It is indeed our fortunate to have the chance to learn from and interact with a number of senior leaders and professionals from various well-established financial institutions over the Wall Street Trek course. As a financial professional who has worked in the investment banking and asset management myself, I feel a lot of the topics and contents discussed very relevant to my everyday work scope. The one which leaves the most impression to me is the talk given by Mr.Andrew Chin on “Leveraging Big Data in Asset Management”.
The development of Artificial Intelligence and Big Data Technology in the recent years has on one hand created various investment opportunities for venture capital firms, more importantly,the technological evolvement has become an nonnegligible force which could potentially disrupt various business models of the financial markets. As a result, a growing number of market participants in the financial industry have started to roll out their strategy and implementation plan in this field by recruiting the talents with computer science and data analytics skills. Although it is still relatively early to observe any substantial contributions on revenue or profit generated by the big data technology, it is crucial for the large financial institutions to start early in order not to be disrupted in the future.
As the Chief Risk Officer and Head of Quantitative Research of Alliance Bernstein Group, Mr.Andrew Chin gave us a very systematic presentation on how the big data technology is changing the way of the global asset management and what the future opportunities and challenges are faced by the large financial institutions leveraging the big data. Mr. Andrew Chin has provided us with a very clear definition of the Big Data from four dimensions, namely volume of data, velocity to collect data, variety of data types and the truth or accuracy of data. The technological improvement of all four dimensions makes the big data much more relevant to the asset management industry of which various types o f asset owners select and incentivize different kind of asset managers to generate positive financial returns.First and foremost, big data could facilitate asset managers to optimize their investment decision process and enhance investment performance. For example, humongous amount of data from social media have been collected and analyzed by the investment professionals to identify early indicators which could provide insights on the result of major political and economic events such as Brexit, US election, and etc. The importance of social media data has almost surpassed that of the data from the main stream media in recent years. Data analytic techniques allow analysts to quantify traditionally qualitative factors such as opinions and behaviors, providing a new source of information for better investment decisions. However,there are still lots of noise in the data collected thus signals identified from such data tend to be short-lived. Going forward, new skillsets and tools for data analytics need to be further developed in order to create long-term benefits to the investment process.
Furthermore, big data could also be used by financial institutions to optimize sales productivity and client interactions. For example, browsing history could be collected and analyzed to enhance the customer profiling process so as to generate fine-tune message for a specific audience based on their needs and interests. However, privacy and confidentiality issues should not be ignored and it is still difficult for financial institutions to identify the effective right data to capture.
Big data and AI is one of the most important areas for my firm’s investment directions in the next few years and I appreciate the knowledge and insights shared by Mr. Andrew Chin over the presentation.
译文
