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Home Published Articles

CohnReznick

byPhil Neuffer
July 20, 2022
in Published Articles

CURRENT


Tama Huang
Chief Innovation Officer

HQ: New York
212-297-0400 • cohnreznick.com

Helping businesses detect and combat fraud, minimize risk and protect vital assets are all focuses for CohnReznick. As companies are forced to contend with analyzing ever-increasing volumes of data, the analog processes many use are proving to be both inefficient and ripe for fraud.

CohnReznick’s cognitive automation platform, machine learning technologies and human-led analysis document a company’s data assimilation capabilities, digitize data and make it available for a company’s analysis using proprietary fraud detection algorithms. The cognitive automation platform efficiently and expeditiously reviews large volumes of data, ensuring data analysis is more accurate and more insightful. The platform can also identify key fraud indicators in metadata, such as the recurrence of an IP address, email domain or phone carrier. These critically important signs of possible fraud cannot typically be identified by human reviewers during routine review processes due to the sheer volume of data. Another key benefit of the platform is it allows human reviewers the ability to direct more time to combating any patterns of bias that arise within data.

CohnReznick’s cognitive automation platform and related technologies and processes are changing the game for clients by optimizing performance, maximizing value and managing risk. By aligning the platform’s capabilities with effective company controls, the firm’s clients are benefitting from the crucial ability to leverage tangential data, minimize the potential for fraud and make meaningful, timely and data-driven decisions for stakeholders. This platform and its capabilities are particularly relevant for members of the secured lending community.

“In the battle of human eyes against overwhelming volumes of data to detect fraud, waste and abuse, advancements in emerging technologies level the playing field.”

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