What is a Loan Stress Test?
A loan stress test is an analysis or simulation designed to determine the ability of a given financial institution or a private borrower to deal with a recession or a financial market crisis.
Historically, we’ve dealt with numerous crises like the Great Depression, the Dotcom bubble, and the Global Financial Crisis of 2008. The stress tests became more common after the latter, the 2008 Global Financial Crisis. The crisis was aggravated when thousands of households were unable to make their mortgage payments and were forced to default on their loans.
The ripples of the meltdown were felt in virtually all of the sectors of the economy. Now, to minimize their exposure to risk, lenders follow a set of strict rules to determine a borrower’s creditworthiness. The lenders want to make sure the borrower is still able to afford their loan payments when unforeseen events take place.
Bank Stress Test Example
Financial institutions in Canada are federally regulated and are bound to a certain set of rules and regulations. The Framework for Risk Identification and Assessment (FRIDA) is used to assess how the financial institutions would perform in a major adverse scenario as mentioned above. In collaboration with the International Monetary Fund (IMF), Canada developed a three-year adverse scenario in 2018 to assess the financial institutions’ ability to withstand and manage major financial shocks.
In order to be more resilient to an adverse scenario, the banks must maintain their capital reserves and debt-to-equity ratio at certain levels. Banks, in turn, stress test borrowers that, for example, are looking to obtain a mortgage to purchase a house.
Mortgage Stress Test Example
With historically low interest rates, more people are able to take out loans and afford to buy a property. Some borrowers pose more risks than others based on their assets, liabilities, earnings, etc.
Just like banks, private borrowers need to go through a stress test to assess their solvency. With a mortgage test, banks simulate scenarios to see if a borrower is able to make their mortgage payments in case there is financial turmoil, the interest rates go up, or any other event that could potentially decrease the borrower’s purchasing power.
New rules passed by Canada’s federal financial regulator in 2018 mean that more borrowers would need to pass the stress test. For a borrower to pass the mortgage stress test, they must qualify at their contracted mortgage interest rate plus 2% or the current five-year benchmark rate of the Bank of Canada. The Canadian central bank’s current five-year benchmark rate is 4.79%.
For example, if a homeowner is applying for a mortgage at a rate of 4.00%, the lender will assess the borrower’s as if they were repaying a home loan at 6.00% (4.00% + 2%) since 6.00% is greater than the Bank of Canada’s five-year benchmark rate.
In reality, if the homeowner wants to borrow $600,000 and the bank is offering a rate of 4.0%, they must prove that they can afford a mortgage payment of about $3,000 per month (at 6.0%), even though their actual monthly mortgage payment (at 4.0%) would be $2,000. Such a requirement makes it tougher for first-time homebuyers because they can borrow less than expected, having now to re-think their purchase or settling for another, less expensive home.
Lenders don’t need to apply the stress test to borrowers who are renewing their existing mortgages. However, there are still some negative consequences for existing borrowers. If they fail the stress test, they will not be able to shop around for better rates and will be stuck with their current lender.
To pass the stress test, a borrower must show that they’ve increased liquidity, which entails larger savings, smaller debt obligations – such as a car, phone, credit card payments – and anything else that would mitigate the impact of an unforeseen financial downturn.
CFI offers the Certified Banking & Credit Analyst (CBCA)® certification program for those looking to take their careers to the next level. To keep learning and developing your knowledge base, please explore the additional relevant resources below: