Matthew DeMello

For a tech subsector on everyone's proverbial lips' at the moment, things can hardly be described as 'easygoing' for the AI vendor startup market in 2023.

While machine learning might be as close to a household name as any AI capability in 2023, any serious historian will tell you the technology itself is nothing new. The term 'machine learning' was coined in an IBM study on computer gaming and AI dating back to 1959.

This article is sponsored by Arkestro, and was written, edited and published in alignment with our transparent Emerj sponsored content guidelines.

Banks and banking AI vendors turn to Emerj to help them maximize ROI by allocating their funds to the most high-need areas. Our research also helps them make smarter decisions by identifying the projects that are more accessible and have the highest chance of resulting in near-term financial returns. 

While the steel industry may not be synonymous with AI adoption, steel manufacturers are not different from any other business in ensuring efficiency in their output and throughput. There are almost certainly opportunities for AI implementation across an industry worth hundreds of billions of dollars that currently lags behind in adopting AI technology.

Intelligent document processing is best thought of as another name for data extraction, where paper-based information is transferred to a digital format. According to the U.S. Governmental Services Administration, roughly 80% of any organization's data comes from unstructured sources – like paper records management. 

Compliance workflows across financial services are no strangers to AI. Noncoding enterprise leaders are often awash in reports on how robust the AI vendor market is for AML and KYC or KYCC (know your customer's customer) compliance. Celent estimated that spending in the financial services sector on AML/KYC compliance tech and operations would reach $37.1 billion last year, an increase of 13.7% from 2020. 

Insurance is a growing arena for AI adoption and in many cases, automation is leading the way to streamline customer experiences and the organizational pipelines behind them along the entire customer journey.

Financial services is an industry rife with repetitive processes and workflows that do not ultimately require human judgment to complete. Nearly three out of five leading banks polled [pdf] in a survey from Arizant, American Banker, and robotic process automation (RPA) vendor UiPath reported that their organizations had already implemented "moderate or significant" automation technologies by March 2022 to accomplish these tasks at their organizations. 

AI plays a more significant role in our lives every day, and cybersecurity is hardly an exception – for both the "cat" and "mouse" sides of the table. According to a study from the Ponemon Institute in partnership with Accenture, cybercrime alone cost financial services firms $18.5 million on average in 2018.

This article was not sponsored, but draws upon a webinar sponsored by Uniphore. This article was written, edited, and published in alignment with our Emerj sponsored content guidelines. Learn more about our thought leadership and content creation services on our Emerj Media Services page.

The AI vendor market is as diverse as the global economy itself. As AI applications evolve into every corner of our lives, so do the expertise and proficiency of the data professionals, business leaders and subject matter experts at the heart of the products and services transforming how we live and work.

This interview analysis is sponsored by SambaNova Systems was written, edited, and published in alignment with our Emerj sponsored content guidelines. Learn more about our thought leadership and content creation services on our Emerj Media Services page.

Payment Card Industry (PCI) compliance is a rite of passage for emerging businesses, or at least a compelling marketing narrative for those who take the initiative to achieve certification before partners, future deals and business circumstances demand it.

COVID-19 did not just bring waves of diseases and contagious variants across the world starting in early 2020 – a tsunami of fraud soon followed the broad sweep of a pandemic that would engulf the global insurance industry. 

The finance industry has evolved quite a long way since the days of the SAC scandal and after being diagnosed with an insider trading epidemic in 2014 by academic studies from McGill and New York University – learning countless lessons along the way.

Picture a financial services company and images of numbers, analysis, and data-crunching in scrutinizing reports come to mind — and for good reason. In the heavily regulated world of financial services, decision-makers rely on data to feed their decisions and support their conclusions. 

In 2020, fines for Anti-Money Laundering (AML) noncompliance reached $2.2 billion, up nearly 400% from 2019, according to Kroll data. The trend continued into 2021. Through June 30, AML fines totaled $994 million, suggesting another year of strict regulatory enforcement action. 

Like many legacy and document-heavy industries in 2022, the entire financial services sector is undergoing a transformation through AI capabilities. These technologies have successfully disrupted many systems and processes once considered sacrosanct: personal financial transactions, collection and analysis of consumer data, personalized offerings of financial products and services, and more.

In June 2014, a bombshell study from researchers at New York and McGill Universities found that a quarter of all mergers and acquisitions of public companies between 1996 and 2012 involved some measurable degree of insider trading.