College District and Los Angeles Trade Technical College.
FICO is an acronym for Fair Isaac Corporation (traded publicly under the symbol FIC) and refers to the best-known credit score model in the United States, which is calculated using mathematical formulae developed by this company. The FICO score is primarily used in the consumer banking and credit industry. Banks and other institutions that use scores as a factor in their lending decisions may deny credit, charge higher interest rates or require more extensive income and asset verification if the applicants credit score is low.
FICO scores are designed to indicate the likelihood of a borrower being delinquent within the next 24 months. No public information is available to determine what the scores mean in terms of statistics. A separate score, BNI, is used to indicate likelihood of bankruptcy.
The three major credit reporting agencies (also often, but inaccurately referred to as credit bureaus) in the United States, Equifax, Experianand TransUnion calculate their own credit scores, which go by different trademark names as well as many different versions of the score (often differing because of what they are meant to predict and when they were written): Beacon, Beacon 96, and Pinnacle are all available only from Equifax; Empirica, Empirica Auto 95, Precision Score, and Precision 03 at TransUnion; and Fair Isaac Risk Score at Experian. These versions, while all developed for the agencies by Fair Isaac, differ and are periodically updated to reflect current consumer repayment behavior. The NextGen Scores are the most recent scores, but creditors vary in which version they prefer to use.
The scores use a multiple scorecard design. Each version uses 10 or more individual scorecards, and an individual is typically compared with similar others. (For example, a borrower with two 30-day late payments will be scored against a population with some minor delinquencies.) An individual is then graded according to what variables seem to indicate a repayment risk in that group. This feature may cause a borrower with delinquencies to score in the same range as a borrower without delinquencies.
Nearly all large banks also build and use their own proprietary statistical models for credit scoring purposes, often in conjunction with the FICO score or other outside scores.
The statistical models that generate credit scores are subject to federal regulations. The Federal Reserve Board's Regulation B, which implements the Equal Credit Opportunity Act, expressly prohibits a credit scoring model from considering any prohibited basis such as race, color, religion, national origin, sex, or marital status. Regulation B also stipulates that credit scoring models must be empirically derived and statistically sound. Furthermore, if an adverse action is taken as a result of the credit score ( e.g. an individual's application for credit is denied) then specific reasons for the denial must be provided to the individual. A statement that the individual "failed to score high enough" is insufficient; the reasons must be specific.
There exist several generally accepted algorithms for extracting the primary contributing factors to a low credit score. One or more of these algorithms is typically used to supply a list of reasons when a loan applicant has been denied credit, in order to satisfy the Regulation B requirement that specific reasons are disclosed. Some consumers feel these adverse action reasons are somewhat disingenuous, as the only determining factor for credit denials is a numeric score — the "reasons" are summed up only for the consumer.
Each of the credit reporting agencies has developed its own version of the credit score intended to compete with Fair Isaac's score. Although not as widely used, these scores (for example Trans Union's "TransRisk" score or Experian's "ScoreX" and "PLUS" scores) are less expensive than the FICO score. These scores are often derisively referred to by consumers and lenders as "FAKO" scores, for they do not use official Fair Isaac methodologies. The cost savings of a non-FICO score are tempting to some banks and credit card companies, who need an accurate risk assessment on millions of accounts every year. For ease of use, these scores tend to be mathematically scaled so that they fall in the same general range as the FICO score. Fair Isaac offers scoring models for the U.S ., Canada, and South Africa. It also offers a "Global FICO" for many other countries.
Credit scores are designed to measure the risk of default by taking into account various factors in a person's financial history. Although the exact formulae for calculating credit scores are closely guarded secrets, Fair Isaac has disclosed the following components and the approximate weighted contribution of each:
35% punctuality of payment in the past (only includes payments later than 30 days past due)
30% capacity used: the ratio of current revolving debt (credit card balances, etc.) to total available revolving credit (credit limits)
15% length of credit history
10% types of credit used (installment revolving consumer finance
10% recent search for credit and/or amount of credit obtained recently
The above percentages provide very limited guidance in understanding a credit score. For example, the 10% of the score allocated to "types of credit used" is undefined, leaving consumers unaware what type of credit mix to pursue. "Length of credit history" is also a murky concept; it consists of multiple factors - two being the oldest account open and the average length of time an account has been open. Although only 35% is attributed to punctuality, if a consumer is substantially late on numerous accounts, his score will fall far more than 35%. Bankruptcies, foreclosures, and judgments affect scores substantially, but are not included in the simplistic pie chart provided by Fair Isaac.
