Analysis & Prediction of Funding for Indian Startups Using Neural Networks - P Mahalakshmi, Soham Bhowmick, Aditya Vikram Sarkar (International Journal of Advanced Science and Technology, 2020)
Since the start-up boom in India, around 90% of them have failed to sustain their idea in the start-up ecosystem. There are several factors for it but one of the major ones is the lack of funding. We hope to analyze the present Indian start-up scenario and provide predictive suggestions on the funding they could expect to raise in the future. Analysis will be based on factors like start-up’s location, its domain vertical, the type of investment funding it is expecting, etc. The project uses real world data from 2016 to 2019 which is analyzed using Tableau and used to answer pertinent questions that a upcoming start-up may have. A predictive model is also built using ANN for predicting the future funding of major start-ups. The model will consider startups which belong to domains such as consumer internet, ecommerce, finance, healthcare, food & beverages, education, technology and logistics. This research work will help the potential enterpriser to understand the current market economy which will allow them to predict the funding that they can expect from investors and also will help them to analyze the market competition and their chances of survival.