AI Articles and Analysis in Finance

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.

Last year, Boston Consulting Group reported that banks were tracking three times as many individual global regulatory changes as compared to 2011. The report added that these institutions were averaging 200 regulatory revisions per day in 2017.

Asset and wealth management firms are exploring potential AI solutions for improving their investment decisions, and making use of their troves of historical data. In fact, according to our AI Opportunity Landscape research into the banking industry specifically, approximately 13.5% of the AI vendors in banking offer solutions for wealth and asset management.

Episode Summary: Natural language processing (NLP) has become popular in the past two years as more businesses processes implement this technology in different niches. In inviting our guest today, we want to know specifically which industries, businesses or processes NLP could be leveraged to learn from activity logs.

Robo-advisors are digital platforms that provide automated, algorithm-based financial planning services with little to no human supervision.