The benchmark interest rate in the United States was last recorded at 4.50 percent. This dataset provides the latest reported value for - United States Fed Funds Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

The benchmark interest rate in Japan was last recorded at 0.50 percent. This dataset provides - Japan Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

The benchmark interest rate in Brazil was last recorded at 14.75 percent. This dataset provides - Brazil Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

United States US: Lending Interest Rate data was reported at 3.512 % pa in 2016. This records an increase from the previous number of 3.260 % pa for 2015. United States US: Lending Interest Rate data is updated yearly, averaging 6.922 % pa from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 18.870 % pa in 1981 and a record low of 3.250 % pa in 2014. United States US: Lending Interest Rate data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Interest Rates. Lending rate is the bank rate that usually meets the short- and medium-term financing needs of the private sector. This rate is normally differentiated according to creditworthiness of borrowers and objectives of financing. The terms and conditions attached to these rates differ by country, however, limiting their comparability.; ; International Monetary Fund, International Financial Statistics and data files.; ;

This dataset provides insights into the global housing market, covering various economic factors from 2015 to 2024. It includes details about property prices, rental yields, interest rates, and household income across multiple countries. This dataset is ideal for real estate analysis, financial forecasting, and market trend visualization.

📑 Column Descriptions

Iran IR: Lending Interest Rate data was reported at 18.000 % pa in 2016. This records an increase from the previous number of 14.210 % pa for 2015. Iran IR: Lending Interest Rate data is updated yearly, averaging 12.000 % pa from Dec 2004 (Median) to 2016, with 13 observations. The data reached an all-time high of 18.000 % pa in 2016 and a record low of 11.000 % pa in 2013. Iran IR: Lending Interest Rate data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Iran – Table IR.World Bank.WDI: Interest Rates. Lending rate is the bank rate that usually meets the short- and medium-term financing needs of the private sector. This rate is normally differentiated according to creditworthiness of borrowers and objectives of financing. The terms and conditions attached to these rates differ by country, however, limiting their comparability.; ; International Monetary Fund, International Financial Statistics and data files.; ;

Nepal NP: Real Interest Rate data was reported at -6.207 % pa in 2010. This records an increase from the previous number of -6.823 % pa for 2009. Nepal NP: Real Interest Rate data is updated yearly, averaging 3.657 % pa from Dec 1975 (Median) to 2010, with 29 observations. The data reached an all-time high of 18.214 % pa in 1977 and a record low of -12.173 % pa in 1975. Nepal NP: Real Interest Rate data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Nepal – Table NP.World Bank.WDI: Interest Rates. Real interest rate is the lending interest rate adjusted for inflation as measured by the GDP deflator. The terms and conditions attached to lending rates differ by country, however, limiting their comparability.; ; International Monetary Fund, International Financial Statistics and data files using World Bank data on the GDP deflator.; ;

The benchmark interest rate in Norway was last recorded at 4.50 percent. This dataset provides the latest reported value for - Norway Interest Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Indonesia Banking Survey: Loan Interest Rate: Whole Year Estimation: in USD: Investment data was reported at 6.566 % in Mar 2025. This records an increase from the previous number of 6.446 % for Dec 2024. Indonesia Banking Survey: Loan Interest Rate: Whole Year Estimation: in USD: Investment data is updated quarterly, averaging 6.330 % from Mar 2012 (Median) to Mar 2025, with 53 observations. The data reached an all-time high of 6.961 % in Sep 2023 and a record low of 4.454 % in Mar 2022. Indonesia Banking Survey: Loan Interest Rate: Whole Year Estimation: in USD: Investment data remains active status in CEIC and is reported by Bank Indonesia. The data is categorized under Indonesia Premium Database’s Business and Economic Survey – Table ID.SE003: Banking Survey: Interest Rate. [COVID-19-IMPACT]

MX: Risk Premium on Lending: Lending Rate Minus Treasury Bill Rate data was reported at 0.653 % pa in 2017. This records an increase from the previous number of 0.570 % pa for 2016. MX: Risk Premium on Lending: Lending Rate Minus Treasury Bill Rate data is updated yearly, averaging 0.884 % pa from Dec 1993 (Median) to 2017, with 25 observations. The data reached an all-time high of 10.993 % pa in 1995 and a record low of 0.319 % pa in 2006. MX: Risk Premium on Lending: Lending Rate Minus Treasury Bill Rate data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mexico – Table MX.World Bank.WDI: Interest Rates. Risk premium on lending is the interest rate charged by banks on loans to private sector customers minus the 'risk free' treasury bill interest rate at which short-term government securities are issued or traded in the market. In some countries this spread may be negative, indicating that the market considers its best corporate clients to be lower risk than the government. The terms and conditions attached to lending rates differ by country, however, limiting their comparability.; ; International Monetary Fund, International Financial Statistics database.; ;

This paper investigates both the effects of domestic monetary policy and external shocks on fundamental macroeconomic variables in six fast growing emerging economies: Brazil, Russia, India, China, South Africa and Turkey—denoted hereafter as BRICS_T. The authors adopt a structural VAR model with a block exogeneity procedure to identify domestic monetary policy shocks and external shocks. Their research reveals that a contractionary monetary policy in most countries appreciates the domestic currency, increases interest rates, effectively controls inflation rates and reduces output. They do not find any evidence of the price, output, exchange rates and trade puzzles that are usually found in VAR studies. Their findings imply that the exchange rate is the main transmission mechanism in BRICS_T economies. The authors also find that that there are inverse J-curves in five of the six fast growing emerging economies and there are deviations from UIP (Uncovered Interest Parity) in response to a contractionary monetary policy in those countries. Moreover, world output shocks are not a dominant source of fluctuations in those economies.

