AI Articles and Analysis in Finance

Starting an early AI project is challenging for large and small enterprises. Perhaps no industry is more aware of these challenges than the highly regulated and especially tradition-oriented financial services sector.

Today, most robotic process automation (RPA) applications in banking consist of deterministic software tools that are not categorically considered artificial intelligence. For most use cases, RPA can be a trustworthy foundation to apply AI and drive even more efficiencies from the workflows they're looking to streamline.  

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.

Well before the surge of COVID-19 unearthed a veritable plague of criminal activity taking place over screens and digitized realms, banks were well aware they had a problem with cybercrime. 

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. 

An operational compliance framework is critical for banks and other financial institutions (FIs). However, it is a tremendous challenge to constantly and uniformly comply with regulations, guidelines, and laws, given the complexity and immensity of legislation.

The era of humans serving as sole agents for lending and underwriting is no more. Machine learning and AI are now more ubiquitous within financial institutions and insurance companies, thanks in no small part to the automation of lending and underwriting processes. 

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.