A central bank is the prime monetary body in a country that oversees the regulation of the monetary policy as well as the functioning of all other banks. A central bank function in the same way as a normal bank does, the difference being the fact that it lends to other financial institutions rather than to the public, and the fact that it has the authority to print the currency.
Central banks are non-commercial banks and do not deal with the public directly. However, the aim of central banks is to facilitate spending and saving of the consumers. Central banks work independently of the government.
Central banks have the sole authority to print currency. This means that the currency published by the central banks cannot be rejected for payment by the citizens of the country. Any currency bill that is used to make a payment is backed by the central banks claim about the value of that bill.
Any mode of payment that is deemed acceptable by the central banks cannot be rejected as payment by anyone in the country.
The central bank has the responsibility of regulating the financial sector. It performs the following functions:
If money is printed beyond the permissible level, then it can lead to inflation in an economy which leads to severe downturns in the economy.
For instance, when the government wants to decrease the money supply in the market, then they can sell government bonds. As people purchase these bonds, they are left with left disposable cash. Alternatively, when the government wants to increase the money supply, then they can buy back these bonds from the market, thereby increasing the disposable cash in the hands of the people.
These open market operations are done to influence the interest rates in the economy. This happens through the monetary transmission mechanism. As bonds are released into the market, their price falls. Due to their inverse relationship with prices of bonds, interest rates rise. Therefore, central banks can control interest rates through open market operations
Central banks also make sure that commercial banks do not fall short of capital. They lend to commercial banks at an interest rate which is called the repo rate. Because of this reason, they are called the “lender of the last resort”. Conversely, the rate at which commercial banks lend to the central bank is called the reverse repo rate.
Image Source: ©Kalkine Group
One of the first financial institutions recognized as a central bank was the Swedish Riskbank. This was formed as a joint stock company with the primary purpose to lend government funds and act as a clearing house. Following this, central banks were formed for the issuing of currency and to purchase the government debt.
Most of these early institutions were private entities financing government debt. These central banks also provided loans to other banks and thus gained a position as the lender of the last resort. They held deposits of other banks as well, which helped them provide loans to other banks. These roles were limited to lending in times of need and did not include other macroeconomic positions like maintaining inflation levels and monetary expansion, etc.
The roles associated with central banks started to take a defining shape post World War I. When countries had to manage the problems on unemployment, inflation, they decided to expand the functions of the central bank.
What is Data Mining? Data mining is a process that facilitates the extraction of relevant information from a vast dataset. The process helps to discover a new, accurate and useful pattern in the data to derive helpful pattern in data and relevant information from the dataset for organization or individual who requires it. Key Features of data mining include: Based on the trend and behaviour analysis, data mining helps to predict pattern automatically. Predicts the possible outcome. Helps to create decision-oriented information. Focuses on large datasets and databases for analysis. Clustering based on findings and a visually documented group of facts that were earlier hidden. How does data mining work? The first step of the data mining process includes the collection of data and loading it into the data warehouse. In the next step, the data is stored and managed on cloud or in-house servers. Business analyst, data miners, IT professionals or the management team then extracts these data from the sources and accordingly access and determine the way they want to organize the data. The application software performs data sorting based on user’s result. In the last step, the user presents the data in the presentable format, which could be in the form of a graph or table. Image Source: © Kalkine Group 2020 What is the process of data mining? Multiple processes are involved in the implementation of data mining before mining happens. These processes include: Business Research: Before we begin the process of data mining, we must have a complete understanding of the business problem, business objectives, the resources available plus the existing scenario to meet these requirements. Having a fair knowledge of these topics would help to create a detailed data mining plan that meets the goals set up by the business. Data Quality Checks: Once we have all the data collected, we must check the data so that there are no blockages in the data integration process. The quality assurance helps to detect any core irregularities in the data like missing data interpolation. Data Cleaning: A vital process, data cleaning costumes a considerable amount of time in the selection, formatting, and anonymization of data. Data Transformation: Once data cleaning completes, the next process involves data transformation. It comprises of five stages comprising, data smoothing, data summary, data generalization, data normalization and data attribute construction. Data Modelling: In this process, several mathematical models are implemented in the dataset. What are the techniques of data mining? Association: Association (or the relation technique) is the most used data mining technique. In this technique, the transaction and the relationship between the items are used to discover a pattern. Association is used for market basket analysis which is done to identify all those products which customer buy together. An example of this is a department store, where we find those goods close to each other, which the customers generally buy together, like bread, butter, jam, eggs. Clustering: