AI Sector Overviews Articles and Reports
Artificial intelligence “sector overview” reports are designed to help business leaders explore the possibilities and important AI trends across industries. Search our sector overview reports below:
The auto-lending industry stands to benefit from artificial intelligence in much the same way as insurance companies, particularly when it comes to underwriting and risk management. According to Deloitte, nearly $500 billion in new loans and leases are originated annually, and 86% of new car purchases rely on borrowed money. In this article, we discuss how AI startups aim to facilitate different processes within the auto-lending industry, looking to two well-funded startups as examples of what's possible in the space:
In July of 2018, Daniel Faggella spoke at the Interpol--United Nations (UNICRI) Global Meeting on the Opportunities and Risks of Artificial Intelligence and Robotics for Law Enforcement. It was the very first event on the usage of AI in policing, security and law enforcement by the UN and INTERPOL.
The retail industry could be losing nearly $1 trillion in sales annually due to business process errors that could be automated by AI, such as restocking in eCommerce. In this article, we discuss the top 3 most well-funded AI startups selling to the retail industry and how their solutions could help retailers and eCommerce sites save money lost to fraud and increase revenue through customer analytics.
Signifyd - Retail and eCommerce Fraud Detection
Signifyd is the most well-funded AI startup in the fraud detection industry for retail and eCommerce, having raised $180 million. They were founded in August 2011 and specialize in fraud detection for retail and eCommerce companies. Their most prominent offering is called “guaranteed fraud detection,” and it likely uses anomaly detection technology to recognize fraudulent transactions and prevent chargebacks. The offering was originally announced exclusively for the Magento eCommerce platform in 2017.
Many of the largest US banks, including Bank of America, are starting to automate many of their business processes with AI. These include ACH payments and more specific processes such as order to cash. Bank of America has been investing seriously in AI and machine learning since at least 2017 and continues to research ways they can take advantage of AI in the future.
Much of the discussion surrounding AI in banking is focused on retail banks, with applications such as chatbots and payment fraud detection. But there exist AI capabilities that stand to benefit investment banking clients specifically as wealth management departments begin to adopt them.
Many AI vendor companies offer AI-enabled products and services for pushing more and more products in front of customers. That said, it is not always clear how these solutions determine which products to advertise to which customers. Retailers and other businesses should consider what they need to do to prepare their enterprise for one of these solutions and familiarize themselves with how AI recommendations are built and trained.
Many large banks and financial institutions are beginning to digitize parts of their business processes to prepare for future initiatives in automation and machine learning. This is particularly true with loan processing. These functions could become faster and more accurate if they use digitized data that is more easily accessible than paper documents.
In this brief overview, we run through several use-cases for voice recognition software in the healthcare industry. Voice recognition software, built on natural language processing (NLP) algorithms, primarily finds a home in the doctor's office. Physicians use it to dictate their notes into their healthcare network's system or update patient electronic medical records (EMR).