The AI Book

CHAPTER 38Dispelling the Illusion

By Richard Saldanha¹

¹Founder and Managing Director, Oxquant

We are still decades away from a true generalized machine or artificial intelligence but quantitative methods in general can be used far more extensively than most people suppose. Whilst such methods have typically been employed in the search for investment performance, the asset management industry spends far less time considering how quantitative methods can be used to improve profitability through cost savings or better task efficiency. Data-based automation is here now and those firms that fail to understand and embrace this fact will struggle.

Data-Based Automation

One of the biggest hurdles to applying good models with the aim of automatic decision-making is poor data management. The failure to design systems that can share data easily means that much time and effort is wasted wrestling data into the correct format. This assumes that relevant data are available in the first place. Many of the simplest questions posed by boards or risk committees can be difficult to answer because of incomplete data or the failure to collect the right data. Boards should not blame their IT departments for these failings. Instead, they should think in advance about the important questions that might need answering.

Planning carefully, collecting the right data, storing it in an appropriate manner (whether that is in a conventional relational, NoSQL or semantic graph database) and making sure ...