Clustering technique involves the creation of a meaningful object with common characteristics. An example of this is the placement of books in the library in a way that a similar category of books is there on the same shelf. Classification: As the name suggests, the classification technique helps the user to classify and variable in the dataset into pre-defined groups and classes. It uses linear programming, statistics, decision tree and artificial neural networks. Through the classification technique, we can develop software that can be modelled so that data can be classified into different classes. Prediction: Prediction techniques help to identify the dependent and the independent variables. Based on the past sales data, a business can use this technique to identify how the business would do in the future. It can help the user to determine whether the business would make a profit or not. Sequential Pattern: In this technique, the transaction data is used and though this data, the user identifies similar trends, pattern, and events over a period. An example is the historical sales data which a department store pulls out to identify the items in the store which customer purchases together at different times of the year. Applications of data mining Data mining techniques find their applications across a broad range of industries. Some of the applications are listed below: Healthcare Education Customer Relationship Management Manufacturing Market Basket Analysis Finance and Banking Insurance Fraud Detection Monitoring Pattern Classification Data Mining Tools Data mining aims to find out the hidden, valid and all possible patterns in a large dataset. In this process, there are several tools available in the market that helps in data mining. Below is a list of ten of the most widely used data mining tools: SAS Data mining Teradata R-Programing Board Dundas Inetsoft H3O Qlik RapidMiner Oracle BI
Earmarking is a term used in the banking industry to refer to funds, which has been set aside to pay for some specific projects. The term is usually associated with transactions as well as earmarked transactions, which could be defined as the business transaction, made to claim any pre-allocated fund to meet the expenditure.
An earnings announcement is a public statement of a company’s earnings, usually done on a periodic basis. These official announcements are released quarterly or yearly to inform the investors and the market about a company’s financial performance. Companies announce their financial reports through press releases on their websites and list them on the stock exchanges website. After the information is released through a conference call, there is a question-and-answer round with the senior management in which analysts, media, and investors can participate. On the basis of the report, analysts then incorporate earning measures such as EPS (Earning Per Share). These reports help investors in making sound investment decisions. Earnings results are announced during the earnings season on a date chosen by the company. Stock prices of the companies take a swing before and after the company releases its earnings report. Equity analysts also predict earnings estimates through their analysis which drives stock prices movement due to speculations. Stock prices even move after the earning results are declared, up or down, depending on how the results have turned out. Source: Copyright © 2021 Kalkine Media Pty Ltd. When are earning announcements made? It is mandatory for every listed company to report its quarterly financial results in the US but not in Australia. In Australia, companies release their financial report on a semi-annual basis. Having said that, many Australian companies also update their shareholders quarterly, but these are not considered official earnings. These quarterly reports are released to satisfy the market demand for information and to disclose the company’s guidance on its performance. The financial calendar varies from country to country and therefore, the earnings season changes as well. In the US, the earnings season starts after the final month of the financial quarter. Usually, American companies start posting their earnings reports in January, April, July, and October. In Australia, companies report twice a year, usually around February and August, or May and October. It depends upon the company’s financial cycle. However, whether quarterly in the US or semi-annually in Australia, these earnings results are required as agreed while listing the company with the stock exchanges. Source: Copyright © 2021 Kalkine Media Pty Ltd. Why are earnings announcements necessary? Financial results help investors, media, and other stakeholders of the company to have a greater understanding of the company’s financial footing. Companies not just provide sales, operating profit, net profits, but also offer guidance and outlook for coming months. Additionally, these reports also have senior management statements directed at the market. Therefore, earning announcements act as an informative document for the investors and analysts to study and gauge a company’s performance. Analysts can provide earnings estimates, and investors can then take wise investment decisions. These documents are also vital for companies when it comes to seeking funding for the business. Financial institutions can also judge a company’s financial health by evaluating earnings reports. The management offers insights on growth drivers, risk factors, etc that impacted the earnings during that particular period. Analysts also assess the earnings results, taking into account the external factors that drove the growth or impacted the firm negatively. These factors could be mergers and acquisitions, bankruptcies, economic discrepancies, policy changes, etc. For investors, earnings reports are essential because these announcements swing the price up or down. Traders keep a keen eye on these reports as it can be a time when they can confirm positions. However, some investors also avoid earnings seasons because of the involvement of various human factors.
Earnings Credit Rate (or ECR) is the interest paid by the bank on a daily basis over the deposits made by customers and is usually aligned with the risk-free rate in the market. The financial institutions such as banks utilise the deposit to offset the service charges by using the deposits as a credit for services.