Open AccessAssessing the sustainability of General Insurance Business through Real Time Monitoring of KPIs using Recurrent Neural Network
Author(s) -
S.R.Pranav Sai,
Ajay Singh Pawar,
Satya Sai Mudigonda,
Phani Krishna Kandala,
Pallav Kumar Baruah
Publication year - 2020
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.c4679.099320
Subject(s) - performance indicator , profitability index , computer science , sustainability , measure (data warehouse) , bridge (graph theory) , work (physics) , process management , business intelligence , operational efficiency , business , data mining , finance , engineering , marketing , medicine , mechanical engineering , ecology , biology
A company’s sustainability is driven significantly by its operational efficiency. Operational efficiency plays a significant role in the growth and the profitability of a company. Thus, operational efficiency of a company forms the basis for the metrics known as the Key Performance Indicators(KPIs). These KPIs bridge the concept of performance an operation and a means to measure the same quantitatively. In this work, we used Recurrent Neural Network (RNN) with the Long Short Term Memory(LSTM) cells for projecting the public disclosure data of select General Insurance(GI) companies operating in India to the future. We use this data to calculate the KPIs pertaining to the operations of general insurance companies and calculate how the operations of the GI company affect its performance at various levels. Since this analysis is done for the projected data, we get a framework to assess the sustainability of the GI companies by monitoring these KPIs in real-time. The complex RNN and LSTM algorithms were implemented with the help of the Google Colaboratory platform by using the GPUs of the Google Hardware with the help of the Cloud Computing framework.