Graph and download economic data for Interest Rates, Discount Rate for United States (INTDSRUSM193N) from Jan 1950 to Aug 2021 about discount, interest rate, interest, rate, and USA.

Costa Rica CR: Real Interest Rate data was reported at 9.193 % pa in 2023. This records an increase from the previous number of 1.017 % pa for 2022. Costa Rica CR: Real Interest Rate data is updated yearly, averaging 9.164 % pa from Dec 1982 (Median) to 2023, with 42 observations. The data reached an all-time high of 17.735 % pa in 1993 and a record low of -32.129 % pa in 1982. Costa Rica CR: Real Interest Rate data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Costa Rica – Table CR.World Bank.WDI: Interest Rates. Real interest rate is the lending interest rate adjusted for inflation as measured by the GDP deflator. The terms and conditions attached to lending rates differ by country, however, limiting their comparability.;International Monetary Fund, International Financial Statistics and data files using World Bank data on the GDP deflator.;;

The benchmark interest rate in Mexico was last recorded at 8.50 percent. This dataset provides - Mexico Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

We study the effects of monetary policy on economic activity separately identifying the effects of a conventional change in the fed funds rate from the policy of forward guidance. We use a structural VAR identified using external instruments from futures market data. The response of output to a fed funds rate shock is found to be consistent with typical monetary VAR analyses. However, the effect of a forward guidance shock that increases long-term interest rates has an expansionary effect on output. This counterintuitive response is shown to be tied to the asymmetric information between the Federal Reserve and the public.

Australia Interest Rate Spread data was reported at 3.543 % pa in 2019. This records an increase from the previous number of 3.282 % pa for 2018. Australia Interest Rate Spread data is updated yearly, averaging 3.048 % pa from Dec 1981 (Median) to 2019, with 39 observations. The data reached an all-time high of 4.183 % pa in 2008 and a record low of -1.888 % pa in 1989. Australia Interest Rate Spread data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Australia – Table AU.World Bank.WDI: Interest Rates. Interest rate spread is the interest rate charged by banks on loans to private sector customers minus the interest rate paid by commercial or similar banks for demand, time, or savings deposits. The terms and conditions attached to these rates differ by country, however, limiting their comparability.;International Monetary Fund, International Financial Statistics and data files.;Median;

HN: Interest Rate Spread data was reported at 11.004 % pa in 2017. This records an increase from the previous number of 10.688 % pa for 2016. HN: Interest Rate Spread data is updated yearly, averaging 9.320 % pa from Dec 1985 (Median) to 2017, with 33 observations. The data reached an all-time high of 14.983 % pa in 1995 and a record low of 5.925 % pa in 1987. HN: Interest Rate Spread data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Honduras – Table HN.World Bank.WDI: Interest Rates. Interest rate spread is the interest rate charged by banks on loans to private sector customers minus the interest rate paid by commercial or similar banks for demand, time, or savings deposits. The terms and conditions attached to these rates differ by country, however, limiting their comparability.; ; International Monetary Fund, International Financial Statistics and data files.; Median;

30 Year Mortgage Rate in the United States decreased to 6.85 percent in June 5 from 6.89 percent in the previous week. This dataset includes a chart with historical data for the United States 30 Year Mortgage Rate.

View data of the Effective Federal Funds Rate, or the interest rate depository institutions charge each other for overnight loans of funds.

Context

Have you ever wondered how lenders use various factors such as credit score, annual income, the loan amount approved, tenure, debt-to-income ratio etc. and select your interest rates?

The process, defined as ‘risk-based pricing’, uses a sophisticated algorithm that leverages different determining factors of a loan applicant. Selection of significant factors will help develop a prediction algorithm which can estimate loan interest rates based on clients’ information. On one hand, knowing the factors will help consumers and borrowers to increase their credit worthiness and place themselves in a better position to negotiate for getting a lower interest rate. On the other hand, this will help lending companies to get an immediate fixed interest rate estimation based on clients information. Here, your goal is to use a training dataset to predict the loan rate category (1 / 2 / 3) that will be assigned to each loan in our test set.

You can use any combination of the features in the dataset to make your loan rate category predictions. Some features will be easier to use than others.

Acknowledgements

https://datahack.analyticsvidhya.com/contest/janatahack-machine-learning-for-banking/True/#ProblemStatement