Uses of AI in Finance in 2020
AI is becoming increasingly important to the finance industry. Over the past several years, companies in the financial sphere have been integrating AI into their businesses in exciting and innovative ways. Below are just a few examples of how some companies are utilizing AI to improve processes, products, services, and customer experience.
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Throughout its 72 year history, Fidelity Investments has been committed to integrating tech into their business model. In the 1990s, the company created the Fidelity Center for Applied Technology (FCAT), which was an early adopter of the internet in the mutual fund industry.
More recently, Fidelity has turned to AI to help improve the customer experience. During calls, the company uses machine learning to determine who is calling and predict their needs in less than a second. Similarly, Fidelity’s chatbot relies on AI to improve the customer experience.
JPMorgan has made a very strong commitment to improving their customer experience with AI. Not only are they committed to implementing AI in their business, but they have also created an AI research program, headed by Manuela Veloso, who’s on leave from Carnegie Mellon University.
Some of the areas of research that the program is focused on include Safe Human AI Interaction, Machine Language and Vision, Secure and Private AI, and Multi-Agent Systems.
The human and artificial intelligence platform focused on providing stock trading insights, Tickeron, has recently released two new features for penny stocks. Using AI to evaluate penny stocks based on a series of fundamental metrics, Tickeron enables self-directed investors to identify the cheaper, penny stocks that are likely to provide substantial returns.
In addition to identifying patterns, the features also determine if they have historically yielded returns, data that can be used to evaluate the possibility of success in the future.
Mercatus, which helps private market investors better manage their data, recently released a platform update that enables customers to more efficiently extract data from PDFs. According to the CEO, Haresh Patel, this new service enables companies to “do in two or three minutes what traditionally has taken three or more days.”
Automating the process of extracting data from PDFs not only saves a considerable amount of time, but also reduces errors, enables businesses to extract information at scale, and frees up employees so that they can spend more time on strategy and other revenue-driving tasks.
Founded in 2014, ComplyAdvantage’s products help financial institutions comply with regulations and sanctions. It also helps prevent financial crimes, such as money laundering, by enabling companies to quickly and accurately identify potential bad actors.
To help reduce the number of false-positives and help companies keep up with rapidly changing information about sanctions, ComplyAdvantage has automated the process of updating their databases of companies and individuals accused of financial crimes. Having streamlined this process, ComplyAdvantage has made it easier for companies to identify possible threats and adhere to regulations.
[Related article: What Finance Companies are Excelling in AI?]
– ODSC West 2020: “Inverse Reinforcement Learning for Financial Applications” Igor Halperin, PhD | Research Professor of Financial Machine Learning | AI Asset Management NYU | Fidelity Investments
– ODSC Europe 2020: “How to Build and Test a Trading Strategy Using ML” | Stefan Jansen Founder & Lead Data Scientist | Applied Artificial Intelligence
– ODSC Europe 2020: “Automated Insights in Finance Using Machine Learning & AI” | Dr. Arun Verma | Head of Quant Research Solutions | Bloomberg