Big Data and Financial Technology

Financial markets have undergone a remarkable transformation over the past two decades due to advances in technology, including faster and cheaper computers, greater connectivity among market participants, and tremendous amounts of data. This era of big data has brought many new benefits to investors including more sophisticated trading algorithms, lower transactions costs, faster execution times, and greater volume of trade. However, big data has also brought unintended consequences in the form of loss of privacy and identity theft, “flash crashes,” botched IPOs, and business-ending trading errors at the speed of light. In this research program, we focus on both positive and negative aspects of big data and financial technology in an attempt to identify and measure the magnitude of emerging problems as well as develop new technologies to address them. Examples of this research include machine-learning models for consumer credit risk management and applications of secure multi-party computation to financial regulation.

Current Research

  • Risk and Risk Management in the Credit Card Industry
    Florentin Butaru, Qingqing Chen, Brian Clark, Sanmay Das, Andrew W. Lo, and Akhtar Siddique
  • Software Engineering and the Structure and Evolution of the United States Code
    William Li, Pablo Azar, David Larochelle, Phil Hill, and Andrew W. Lo