7 ways machine learning helps financial institutions Posted on : Nov 18 - 2019

Solutions powered by machine learning can help financial institutions address their most pressing challenges

Machine learning is one of the most promising technologies today that makes it possible for machines to learn how the human brain works and replicate this learning to analyze varied data types and deduce meaningful insights.

Machine learning models

At the core of machine learning are three models that help machines unearth insights and patterns. These are:

Supervised models: These are used with historical data where the output is pre-defined. For instance, when you speak, Alexa can recognize the words and sentences she has been trained on and respond appropriately.

Unsupervised models: These are used on transactional data to identify patterns. Based on your interaction with Alexa, she can identify the patterns to suggest topics you may be interested in.

Reinforcement learning: It is a technique where machines learn to respond to situations on their own, without instructions. For every mistake (a negative outcome) that Alexa makes, she ‘learns’ from it to become smarter and refine the response next time.

FIs can benefit the most from machine learning

Businesses are increasingly leaning on machine learning, as volumes of data are exploding and they need actionable insights to fuel business growth. Given the benefits it promises, numerous industries—manufacturing, energy, healthcare, cyber defense, financial institutions—are making significant investments in machine learning. In fact, financial institutions (FIs) stand to benefit the most from machine learning. View More