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Why You Need to Take Tech Seriously When It Comes to KYC

By Wayne Johnson, CEO & co-founder, encompass corporation. At the heart of any strong Know Your Customer (KYC) or Anti-Money Laundering (AML) programme is data. The ability to access and analyse information in a methodical way that ensures customer records are complete, accurate and, crucially when it comes to AML, compliant with the latest requirements,…

Don’t Believe the Hype

Wading through the hysteria to find an intelligent approach to AI By: Andrew Kouloumbrides, CEO of Xceptor. Having started its humble beginnings as a device to denote either a utopian dream or a dystopian nightmare in Sci-Fi novels, artificial intelligence (AI) is now well and truly finding practical applications and showing no signs of abating….

Data Science 101 – a CDO’s Viewpoint

By: Michael Conlin, Chief Data Officer at the US Department of Defense. The DoD selected me as its first Chief Data Officer to introduce new ways of doing new things. To that end, I’ve introduced new ways of thinking as well. Here is a snapshot. Ready, willing & able The number one criteria for launching…

Addressing the Challenges and Realising the Benefits of a ‘Cloud First’ Policy

By Andy Mather, European Financial Services Industry Specialist, Telstra. The move to a ‘cloud first’ policy by financial firms is a tantalising idea. After all, which chief technology officer wouldn’t want to seriously reduce their company’s on-premise compute and storage costs, while at the same time boosting agility and ability to profit from new, innovative,…

Data Governance a Top 2019 Priority, Says Syncsort

According to a new survey from Syncsort, a US-based provider of Big Iron (aka mainframes) to Big Data software, many firms are still struggling to make data accessible and get value from it, with 68% of respondents reporting that siloed data negatively impacts their organization. The 2019 Data Trends survey found that most IT departments…

Recorded Webinar: Listen to two buy-side CDOs discussing how to get data management right

Is your firm struggling to get cost-efficient data management in place to meet both strategy and regulatory requirements? Could innovative data management help to deliver much-needed business growth at your firm? Are you short of resources and skills to implement best practice data management? If your answer to any of these questions is yes, you…

Refinitiv Reviews Potential of Machine Learning and Problems of Data Quality

Machine learning and artificial intelligence (AI) have moved beyond the experimental stage to become core components of business strategy and investment. Key use cases include risk management, performance analysis and trading idea generation, ahead of automation and cutting costs. The whole is driven by growing numbers of data scientists employed by financial organisations. The barriers…

Data Management Innovation Delivers Significant Benefits, But it’s Not Easy

Innovation in data management can improve analytics, generate revenue potential, reduce costs, help companies monetise data and support digital transformation – but there are caveats, including the challenges of legacy systems, lack of budget and skilled resources, and cultural resistance. A recent A-Team Group webinar discussing how to leverage innovation in data management covered these…

Shape Releases AI-based Data Monitoring Solution for Data Management and Data Science

Shape, a Brussels-based start-up, has released a data monitoring solution for data management and data science that is built on machine learning and artificial intelligence (AI) technologies and designed to ensure data is trusted and fit for purpose. When used as a data management tool, Shape.AI allows data science and analytics teams to define their…

Recorded Webinar: Leveraging innovation in data management

Financial Institutions are going through considerable change as they look to deploy innovative technologies and solutions that could radically change data management processes and deliver operational and business benefits. This webinar will review innovation in data management – including technologies such as machine learning, pattern matching, artificial intelligence and solutions such as utilities and managed…