Author: AI & ML Simplified Editorial

This article explores the various machine learning models employed in the banking and finance sectors. It delves into the different categories of problems these models address and provides a detailed explanation of supervised and unsupervised learning.

In Machine Learning Algorithms role of data is to train models and make predictions. Different types of data are used by Machine Learning algorithms. A simple example of loan approval is used to illustrate the ideas.

AI systems with ML algorithms can be used at different stages of the loan approval process – application verification, risk assessment, credit decisioning. Using AI banks can scale credit services to include underserved markets.

Core Concepts of AI and ML – Data Science, Machine Learning Algorithms, Neural Networks, Deep Learning, Supervised Learning, Unsupervised Learning, Natural Language Processing (NLP)

This article explains the importance of AI & ML in finance and banking industry in simple words. A brief look into the history of AI & ML in finance and what lies ahead.