Confidence interval for the  financial sector: …a measurement paradox

 In my previous articles about the collapse of the seven universal banks namely UT, Capital, BEIGE, Sovereign, Construction, UniBank, and Royal Bank, I had mentioned the role of the auditors’ independence risk to address how it happened.  Dodoo and Simons (2018) have also discussed why this happened in their article titled “Banking Sector Crisis: Cleaning the Financial Sector Through Standards.” In the same newspaper published on October 12, 2018, I suggested the reasons to address the question who made it happen with my article titled “Financial Entrepreneurs: Capabilities and Ponzi Scheme. This article is aimed at addressing the question “Where it happened?”

The Governor of the Bank of Ghana comment in debunking the assertion that there is no banking crisis in Ghana as alluded to by Dodoo and Simons (2018). Dr. Ernest Addison mentioned that:

When people talk about the banking crisis, then it is an exaggeration. 90% of the industries are operating as normal. That I think is a message that has not been properly articulated. Secondly, also, the local indigenous banks are relatively stable. The indigenous banks that are having problems are those that are perceived to be badly managed with major corporate governance issues, so the industry is fairly robust.

.Therefore, there is no financial crisis as other financial experts have mentioned and providing various ways to handle this crisis. The Governor mentioned the rate of 90% of the financial institution operating as normal triggered my mind to statistics on the topic CONFIDENCE INTERVAL (CI) and Significance Interval. These two elements are critical in giving ASSURANCE. Most decisions are made based on these.

Confidence interval talks about the accuracy of the population mean, and the significance level helps in determining the decision rule to rejecting the null hypothesis. The null hypothesis is a general knowledge known unless there is an alternative. The decision is that reject the null hypothesis when the resulted figure is greater than the critical value. Once the hypothesis is rejected, then we accept the alternative hypothesis.

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The significance level and the confidence interval are inversely related. The formula for significance level (  ) = 1 – CI. It gives the P-value or the critical value that will be used in the decision making. I have shown this in order to address the 90% rate given by the Governor of the Bank of Ghana and its interpretation to the financial industry on whether it is in crisis or not and why Ponzi schemes are happening in Ghana.

If we based our confidence interval on 90% for normal operating banks, therefore, the significance level will be  (  ) = 1 – 0.9 = .10. In analyzing the Governor’s statement, less than 10% failure of the existing banks does not mean there is a financial crisis. In principle the smaller the significant level, the better the confidence interval which means that, the greater the ASSURANCE of the financial industry. Noticing the impact of financial failures on the citizens and the economy, the significant level must be better set at 1% or 5% or confidence interval of 99% or 95%. A 90% confidence interval or a significant level of 10% will indicate the financial crisis and a loss of confidence in the industry with a more significant impact on the economy as we are currently experiencing.

In 1997, a legalized Ponzi Scheme caused the Albania government to collapse. The citizens invested in the scheme because the government endorsed and invested in these firms which were operating these Ponzi schemes. It caused mass unrest, and more than 2,000 people died as a result of it. Until the International Monetary fund stepped in to help, approximately $1.2billion had been lost. It happened because of the government’s assurance upon a the low-level confidence interval in the industry that gave room to Ponzi scheme operators. It resulted in the payment of high-interest rate and promotion of instant wealth.

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Any country which has a low confidence interval will promote the existence of legalized ponzi schemes. It is because the failure of these Ponzi schemes will be seen to be within the accepted normal distribution or range of normal operation. As the significance level for medicine production or health institutions operation are set at 1% or a confidence interval of 99%, so must the financial sector. The impact of the failure of the wrong medication will be the same as financial sector failure. They will all lead to death.

I recommend that BOG revisit their set level of confidence and significance level to prevent the establishment of Ponzi schemes in Ghana. This article support Dodoo and Simons (2018) recommendation that standardization is the best way to eliminate financial crisis as noted by the International Organization of Standardization (ISO).  A further commendation is for a financial institution to use Six Sigma approach in eliminating the waste in their operations. Six Sigma provides a statistical approach to improving the capabilities of the business process. It occurs when no defects are expected in 99.99966% of all chances of financial industry operations.


Dodoo, A. & Simons, B. (2018, October 12). Banking Sector Crisis: Cleaning the Financial Sector Through Standards. Business & Financial Times, p. 12.

The writer is a Ph.D. in Commerce candidate (majoring in Accounting and Finance)

of  the Adventist University of the Philippines.Putting Kahoy, Silang, Cavite, Philippines


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