AI’s ability to process large volumes of data with speed and accuracy can potentially transform regulatory compliance — but not without attendant risk and challenges. In the short term, the technology can be used to assist business leaders to understand compliance requirements easily and take apposite action, but circumventing human intelligence and our ability to think ethically and abstractly makes AI’s role in compliance controversial and complex.
Key Insights and Trends from the MetricStream GRC Summit 2018 MetricStream’s 2018 Summit in Baltimore saw several hundred business executives, government leaders, GRC practitioners and industry analysts gather to talk GDPR, strategies and solutions for building better governed, more compliant organizations and more. Gaurav Kapoor, MetricStream's Chief Operating Officer, shines ...
Read moreBruce Orcutt from ABBYY shares how artificial intelligence can extract meaning from contracts in the same way as humans do, the challenges businesses face in using AI and the benefits the technology can offer. Contracts are the engine of a business; they contain critical business intelligence needed to run the ...
Read moreArtificial Intelligence Takes On Transactional Fraud In the field of fraud prediction, with transactional fraud raising every day; investors, board, management and business heads are keen to look at possibilities of detecting fraudulent transactions before they pass through the system. Machine learning algorithms bring efficiency in identifying potentially fraudulent transactions. ...
Read moreHow to Overcome Technological Roadblocks What a time to work in the GRC field: new technologies are constantly emerging to help companies meet their regulatory obligations. At the same time, many fragmented requirements have piled up over time. Chris Ekonomidis, Head of U.S. Business Consulting at Synechron, discusses the three ...
Read moreBuzzwords like AI and machine learning tend to grab the attention of C-suite leaders, but the most exciting tool in the digital transformation toolbox is RPA, robotic process automation. Anthony Macciola defines RPA, discusses the realities of machine learning and covers strategies for driving content intelligence. There has been no ...
Read moreEmbracing New Technologies Fenergo’s Laura Glynn discusses how banks around the world are embracing a more digitalized and transformative approach to compliance and, indeed, client life cycle management. Read Part 1. The global financial services industry is currently on the brink of a massive technological disruption. Financial institutions are now ...
Read moreThe Value of Big Data A crucial shift is underway in the financial services industry when it comes to regulatory compliance; cultures are changing, and new value is being created for banks and their customers because of AI technology. Grace Brasington of Watson Financial Services discusses the role technology can ...
Read morePutting Plans Into Effect As tech evolves, so too does the compliance landscape, and keeping up can prove quite the challenge for many businesses. Here, we share trends and predictions from Anthony West, CTO at Actiance and an expert in electronic communications compliance. While 2017 was spent frantically preparing for ...
Read moreDriving Down Risk, From the Cubicle to the C-Suite Effective employee engagement and reporting is key to accountability and effective risk management. So why are we not paying more attention to how today's workforce prefers to communicate? with co-author Jay R. Taylor, CEO of EagleNext Advisors We are entering an ...
Read moreThe Inherent Risk (and Reward) of Innovation This year, cybersecurity officers must rethink their end-to-end security ecosystem. Top priority will be identifying and addressing evolving vulnerabilities to people, processes, technologies and service providers. It's time both to re-evaluate the overarching security strategy and to take a more security-minded approach from ...
Read moreLike Achilles or Sampson, the power and potential of AI has a weakness, a vulnerability. In the case of financial services that weakness is its opacity. In general, the better the machine learning system, the blacker the box - that is, the harder it is to decipher what is going ...
Read moreThe advances in technology in recent years have led to an exponential increase in the volume of data collected and stored. How can investigators maximize data analytics to achieve the most effective—and efficient—results for their clients? The answer lies in harnessing the power of AI to augment the capability and ...
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