AI Articles and Analysis in Finance

Reuters referenced a Stratistics MRC figure estimating the size of the business intelligence industry around $15.64 billion in 2016. It follows that AI would find its way into the business intelligence world. In our previous report, we covered 6 use-cases for AI in business intelligence. As of now, numerous companies claim to assist business leaders in the finance domain, specifically, in aspects of their roles using AI.

We have identified three areas in finance where companies are applying AI to solve real business problems: fintech, regtech, and suptech.

The banking and financial sectors are among the top five applications for artificial intelligence across the globe. With India seeming to have woken up to the potential of AI, we decided to cover the developments in the Indian artificial intelligence sector. We then researched the use of AI in the Indian financial services market to better understand where AI comes into play and to answer the following questions:

In 2017, Equifax’s systems were compromised by hackers, and the data of over 143 million Americans was exposed. Other incidents, such as the WannaCry and Petya ransomware scams, have highlighted the vulnerabilities in financial cybersecurity globally. According to the Global Banking and Finance Review, such cyber attacks have cost nearly USD 360 billion per year in losses for each of the last three years.

The insurance industry is looking to adopt artificial intelligence applications for a variety of business functions due to its access to large volume of customer data. According to our AI Opportunity Landscape research in insurance, approximately 46% of AI vendors in insurance offer solutions for claims and 43% offer solutions for underwriting. While there are other areas of insurance that could benefit from AI, it's clear that these two core insurance tenets are where the traction is with AI in the industry.

According to the Consumer Financial Protection Bureau, Americans filed more grievances about debt collections than about any other financial incident. Of the 316,810 complaints received by the CFPB about debt collection in 2017, the most common was, “Continued attempts to collect debt not owed,” which was cited by 39 percent of grievance filers.

Today, two highly discussed disruptive technologies are artificial intelligence and blockchain. In this piece, we aim to highlight projects where AI and blockchain might be used together to support the B2B environment.

According to the Automated Imaging Association (AIA), machine vision is a combination of hardware like cameras, image sensors, and image processing software that can help automate applications like inspection and analysis by allowing machines (such as robots) to ‘see’ their surroundings.