Purpose This study aims to investigate the intersection of financial technology (fintech) and
credit risk exploring the impact of fintech on credit risk within the banking and financial …

Prediction of currency exchange rate becomes highly desirable due to its greater role in
financial and managerial decision making process. The fluctuations in exchange rate affect …

Banking industry has the major activity of lending money to those who are in need of money.
In order to payback the principle borrowed from the depositor bank collects the interest …

abstract Traditional automated trading systems use rules and filters based on Chartism to
send orders to the market, aiming to beat the market and obtain positive returns in bullish or …

Financial institutions, by and large, rely on the use of machine learning techniques to
improve the classic credit risk assessment model for reduction of costs, delivery of faster …

In this paper, a radial basis function neural network (RBFN) model has been trained by
canonical particle swarm optimisation (PSO) and improved particle swarm optimisation …

Financial time series data is very chaotic, noisy, fluctuating and nonlinear as different events
have occurred in various time periods. Therefore, it is very challenging for researchers to …

The interest collected by the main borrowers is collected to pay back the principal borrowed
from the depositary bank. In financial risk management, credit risk assessment is becoming …

In this ever-changing world, cloud computing will definitely play a vital role in our daily life as
everything is going to be mapped on it. In this paper, we have considered the cloud …

Decision tree is a renowned classifier reformed by innumerable tree generation techniques
to construct efficient trees. In this paper, a novel framework for constructing decision tree …