Buisness-Forecasting-using-Time Series

Neo Bank of India (a fictional bank) receives a lot of requests for its various finance offerings that include housing loans, two-wheeler loans, real estate financing, and microloans. The number of applications received is something that varies a lot with the season. Going through these applications is a manual and tedious process. Accurately forecasting the number of cases received can help with resource and manpower management resulting in quick response on applications and more efficient processing.

You have been appointed with the task of forecasting daily cases for the next 1 month for 2 different business segments aggregated at the country level keeping in consideration the following major Indian festivals (inclusive but not exhaustive list): Diwali, Dussehra, Ganesh Chaturthi, Navratri, Holi, etc. (You are free to use any publicly available open-source external datasets). Some other examples could be: Weather Macroeconomic variables, etc.

NOTE: The data used in this competition is not owned by the author. The above-mentioned business entity is fictional. Data is obtained by using one of the freely available data sources. Rights are reversed to orginal providers.

Three models were used to forecast no. of applicants:

• SARIMA
• Prophet Model
• LSTM