- Marwan ElEskandarani
How the CBE’s New Regulation Will Affect SMEs, Banks, & the Entire Economy
Updated: Oct 24, 2021
New regulations, they come and go, and most of us have no control over them. We can only comply and hope that we – and our businesses – can cope with such changes without too much trouble and hopefully with some substantial gains in our bank accounts for us and our companies.
Pioneering these important and critical changes is the Central Bank of Egypt (CBE). The CBE’s decisions can affect entire economies and nations. This ensures that all decisions undergo a rigorous examination and validation process to ensure that Egypt is following the latest international trends in the financial world and also that it makes sense in the local context.
Recently, the CBE issued `a new regulation that can single handedly propel the business ecosystem light years forward, granted that it is integrated correctly.
What is the Decision?
The new regulation states that banks are finally able to use behavioral and generally alternative data instead of traditional data provided by companies to assess the credit worthiness of an SME applying for a loan.
If you are a bank or a business owner, this is big news that could potentially allow for the creation of endless new opportunities for both parties.
Alternative & Behavioral Data
By definition, alternative data is data that is not traditionally used for analysis or assessments. The question remains, what will be used to assess credit worthiness.
The undiplomatic answer is that it depends on what you have, but it can vary from:
Industry data that the company is operating in (business opportunities, market growth, etc.
Business processes including credit/debit, web data, public data, email/consumer receipts
Number of employees, their functions, their responsibilities, their education level
Social sentiment through web listening and data scraping
Telecom data
Social media data
However, even with the exponential rise of created data on a second-by-second basis and the increased computational power at our disposal, the usage of traditional data will not be thrown to the side completely.
Traditional data also plays an important role in determining the credit worthiness of any SME since the machine learning model assigns different weights to all different features or components that determine the success or failure of any SME applying for a loan. These factors can change all the time and that is why they must be included within the model for analysis.
The Current Loan Status
Let us say one SME wants to build a plant and the other wants to import raw materials for a specific project, although one is a long-term investment and the other is a short term one; banks more or less require the same types of reports to accept or reject the loan application.
Typically, banks would thoroughly examine a company’s balance sheets & financial statements to extract several pieces of information such as projections and ratios (leverage, debt to equity, etc.), and the current management in place; at times, banks could require the owners to sign documents binding them to the position for the duration of the loan.
This can be an area of concern. But why is that?
You need to ask yourself if these data enough to truly assess the risk at hand? Are these leading factors that predict the success of that company in its respective market?
Well, sometimes it seems to be true, but the majority of the times these assessments can lead to defaults and Non-Performing Loans (NPLs).
The Opportunity for Banks
To all banks, bankers, credit officers, and risk analysts, this part is specifically written for you.
Because we’re a data science company, we believe in the facts & figures; currently in the Egyptian market, there are more than 1.7 million SMEs in operation (not counting those that are launching everyday), and the numbers report that around 40% of those have unmet needs which can include (slow transactions, high transactional fees, bad terms for the SMEs, etc.) while 70% of SMEs don’t even go in for that loan request, which can truly hinder the progress of companies which form the backbone of the economy.
By doing some simple math, if the average loan size is EGP 60 million, that means banks are missing out on a whopping EGP 71.4 billion (assuming that the 70% of SMEs that don’t request loans suddenly decide to apply for loans.)
It doesn’t need a statistician or mathematician to know how substantial this is.
The Opportunity for SMEs
As for the SMEs, now is the time to leave your worries behind if -for now- your ratios aren’t what banks and risk analysts are looking for and you think that you won’t be able to finance your new projects and ideas because -drumroll please- that maybe isn’t what the main factor of your success relies on.
With new features being examined, fairer credit worthiness assessments, faster turnaround times, and better terms, now more than ever is the time for the SME ecosystem to flourish & blossom into what it originally was meant to be. The powerhouse of the economic system, the backbone of innovation, and the breeding ground for pioneering new tech for the masses.
What Should You Do As An SME?
There are 2 sides to this question.
If you are an SME looking for a loan; I believe that all banks in the coming future will be well-equipped with the necessary tools to accurately and quickly assess the creditworthiness of your company so that you could further fuel your business and truly grow.
What Should You Do As A Bank?
If you are a bank, then it is time to equip yourself with the necessary tools to expedite your credit decision turnaround time, reduce your defaults and NPLs, and be at the forefront of financial innovation.
This includes:
Cleansing and wrangling the data that exists within the databases
Exploring and ensuring that the data collected covers the essential features and dimensions
Assigning the right teams to tackle the problem (this includes mathematicians, statisticians, engineers, and computer scientists)
Assigning the right project manager and business consultant to head the project – this individual needs to be tech savvy while also understand the business inside and
Preparing the internal teams to new possible changes to the current operations
Conclusion
At Synapse Analytics, we have a team of mathematicians, statisticians, computer scientists, and consultants ready at a moment’s notice to tackle these problems through a mixture of our products and services.
Our extensive knowledge of the credit scoring and creditworthiness applications across both consumer finance and banking institutions allow us to utilize our know-how across different use-cases.
Favorite Quote of the Week
“Data is a precious thing and will last longer than the systems themselves.” - Tim Berners-Lee
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