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Shaping Global Markets - Episode 1 ft. Naveed Asem, Chief Data & Analytics Officer

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Curious about data? How is machine learning and AI shaping our everyday life in a positive way? Find out the challenges with data today, how to establish a data governance program, and more about machine learning and AI. We also chat about the impact of “always being on” and the benefits of mindfulness practices. Tune into Episode 1 of Shaping Global Markets with Naveed Asem.


[Nataly] Welcome to the first episode of Shaping Global Markets presented by DFIN. My name is Nataly and I'm thrilled to bring you a series focused on key topics driving the regulatory and financial technology space forward. Every episode, I'll be joined by industry experts who will share their unique perspectives and personal philosophies that have shaped their careers and their vision for the future of the industry.

[Music Interlude]

[Nataly] In this episode, we uncover what makes data governance and standardization so critical to addressing your data quality needs. We'll also talk about the best way to spend your lunch hour according to our esteemed guests. I'm pleased to welcome Naveed Asem, chief data and analytics officer at DFIN. Now, let's dive in and learn about AI, machine learning, data, mindfulness, and more.

Hi Naveed, thanks so much for joining me.

[Naveed] Thank you for having me here, talking about some of these ideas around data.

[Nataly] Yes, thank you so much for being here Naveed. It's so exciting to have a chance to speak with you. I'm going to start with a little bit about what you've experienced throughout your career. What do you think is most critical for companies today in their data governance and standardization efforts?

[Naveed] Yeah, so to answer that question you have to understand why do companies do data governance and standardization. And the main goal around that is things like twisted decision-making.  So, if I'm a company, and I'm going to be buying another company or making decisions on mergers and acquisitions, I want to make sure that I'm making decisions based on data that is trustworthy. The other aspect of that is where you may be giving your data or exchanging it with other trusted partners.

When we go to regulatory bodies, and we are giving them data on behalf of our customers, our customers trust us with their data, and the SEC is expecting a level of trust on the data itself. As the middleman, at that point, we are making sure that the data is of high quality.

So, the most critical component in data governance programs and data standardization is:

  • Ensuring that the quality of data is fairly high
  • And ensuring that the quality of data stays high throughout the entire program

[Nataly] And is there anything that companies who are just in the beginning stages of addressing their data quality issues, that may not have certain skillsets that might be beneficial to them, what can they do as a first step to start a data governance program?

[Naveed] I love that question, mostly because it's also a coaching opportunity for me. So, first, we have to understand that the data quality problem, or the issues with data quality, is a pervasive problem. Basically, all organizations, small or large, they have it. And just to quote a few things, Gartner published an article that said, poor quality of data is costing companies 14 million dollars per year. And this is not even the complete picture because these are only the companies that know they're losing that much money. There are a lot of companies out there that don't even know how pervasive data quality problem is; they don't even know how much revenue they're losing. So, it could be upwards of 50, 60, even hundreds of millions of dollars per year! So, it's a fairly big problem.

The other thing I'll quote is a Forrester example. They published research where they said, one-third of analysts, like data analysts, they spend half of their time just massaging the data, cleaning the data up.

So, think about it this way, if you hire a data analyst and their job is to give you insights on data, they're spending half of their day, cleaning up the data.

So, the first step that I tell companies, or any organization…