AI Articles and Analysis in Finance

In a 2017 symposium in Harvard’s Institute for Applied Computational Science, R. Martin Chavez, Deputy Chief Financial Officer of  Goldman Sachs explains that the company’s US cash equities trading division used to employ over 600 human traders back in 2000. Today that number is down to just two human traders, with the rest of the jobs being taken over by automated trading platforms that are managed by around 200 computer engineers.

Today, customers interact with banks and financial institutions across several different channels which has lead to an explosion in customer data being collected by these organizations. This data can be effectively leveraged using AI to gain insights on current and future customer behavior.

Health insurance is a critical component of the healthcare industry with private health insurance expenditures alone estimated at $1.1 billion in 2016, according to the latest data available from the Centers for Medicare and Medicaid Services. This figure represents 34 percent of the 2016 National Health Expenditure at $3.3 trillion.  

AI could play a major role in the way European insurers do business going forward. It may provide insurers new methods for collecting customer data that offer valuable insights insurers can use to attract and maintain customers.

Businesses today around the world have some portion of their operations being automated, which concurrently has meant that a lot of data about these processes is being collected (from sensors or internal company data etc). A combination of AI, big data analytics, and data science techniques seem to be a growing trend in many industry sectors, with predictive analytics being one of the most well-known.

In 2015, fraud losses on credit, debit, and prepaid cards issued worldwide reached $21.84 billion, according to a Bloomberg report. By 2020, Bloomberg predicts that this could grow by a rate of 45 percent.

We've noticed a lot of interest from our readers for our pieces dealing with AI applications in the finance and banking sectors. New applications for artificial intelligence often seem to develop by transferring an existing use-case in a related field, and this might be the case with AI applications for ATMs as well.

The ability of companies to collect external data is likely to change the insurance industry as it is today. Traditionally, insurance companies would collect internal data from customers: data such as their weight, gender, and any family history of health issues. However, with the advent of technologies making possible the collection of data specific more to individuals than large groups of people, insurance companies could be able to offer unique, tailor-made policies to their customers.