L'évaluation du risque de prêt joue un rôle central dans l'industrie financière, et les modèles prédictifs sont essentiels pour prendre des décisions de prêt en connaissance de cause. Ce projet de recherche se penche sur le domaine de l'évaluation du risque de prêt, un aspect critique de l'industrie financière, en proposant une approche innovante utilisant l'algorithme Feed Forward Neural Network (FNN). L'objectif principal est de comparer l'efficacité de l'algorithme FNN avec les machines à vecteurs de support (SVM) largement adoptées pour la prédiction du risque de prêt....

In the contemporary business landscape, marked by the dynamic interplay of Entrepreneurship and Modern Banking, the confluence of rapidly evolving customer needs, heightened competition, and groundbreaking technological innovations shapes a paradigm where strategic imperatives take center stage. Amidst this intricate tapestry, Customer Relationship Management (CRM) emerges not merely as a tool but as a pivotal strategy and technological cornerstone, exerting a profound influence, particularly within the spheres of entrepreneurship and banking. This research embarks on a semi-systematic...

Loan risk prediction is crucial for financial institutions to minimize lending risks. This study investigates the effectiveness of transaction data in loan risk prediction, comparing the performance of two popular algorithms: logistic regression and feed-forward neural networks. The research aims to assess the predictive capabilities, interpretability, and practical applicability of these models in identifying potential loan defaults based on transactional patterns. Transactional data, acquired from Kaggle, underwent rigorous preprocessing and feature engineering tailored to the unique...

Loan risk assessment plays a pivotal role in the financial industry, and predictive models are essential for making informed lending decisions. This research project delves into the domain of loan risk assessment, a critical aspect of the financial industry, by proposing an innovative approach utilizing the Feed Forward Neural Network (FNN) algorithm. The primary focus is on comparing the efficacy of the FNN algorithm with the widely adopted Support Vector Machines (SVM) for loan risk prediction. The objective is to assess the FNN algorithm's effectiveness in predicting loan defaults, aiming...

The process of converting one currency into another for a variety of purposes-most commonly trade, tourism, or commerce-is known as foreign exchange, or forex (FX). As exchange rate pairs, currencies are traded against one another. For instance, the currency pair EUR/USD allows traders to trade the euro versus the US dollar, while GBP/JPY (British Pound/Japanese Yen). Foreign exchange (Forex) markets, as the world's largest financial arena, demand robust forecasting strategies to navigate their dynamic and complex nature. This research undertakes a thorough comparative analysis of forecasting...

It's no secret that social media platforms are proliferating at an unprecedented rate, and with internet access becoming increasingly ubiquitous, the dissemination of fake news has become a swift and effortless process. The ramifications of this phenomenon are profound, particularly in the realms of politics and education, where the impact of fake news can be significantly disruptive.In this research study, we will be using Natural Language Processing (NLP) to transform text- based news headlines into numerical vectors. We examined and contrasted two NLP methods, Bag of Words (BoW) and Term...

Die Bewertung von Kreditrisiken spielt in der Finanzbranche eine zentrale Rolle, und Vorhersagemodelle sind für fundierte Kreditentscheidungen unerlässlich. Dieses Forschungsprojekt befasst sich mit dem Bereich der Kreditrisikobewertung, einem kritischen Aspekt der Finanzindustrie, und schlägt einen innovativen Ansatz vor, der den Algorithmus des Feed Forward Neural Network (FNN) nutzt. Das Hauptaugenmerk liegt auf dem Vergleich der Wirksamkeit des FNN-Algorithmus mit den weit verbreiteten Support Vector Machines (SVM) zur Vorhersage von Kreditrisiken. Ziel ist es, die Effektivität des...