Steps To Take When Applying For Secured Loans
Whatever you’re thinking of financing with a secured loan, the UK’s specialist lending market is becoming more diverse all the time. From urgent one-off costs to planned purchases and investments, there are secured loans available to suit all requirements and budgets.
In this article, we’ll be taking a look at the seven steps every responsible borrower should take when applying for a secured loan.
1. Check your credit score
Some lenders issue secured loans without taking credit scores into account. If you can provide sufficient collateral to cover the cost of the loan, your credit history may be deemed irrelevant. However, many secured lenders continue to impose credit checks as a standard part of the application process. It’s therefore advisable to check your credit score before applying, in order to know exactly where you stand.
2. Consider your equity and assets
If you intend to secure a loan against your assets or equity, you’ll need to determine exactly how much they’re worth. This could involve organising a formal property valuation, which will need to be approved by the lender. Bear in mind that you’ll only be able to borrow against the value of your property you own outright - not the outstanding balance on your mortgage.
3. Work out how much you can afford
Use an online secured loan calculator to explore the various options and see how much you can afford to borrow. Experiment with different loan amounts, different repayment periods and so on, which will give you an idea of the overall borrowing costs and the affordability of the loan you need.
4. Compare the market
The fastest, easiest and most effective way to compare the market is to join forces with an independent broker. Finding the best secured loan deals on the market typically means setting your sights beyond the High Street. There’s an extensive network of independent specialist lenders operating in the UK, which in some instances can only be accessed with the support of a broker. Submit your requirements, your preferences and your budget to an experienced broker, rather than approaching a single lender directly.
5. Carefully consider all terms and conditions
Bear in mind that you’re under no obligation to go ahead at any time, right up until you sign the final loan agreement. Even in time-critical situations, it’s a good idea to take the time to study the terms and conditions in full, consider your requirements once again and ensure you’re doing the right thing. You run the risk of losing your property and/or assets if you fail to repay the loan as agreed, so it’s never worth rushing into a secured loan agreement. If in doubt, consult with your broker and ask as many questions as necessary.
6. Complete and submit your application
The importance of checking and re-checking all aspects of your loan application cannot be overstated. Any errors or omissions (minor or otherwise) could invalidate your application and affect your future eligibility with the same lender. Carefully check your application before submission, ensuring you provide any supporting documentation as requested by the lender.
7. Consider early repayment where possible
Last but not least, there’s typically a clause in most secured loan agreements that allows for early repayment. The difference being that while some lenders encourage early repayment with heavily reduced borrowing costs, others impose penalties and levies for repaying loan balances early. If you intend to repay your loan as early as possible - which is usually advisable - it’s worth checking the respective lender’s policies ahead of time. Again, ideally under the supervision of an independent broker.
Data Science in Finance: 9-Book Bundle
Master R and Python for financial data science with our comprehensive bundle of 9 ebooks.
What's Included:
- Getting Started with R
- R Programming for Data Science
- Data Visualization with R
- Financial Time Series Analysis with R
- Quantitative Trading Strategies with R
- Derivatives with R
- Credit Risk Modelling With R
- Python for Data Science
- Machine Learning in Finance using Python
Each book includes PDFs, explanations, instructions, data files, and R code for all examples.
Get the Bundle for $39 (Regular $57)Free Guides - Getting Started with R and Python
Enter your name and email address below and we will email you the guides for R programming and Python.