What is credit crunch and can data analytics prevent it?

What is credit crunch and what causes it? How can financial institutions make better, data-driven decisions to avoid this scenario? 

In this article, we’re taking a close-up look at the factors leading to a credit crunch, with the credit crunch of 2008 as a flagship example, the consequences a credit crunch may have and how data analytics can help minimise this risk. 

What is credit crunch? 

A credit crunch, also known as credit squeeze, credit tightening or credit crisis, is an economic situation when financial institutions reduce their lending activity or tighten up the requirements for obtaining a loan, making loans less available.  

A credit crunch often happens in times of recession, when investment capital is hard to secure. Banks are cautious with lending money to borrowers who may default at any time. This risk translates into higher interest rates. The result is that businesses who could formerly obtain a loan with no problem, suddenly cannot get it. No extra funds mean no extra investments, and in the long run – a plateau in the economic growth felt throughout the whole economy.  

Is credit crunch the same as a recession? 

No, a credit crunch is not the same as a recession, although both have a negative impact on the economy.  

The difference between a credit crunch and a recession is that the latter refers to a general decline in economic performance, which continues for two consecutive quarters and occurs when there’s a decrease in spending.  

A credit crunch may eventually lead to a recession. If businesses can’t gain extra funds for planned investments, they start cutting on all their expenses, including the employment budget. The uncertainty leads to the decline of productivity and the rise of unemployment.  If that continues for a longer time, the general economic activity gets a hit, and a recession gains momentum. 

What causes credit crunch? 

A credit crunch occurs when financial institutions grant loans to borrowers with a low credit rating and a doubtful ability to repay. In other words, it’s caused by inappropriate or even lenient lending. This is a straight path to a rising default rate and bad debt that lead to losses for financial institutions. In extreme cases, banks may even become insolvent.  

Why then, banks get so careless in lending money to debtors who cannot repay? There may be a couple of reasons for that:   

• bad estimation of debtors’ creditworthiness,  
• anticipated decline in the value of the collateral used by the banks to secure the loans,  
• a change in monetary conditions, for example as a result of raising reserve requirements or imposing new regulatory constraints on lending by a central bank,  
• credit controls imposed by a central government on the banking system,  
• an increased risk to solvency of other banks within the banking system. 

What caused the 2008 credit crunch? 

The 2008 credit crunch was caused by the lenient lending standards causing an increase in mortgage defaults.

The background for it was the rise of real estate prices that reached its peak in 2006. Buyers were afraid that the prices would never stop increasing and jumped to buy houses. 

To take advantage of this boom, banks offered subprime mortgages, that is mortgages issued to borrowers with low creditworthiness. After 2-3 years borrowers started to default, the value of real estates began to fall and banks noted huge losses. The Great Recession was sparked worldwide. 

You can learn more about the background of the 2008 credit crunch in the UK from this article in the Guardian. 

What are the effects of a credit crunch? 

The biggest consequence of a credit crunch is, as we already mentioned, a recession. Higher borrowing costs, caused by an increased interest rate, lower people’s ability to buy goods, and thus slows down the economy. 

From an individual consumer’s perspective, the effects of a credit crunch are far more severe. As their employers struggle to stay afloat cutting all the expenses, including the workforce, their jobs are at threat. The unemployment rate rises and social unrest increases.  

How to make wiser credit rating decisions? 

The phenomenon of a credit crunch shows the importance of data analytics in making credit rating decisions. Accurate risk assessment is key.  

Combining a variety of up-to-date data on a debtor’s life situation and their credit history into insightful reports is vital to single out at-risk borrowers. This is something a smart debt management platform can help you with.  

DebtPro is one of such solutions. It gives you advanced analytics and reporting functions allowing you to make decisions backed by data and get insights about your debt collection process, such as average cycle length, costs, or arrears. These insights can help you hone or reshape your debt collecting strategy in order to minimise the risk and increase the effectiveness of debt collection.  

Read about DebtPro’s features in more detail and book a free demo >>