Graph Theory for Computer Science

2Advancing Systemic Risk Assessment in Financial Networks with Neural Networks and Graph Labeling

Sreena T.D.¹* and Surabhi N.V.²

¹Department of Mathematics, Sree Narayana College Nattika, Thrissur, Kerala, India

²Department of Commerce, Sree Narayana College Nattika, Thrissur, Kerala, India

Abstract

The financial stability of an organization depends on strong risk assessment technologies that demand innovative solutions in advanced technology. This research proposes a new framework for assessing financial stability and collaboration feasibility among companies using neural networks and graph theory. We use neural network models to demonstrate the connection between the organizations and graph labeling techniques for better understanding. Using techniques of neural network models and graph theory, we can identify the economic stability of an organization and predict systematic risks based on real-world data.

Keywords: Financial networks, financial performance, graph labeling, neural network, systematic risk

2.1 Introduction

The trade world brings numerous openings and challenges to commerce world, including changing customer tastes and quickly creating innovations in a competitive worldwide environment. The unused period is characterized by a stage of exceptionally distinctive interconnects, and businesses that work in worldwide markets are characterized by expanding competition and the steady development of the showcase. The conventional ideas of competition have fallen, ...