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This chapter introduces the concept of financial market and highlights the role of e-payment systems in the financial market by focusing on the keywords of financial innovation, e-payment and sustainability.

This study gauges the profitability and performance of Indian commercial banks under the technology advancements. In this study, the authors identified three domains that give advantage to banks due to technology incorporation, that is, increased sales revenue, reduced operating expenses, and increased employee productivity. The authors assess the effect of these domains on banks’ profitability and performance. This study is conducted for the period between the years 2003 and 2018 across 34 public and private banks for empirical analysis. The authors examined the impact of investment in technology on the profitability using panel data analysis and evaluated the long-term effect of technology investment using the vector error correction model. This study found that there is a mixed effect of technology spend on the profitability and performance of Indian banks, where private sector banks are more aggressive in technology investment as compared to the public sector banks. This study recommends an optimal technology-related strategy to gain improved productivity for the banking business, that is, planned technology reserves, customer awareness campaigns about technology-enabled products, and robust employee–customer motivation policy.

Introduction: With many new technologies requiring real-time data processing, cloud computing has become challenging to implement due to high bandwidth and high latency requirements.

Purpose: To overcome this issue, edge computing is used to process data at the network’s edge. Edge computing is a distributed computing paradigm that brings computation and data storage closer to the location where it is needed. It is used to process time-sensitive data.

Methodology: The authors implemented the model using Linux Foundation’s open-source platform EdgeX Foundry to create an edge-computing device. The model involved getting data from an on-board sensor (on-board diagnostics (OBD-II)) and the GPS sensor of a car. The data are then observed and computed to the EdgeX server. The single server will send data to serve three real-life internet of things (IoT) use cases: auto insurance, supporting a smart city, and building a personal driving record.

Findings: The main aim of this model is to illustrate how edge computing can improve both latency and bandwidth usage needed for real-world IoT applications.