Artificial Intelligence for Asset Management and Investment by Al Naqvi

Author:Al Naqvi [Naqvi, Al]
Language: eng
Format: epub
ISBN: 9781119601845
Published: 2021-02-09T00:00:00+00:00

What is so special about flywheel? More importantly, why do so many firms—in all sectors—struggle to embrace the concept of flywheel? Why are so many executives and managers trying, but failing, to get it right?

The difference, in a nutshell, is that firms are not thinking competitive advantage. In a fast-paced world where competition can strike from any side, investment management firms have not figured out how to blend their artificial intelligence pursuits with their firm's overall strategy. They approach them as two different areas. This creates a void, and that void is being filled by siloed projects.

Siloed innovation is not modernization. It is a burden. Sooner or later, it will lead to value loss. Machine learning, when approached in a siloed piecemeal manner, will create more problems than solve them. In fact, companies are finding out that 75 to 85% of their AI projects are failing or failing to impress executives (Nimdzi 2019). The real problem is not that AI projects are failing. I firmly believe that the real problem is that firms are approaching AI as projects. AI is not “projects.” AI is a way of life. It is a transformational change. It is a strategy. It is the new way to operate your business.

What you must do is modernize your asset management firm and do it systematically and with a plan. You do that by moving your firm to a science-oriented firm. Becoming a science-oriented firm is key to acquiring the competitive advantage your asset management business needs, and these days the only way to become a science-oriented firm is by building your firm around artificial intelligence.

The question is how to build a flywheel for an asset management firm. What would that plan be? What will an investment science firm look like when it is transformed?

Part 2 will show you how to build your firm around AI. It will challenge you to think differently. It will link business outcomes with an artificial intelligence–centric transformation.

In a world dominated by hard-core technology researchers and mathematicians on one side and soft-skilled graduates of management schools on the other side, we will erect a bridge where the two sides can meet. The innovation spark happens when the two come together.

The line of thinking is built upon approaching strategy from a flexible perspective where innovation and change in markets are constantly tracked and considered. The execution layer is designed to be responsive and adjustable to the changing plans.

However, before we introduce the model, it is helpful to first address two questions:

What about all the cognitive and digital automation projects that IT teams are currently engaged in in your firm—isn't that building your firm around AI?

Why should you shape your firm around AI?

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