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Advance Rate Definition
An advance rate is a percentage of the value of the collateral set by the lender, up to which the lender agrees to extend the loan amount. When a lender provides a loan against collateral that has a fluctuating value, the lender needs a predetermined advance rate to protect themselves from loss. Depending on the advance rate, the borrower decides what collateral to be provided to secure the desired amount of loan.
A Little More on What is Advance Rate
Lenders accept collateral as a security for a loan to reduce the loss exposure. If the borrower fails to repay the loan, the lender can sell that asset to recover the loss. The loans with collateral are offered at a much lower rate than the unsecured loans.
If the asset that is being provided has a fluctuating value, the lender set an advance rate to minimize the risks such as the depreciation of the collateral. If the borrower fails to repay the loan and the value of the collateral reduces, the advance rate ensures the lender can still recover the principal amount of the loan by selling the collateral.
For example, let’s assume the advance rate of a loan is set as 90% by the lender. Now, if the borrower provides the collateral the value of with is $10,0000, the maximum loan the borrower will receive against that collateral is $90000.
The common collateral that is used in securing loans is automobiles, insurance policies, cash accounts, real estates, future payments and machinery, and equipment. Some of these collaterals have depreciating value. The advance rate protects the lender against that value fluctuation.
The lender analyzes the financial condition of the borrower before determining the advance rate. The ability of the borrower to repay the loan is assessed. Usually, the borrower’s credit risk is calculated by the lender using “the five Cs” framework- Credit history of the applicant, applicant’s capacity to repay, capital of the applicant, conditions of the loan and the collateral.
After analyzing and assessing the applicant’s credit risk, the advance rate is determined by the lender. If the present collateral doesn’t cover the required loan amount, the borrower either have to compromise with a lower amount or needs to provide some other collaterals.
Reference for “Advance Rate”
Academics research on “Advance Rate”
The Determinants of Deposit‐Rate Setting by Savings and Loan Associations, Goldfeld, S. M., & Jaffee, D. M. (1970). The Determinants of Deposit‐Rate Setting by Savings and Loan Associations. The Journal of Finance, 25(3), 615-632.
Loan sharks, interest-rate caps, and deregulation, Mayer, R. (2012). Loan sharks, interest-rate caps, and deregulation. Wash. & Lee L. Rev., 69, 807.
The Federal Home Loan Bank System: The Lender of Next‐to‐Last Resort?, Ashcraft, A., Bech, M. L., & Frame, W. S. (2010). The Federal Home Loan Bank System: The Lender of Next‐to‐Last Resort?. Journal of Money, Credit and Banking, 42(4), 551-583. The Federal Home Loan Bank (FHLB) System is a large cooperatively owned government‐sponsored liquidity facility that lends predominately to U.S. depository institutions. This paper documents the significant role played by the FHLB System at the outset of the recent financial crisis and provides evidence on the uses of FHLB funding by member banks and thrifts during that time. We then compare lending activity by the FHLB System and the Federal Reserve during 2007 and 2008, discuss the types of institutions seeking government‐sponsored liquidity at various times, and identify the trade‐offs faced by borrowers eligible to tap liquidity from both facilities.
An overview of project finance binomial loan valuation, Winsen, J. K. (2010). An overview of project finance binomial loan valuation. Review of Financial Economics, 19(2), 84-89. Setting project financing parameters, such as the loan to valuation ratio, loan interest rate, repayment schedules, and fees, requires detailed modelling of the resulting credit risk in a non-recourse setting. Structured credit risk models, based on the early work of Merton, have been developed in continuous time which can assist with project financing structuring. These models require a level of mathematical sophistication that may not always be available to those undertaking project financing analysis. This note provides an overview of a discrete time binomial approach to structural credit risk modelling, which enables project financing analysts a more accessible tool to evaluate project loan structures.
A model to analyse financial fragility: applications, Goodhart, C. A., Sunirand, P., & Tsomocos, D. P. (2004). A model to analyse financial fragility: applications. Journal of Financial Stability, 1(1), 1-30. The purpose of our work is to explore contagious financial crises. To this end, we use simplified, thus numerically solvable, versions of our general model [C.A.E. Goodhart, P. Sunirand, D.P. Tsomocos, A Model to Analyse Financial Fragility, Oxford Financial Research Centre Working Paper No. 2003fe13, 2003]. The model incorporates heterogeneous agents, banks and endogenous default, thus allowing various feedback and contagion channels to operate in equilibrium. Such a model leads to different results from those obtained when using a standard representative agent model. For example, there may be a trade-off between efficiency and financial stability, not only for regulatory policies, but also for monetary policy. Moreover, agents who have more investment opportunities can deal with negative shocks more effectively by transferring ‘negative externalities’ onto others.