Assessing Sustainability of General Insurance Business through Real Time KPI using GPUs and Neural Networks
S. R. Pranav Sai1, Phani Krishna Kandala2, Satya Sai Mudigonda3, Pallav Kumar Baruah4

1S. R. Pranav Sai, Research Scholar, Department of Mathematics and Computer Science, Sri Sathya Sai Institute of Higher Learning Puttaparthi (Andhra Pradesh), India.
2Phani Krishna Kandala, Visiting Faculty Sri Sathya Sai Institute of Higher Learning Puttaparthi (Andhra Pradesh), India.
3Satya Sai Mudigonda, Professor, Department of Mathematics and Computer Science, Sri Sathya Sai Institute of Higher Learning Puttaparthi (Andhra Pradesh), India.
4Dr. Pallav Kumar Baruah, Associate Professor, Department of Mathematics and Computer Science, Sri Sathya Sai Institute of Higher Learning, Puttaparthi (Andhra Pradesh), India.
Manuscript received on 02 December 2019 | Revised Manuscript received on 20 December 2019 | Manuscript Published on 31 December 2019 | PP: 620-628 | Volume-8 Issue-4S2 December 2019 | Retrieval Number: D11291284S219/2019©BEIESP | DOI: 10.35940/ijrte.D1129.1284S219
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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: Sustainability of a company is driven by its operational efficiency. The operational efficiency plays a significant role in a company’s growth and profitability. Thus, it forms the foundation for the metrics of performance known as the Key Performance Indicators (KPIs). The KPIs establishes a connection between the concept of performance and the means to gauge the same. In this work, we use a neural network with two fully connected layers for analyzing and predicting the factors which are used for calculating the KPIs. The implementation was done with the help of a Graphics Processing Unit for running the complex calculations. The KPIs are obtained for the projected factors and the inference was done for five different non- life insurers in India, based on the public disclosure data available with insurance supervisors in India.
Keywords: Key Performance Indicators, Actuarial Analysis, Predictive Analytics, Fully Connected Neural Network, GPU.
Scope of the Article: Real-Time Information Systems