Episode 1
Tech For Good: How HSBC Uses Technology To Combat Crime
As one of the largest banks in the world, HSBC owns huge amounts of data – but understanding the networks and relationship within that data can be a challenge. In this episode, Vishal Marria speaks with Jennifer Calvery, Head of Financial Crime at HSBC, to see how the bank is using technology to manage its data effectively and improve financial crime detection to tackle horrific crimes, from terrorist financing and human trafficking.
Episode 2
Tech For Good: How SCB is Revolutionizing Investigations
Enterprises have vast amounts of data but often lack the software to maximize the value of all this information – resulting in missed risk. However, Standard Chartered Bank has made huge strides to harness the power of data to revolutionize financial crime investigations. David Howes, Global Co-Head of FinCrime Compliance at Standard Chartered Bank, shares how the bank is using contextual decision intelligence to enhance investigations.
Episode 3
How Allianz Is Transforming Using Tech
With the right technology, insurance firms can maximize the value of data to drive better decisions. In this episode, Vishal Marria speaks with Andrea Pettinelli, CFO at Allianz, to discuss the challenges of adopting technology across the enterprise and the role of data in customer-centricity.
Episode 4
How Danske Bank Is Adopting Data and Analytics Technology
To maximize the value of data, enterprises need to have the right IT infrastructure in place. In this episode, Vishal Marria, CEO at Quantexa, speaks with Bo Svejstrup, CIO at Danske Bank on resolving legacy challenges around data, improving collaboration between business and IT, and the future of cloud adoption.
Episode 5
Creating Value For The Enterprise Using Data
Data is the center of decision-making. In this episode, Vishal Marria, CEO at Quantexa, speaks with Dr Anthony Scriffignano, Chief Data Scientist at Dun & Bradstreet, on how to overcome common data challenges, as well as the emerging trends in digital resilience, AI and machine learning, and data and analytics.
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