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How Financial Institutions Can Deal with Unstructured Data Overload

In this contributed article, Chandini Jain, CEO of Auquan, outlines how new AI-powered tools can aggregate, query, analyze and leverage unstructured data to unveil deep insights in record time. She takes a look into how these tools are providing value and helping financial institutions turn mounds of unstructured data into decision-making power.

Federal Reserve Considering Formal Request for Public Feedback about the Adoption of AI in the Financial Services Sector

It’s great to see the Fed move in the direction of potentially providing clarification and additional guidance around supervision of AI/ML in financial services. Additional guidance from the Fed and other agencies (OCC, CFPB) would help a lot to clarify supervisory expectations when AI/ML models are used. Specific guidance around these topics, provided by Anupam Datta, the Co-Founder, President, and Chief Scientist of Truera, are important.

How AI Technologies Can Put Purpose and Profit into ESG Investments

In this contributed article, Ruggero Gramatica, Founder and CEO of Yewno, discusses how institutional investors can increase financial returns and make better investment decisions in the field of environment, social, and governance (ESG) investing.

Looking at a New AI Tool for Financial Services – Insights for Wealth Advisors, Managers and Retail Bankers

Salesforce announced a complete AI-augmented platform built specifically for financial institutions, offering wealth managers and bankers AI-powered insights and recommendations that will help grow their book of business and deepen client relationships.

Big Data in Financial Services: Analyze-As-You-Go

In this contributed article, Hassan Mohamed, a London-based analyst specializing in financial operations and credit management in EU markets, explains where to hit in any organisation in order to monetize big data with an action plan. Also included is a comparison between 3 Vs and 5 Vs, a discussion of how to improve performance in any corporate department using big data, unquestioned answers about big data, and a clear action plan to monetize big data and gain the most of it.

Applying AI Technology to Reduce AML Risk for Global Financial Institutions

The proven field of AI and machine learning for anti-money laundering (AML) is the only technology that can effectively improve financial crime investigations, scale to the volume and velocity of the modern financial system, and counter criminals’ evolving approaches to money laundering. QuantaVerse published a new paper that examines how financial institutions can apply AI […]

How Data Science Can Save the Traditional Banking Industry

In today’s technologically advancing world, traditional banking groups are being seriously challenged. As Google, Amazon, Facebook, Apple offer more and more banking services and financial technology startups gain traction, the banking industry must take a look at how it can stay competitive. To do this, banking needs to rely on data science.

Mitigating IT Risk for Financial Risk Analytics

Financial Risk Analytics has evolved beyond a secondary regulatory and cost-focused perspective, to become a core part of businesses. Today, Risk Analytics provides a competitive edge by enabling businesses to efficiently use capital and manage risk exposures with higher confidence to make better informed and timelier business decisions. Hence CEOs increasingly rely on their CFOs and their Chief Risk Officers (CROs) for strategic advice and active risk management.