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Machine Learning: Who’s Using it and Why

OCTOBER 11, 2017

Whether we realize it or not, we encounter machine learning on a daily basis. Aside from in our day-to-day lives, industries from retail to government and more are depending on machine learning to get things done. Below is a short list of how different industries are utilizing machine learning.

This is not a complete list, as dozens of industries are using machine learning in a vast number of ways.

FINANCE

With its quantitative nature, banking and finance are an ideal application for machine learning. The technology is being used in dozens of ways industry-wide, but here are a few of the most commonly used:

  • Fraud – Machine learning algorithms can analyze an enormous amount of transactions at a time, and learn a person’s typical spending patterns. If a transaction is made that is unusual, it will reject the transaction and indicate potential fraud.
  • Trading floors – With its ability to efficiently assess data and patterns, machine learning can assist with quick decision-making in real-time.
  • Credit and risk management – Typically assessing credit risk is labor intensive and is prone to human-subjected errors. With machine learning, certain algorithms can help to provide mitigation recommendations.
UTILITIES

Utility companies can utilize machine learning in a number of ways, including uncovering hidden energy patterns, learning customer’s energy behaviors, and more.

HEALTHCARE
  • Diagnoses – Machine learning can analyze data and identify trends or red flags within patients to potentially lead to earlier diagnoses and better treatments.
  • Patient information – Data can be collected from a patient’s device to assess their health in real-time. Drug discovery – Given its ability to detect patterns within data, scientists are able to better predict drug side effects and results of drug experiments without actually performing them.
MARKETING AND SALES
  • Personalization – Machine learning allows online brands to suggest and advertise things you may like based on your browser and search history. Brands use their collected data to give customers a unique and personalized experience.
OIL AND GAS
  • Energy sources – By analyzing different minerals in the ground, machine learning provides the potential to discover new energy sources.
  • Streamlining oil distribution – Algorithms work to make oil distribution more efficient and cost-effective.
  • Reservoir modeling – Certain machine learning techniques can focus on optimization of hydraulic fracturing, reservoir simulation, and more.
TRANSPORTATION
  • Efficient transportation – Analysis of data can identify certain patterns and trends to make routes more efficient for public transportation, delivery companies, and more.

 

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Lauren Spinella
About the Author
Lauren is a content marketing professional with experience in digital and social marketing. As a Content Marketing Specialist at Interactions, she assists with content creation and social media strategy. Lauren holds a BA in Journalism from Northeastern University.