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A.I. in Finance: Technology as a Skill for Non-Engineers

A.I. in Finance: Technology as a Skill for Non-Engineers | IE Business School

Students discuss anti-fraud technologies and stock picking.

Ignacio Larrú Martínez, CFO at K FUND, spoke to IE Business School students about the role of artificial intelligence in the financial sector, the democratization of technology and how important it is for non-engineers to foster technological knowledge to drive business success.

Larrú explained in a webinar format the core concepts like machine learning, deep learning, neural networks, and node layers mimicking human neurons. He also addressed finance-specific issues like anti-fraud technologies and stock picking.

He invited students to reflect on the democratization of technology and how tech practices have shifted from a specialized vertical knowledge for engineers to a more mainstream horizontal skill that is present and has an impact in a wide array of sectors and industries.

“Back in the day, there used to be a clear separation between engineering backgrounds and other backgrounds. That separation has been blurred by the horizontal nature of technology.”

Ignacio Larrú Martínez, Adjunct professor of Technology Entrepreneurship and Big Data at IE Business School

In addition to the tech talk, the webinar laid out specific steps on how to implement artificial intelligence models and handle data for business ventures. Larrú shared the three main benefits of applying A.I. for financial institutions: increasing revenues, reducing costs and increasing competitive advantage due to upscaling opportunities.

The webinar was an introduction to the Executive Education Online Program, Fintech: Powering the Financial Revolution offered by IE Exponential Learning. A five-week program where Larrú reviews different technologies and will discuss application technologies in the financial world.

Larrú talked about the future of A.I. and about how user-generated data powers the digital revolution.

“For the last 15 years, we have digitalized our lives, leaving a digital trail,” he said. “Our digital footprint and habits are the raw materials for artificial intelligence and machine learning technologies.”