Assessing the sustainability of General Insurance Business through Real Time Monitoring of KPIs using Recurrent Neural Network
S.R.Pranav Sai1, Ajay Singh Pawar2, Satya Sai Mudigonda3, Phani Krishna Kandala4, Pallav Kumar Baruah5
1S.R.Pranav Sai*, Doctorial Research Scholar, Department of Mathematics and Computer Science, Sri Sathya Sai Institute of Higher Learning, Puttaparthi,, India.
2Ajay Singh Pawar, Master’s Student, Department of Mathematics and Computer science, Sri Sathya Sai Institute of Higher Learning, Puttaparthi India.
3Satya Sai Mudigonda, Senior Tech Actuarial Consultant, Hon. Professor in Department of Mathematics and Computer Science, Sri Sathya Sai Institute of Higher Learning Puttaparthi, India.
4Phani Krishna Kandala, Visiting faculty, Sri Sathya Sai Institute of Higher Learning, Puttaparthi, India.
5Dr. Pallav Kumar Baruah, Associate Professor, Department of Mathematics and Computer Science, Sri Sathya Sai Institute of Higher Learning, Puttaparthi, India.
Manuscript received on August 01, 2020. | Revised Manuscript received on August 05, 2020. | Manuscript published on September 30, 2020. | PP: 728-738 | Volume-9 Issue-3, September 2020. | Retrieval Number: 100.1/ijrte.C4679099320 | DOI: 10.35940/ijrte.C4679.099320
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: 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.
Keywords: Actuarial Analysis, General Insurance, Public Disclosure, RNN, LSTM, Google Colaboratory.