Further, Fair Isaac does not use the same "scorecard" for everyone. The scorecards are segmented so that there are over 100 different actual scoring models that are applied to different individuals based on different ranges of input values (some scorecard segmentations include: age, depth of credit history, etc.) The implications of this segmentation are that while the approximate weighted contribution above may be an average across all scorecards, individuals will receive different scores or weightings based on the scorecard segmentation that they fall into. Some consumers have noticed their scores decreasing by small amounts for no apparent reason.
Current income and employment history do not influence the FICO score, but they are weighed when applying for credit. For instance, an unemployed individual with no other sources of income will not usually be approved for a home mortgage, regardless of his or her FICO score.
There are other special factors which can weigh on the FICO score.
Any monies owed because of a court judgment, tax lien, or similar carry an additional negative penalty, especially when recent.
Having above a certain number of consumer finance company credit accounts also carries a negative weight (critics say that this causes a vicious cycle, locking people into continuing to use consumer finance companies).
The number of recent credit checks also can weigh down the score, although the credit agencies claim to allow for credit checks made within a certain window of time to not aggregate, so as to allow the consumer to shop around for rates.
A FICO score generally ranges from 300 to 850. It exhibits a left-skewed distribution with a US median around 725. 660 is generally regarded as potentially subprime and represents an important break point for credit worthiness. The performance of the scores is monitored and the scores are periodically aligned so that a credit grantor normally does not need to be concerned about which score card was employed.
Each individual actually has three credit scores for any given scoring model because the three credit agencies hold their own, independent databases. These databases are independent of each other and may contain entirely different data. Many lenders will check an applicant's score from each bureau and use the median score to determine the applicant's credit worthiness.
A new Vantage score has been offered by all three credit bureaus to creditors since spring 2006. It will soon be available to debtors. Its range is from 501 to 990. It is graded A (901-990), B (801-900), C (701-800), D (601-700), and F (501-600). It remains to be seen whether the Vantage Score will replace the FICO score or even be accepted by many creditors.
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it has become very easy to borrow loans these days. Advancements in technology particularly with the Internet have made it convenient for loan seekers to track the loan of their choice. With just a few clicks on a lender's website you can access the desired loan online. The ease with which loans are available online nowadays is the main reason behind the growing number of debt-related problems.
The vast number of loans taken on different occasions may have benefited you many times and may have even been a lifesaver in an urgent situation. However, you may not have known that these loans can pose a threat to you. Now you have to remember which lender to pay, how much and when. Failing to pay any of the installments on the loan may affect your credit score adversely. In such circumstances, debts become a burden. You may get into a life-long debt trap if you don't know how to handle these debts. A debt management program in such conditions can work as an effective debt management tool helping you in reducing the debt burden.
Here are a few debt management tips that can help you in managing your debts and getting your life back on the right track:
Create A Budget
An organized and well-planned budget can help you in keeping control over your monthly expenses. Write down each and every financial transaction you do each month; this will help you stay on track. It will give you a real idea of your finances and thus you can make the decision accordingly. A budget will give you an overview about how many funds you do have and how you are going to disburse the expenses with the available money. Setting up the budget is not enough: what is important is to stick to it.
Consolidate High Interest Loans
Consolidate your debts that carry a high rate of interest with a debt consolidation loan. A debt consolidation loan can work as an effective debt management tool. It will help you in getting rid of the debt burden by reducing the monthly outgoings. With a debt consolidation loan, you will get freedom from all the hassles involved in dealing with several creditors, you will be accountable to only one loan, one lender and one lower monthly installment.
Avoid taking on new credit
If you are already in a debt trap, avoid taking up a new loan. Borrowing a new loan may be of great help to you, but it will be in the short term. It may increase the debt burden and will add to your troubles rather then solving them.
Debt Management Counseling
You can also seek for advice from debt management counselors. The majority of the lenders in the US engage debt management counselors who have years of experience and can provide you with an easy road map to get rid of the debt trap by paying off the existing debts.
Learn To Save
A need for a loan arises when you do not have sufficient funds in your saving account to meet your personal desires. Make saving a habit, try not to overspend on unnecessary things. No, don't become a miser but use the funds carefully, a little sum of money saved today will be highly beneficial for you in the future and will make it easy for you to deal emergency cash need with the available funds on the right time and in the right manner.
Debt management is a time-consuming process. You can save your time and hard-earned money by employing a debt management company who will take care of your debt and can offer effective solutions to all your debt-related problems.
Tips for managing debts employed in the right manner can curb the menace created by debts, helping you get out of debt in an easier way. Paying off the existing debts will help you in securing a smoother and easier life for the future
it has become very easy to borrow loans these days. Advancements in technology particularly with the Internet have made it convenient for loan seekers to track the loan of their choice. With just a few clicks on a lender's website you can access the desired loan online. The ease with which loans are available online nowadays is the main reason behind the growing number of debt-related problems.
The vast number of loans taken on different occasions may have benefited you many times and may have even been a lifesaver in an urgent situation. However, you may not have known that these loans can pose a threat to you. Now you have to remember which lender to pay, how much and when. Failing to pay any of the installments on the loan may affect your credit score adversely. In such circumstances, debts become a burden. You may get into a life-long debt trap if you don't know how to handle these debts. A debt management program in such conditions can work as an effective debt management tool helping you in reducing the debt burden.
Here are a few debt management tips that can help you in managing your debts and getting your life back on the right track:
Create A Budget
An organized and well-planned budget can help you in keeping control over your monthly expenses. Write down each and every financial transaction you do each month; this will help you stay on track. It will give you a real idea of your finances and thus you can make the decision accordingly. A budget will give you an overview about how many funds you do have and how you are going to disburse the expenses with the available money. Setting up the budget is not enough: what is important is to stick to it.
Consolidate High Interest Loans
Consolidate your debts that carry a high rate of interest with a debt consolidation loan. A debt consolidation loan can work as an effective debt management tool. It will help you in getting rid of the debt burden by reducing the monthly outgoings. With a debt consolidation loan, you will get freedom from all the hassles involved in dealing with several creditors, you will be accountable to only one loan, one lender and one lower monthly installment.
Avoid taking on new credit
If you are already in a debt trap, avoid taking up a new loan. Borrowing a new loan may be of great help to you, but it will be in the short term. It may increase the debt burden and will add to your troubles rather then solving them.
Debt Management Counseling
You can also seek for advice from debt management counselors. The majority of the lenders in the US engage debt management counselors who have years of experience and can provide you with an easy road map to get rid of the debt trap by paying off the existing debts.
Learn To Save
A need for a loan arises when you do not have sufficient funds in your saving account to meet your personal desires. Make saving a habit, try not to overspend on unnecessary things. No, don't become a miser but use the funds carefully, a little sum of money saved today will be highly beneficial for you in the future and will make it easy for you to deal emergency cash need with the available funds on the right time and in the right manner.
Debt management is a time-consuming process. You can save your time and hard-earned money by employing a debt management company who will take care of your debt and can offer effective solutions to all your debt-related problems.
Tips for managing debts employed in the right manner can curb the menace created by debts, helping you get out of debt in an easier way. Paying off the existing debts will help you in securing a smoother and easier life for the future
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Often we forget the little guy, the SMB, in our discussions of the comings and goings of the Internet marketing industry. Sure there are times like this when a report surfaces talking about their issues and concerns but, for the most part, we like to talk about big brands and how they do the Internet marketing thing well or not so well.
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Affiliate Marketing is a performance based sales technique used by companies to expand their reach into the internet at low costs. This commission based program allows affiliate marketers to place ads on their websites or other advertising efforts such as email distribution in exchange for payment of a small commission when a sale results.
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How To Make money with affiliate programs Today. Affiliate marketing is the easier and probably the most effective method to make money from the internet. It is basically, a kind of selling technique where potential buyers from your website are directed to the websites of sellers. For every click, the website owner gets a small commission.
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