David K.A. Mordecai Participated in Demo Day 2020 for FinTech Innovation Lab

Print Friendly, PDF & Email

David K.A. Mordecai participated in Demo Day 2020 for FinTech Innovation Lab (FTIL) on June 25, 2020, as Scientist-in-Residence for FTIL. FTIL is an accelerator platform for early and growth stage technology firms, organized by the Partnership Fund for New York City, in conjunction with Accenture and a consortium of venture capital firms and global financial institutions.

As Scientist-in-Residence for FTIL, David K.A. Mordecai is one of six distinguished senior advisors who are members of the FTIL Mentors Network, comprised of seasoned entrepreneurs that have successfully launched and scaled a financial technology company to acquisition or IPO. Members of the Network serve as mentors and informal advisors for companies accepted into FTIL, providing guidance on the broad range of issues faced by senior management of financial technology (FinTech) companies.

Due to the COVID-19 pandemic, the entire FTIL 2020 cycle was conducted remotely. In addition, FTIL Demo Day 2020 was held remotely via YouTube, making it the first such FTIL Demo Day to be conducted entirely online.

David Mordecai leads research activities at RiskEcon® Lab @ Courant Institute of Mathematical Sciences and is President of Risk Economics.

FinTech Innovation Lab

Demo Day 2020
Applicants to FTIL must have at least a working beta version of their technology that is ready for testing in either the institutional or retail market. The Chief Technology Officers from the 43 supporting financial firms selected the current set of ten participants for the 2020 cycle:

  • Alkymi: “Uses machine learning to create a data inbox that extracts business data from email and documents to accelerate business processes.”
  • ArthurAI: “A production Artificial Intelligence (AI) monitoring platform that seeks to provide enterprises with the tools to detect model performance issues proactively, provide auditability and explainability to black box decisioning, and measure algorithmic bias to ensure fair decisioning.”
  • Broker Buddha: “A software-as-a-service (SaaS) platform for independent agents that helps them grow their business through interactive customer, friendly, online applications.”
  • ClauseMatch: “A content collaboration platform seeking to enable financial institutions’ global compliance and risk teams to interact with, review and approve centralized policy documents with a precise audit trail mapping them to regulatory obligations to help ensure regulatory compliance.”
  • Datafleets: “An enterprise federated intelligence platform that uses machine learning to analyze unseen, sensitive data to generate business insights without compromising data privacy.”
  • Knoema: “A knowledge and data management firm that works with corporates, buyside and sellside firms to manage, catalog and discover all of their subscription, public and internal data assets.”
  • Sigma Ratings: “A counterparty risk platform that seeks to leverage machine learning and deep domain expertise to enable automated entity-level risk benchmarking and ongoing monitoring of non-credit risks at scale.”
  • SkyHive: “An AI technology that seeks to transform the reskilling process for workers and workforces. SkyHive rapidly identifies internal skill sets, compares to the external labor market, identifies emerging and future skills, and automates the navigation of reskilling to the future state in real-time.”
  • Summer: “Seeks to help student loan borrowers lower their debt by using technology and industry expertise to identify and enroll them in the best possible repayment plan for their financial situation.”
  • True Flood Risk: “An AI-driven property risk management platform that seeks to provide individual property level data & real time analytics helping banks, insurers, property owners and risk mitigation experts identify and quantify the financial impact of flood risk in real-time.”

About RiskEcon® Lab @ Courant Institute
The mission of RiskEcon® Lab for Decision Metrics @ Courant Institute of Mathematical Sciences is the development of experimental testbeds and analytics that employ high-dimensional datasets from innovative sources by applying a range of computational and analytical methods to commercial and industrial sensor networks and edge computing embedded systems, focusing primarily on research and development (R&D) of remote- and compressed- sensing, anomaly detection, forensic analytics and statistical process control. By employing applied computational statistics within the context of robust and scalable data analytic solutions, our goal is robust integration of machine learning with signal processing for measurement and control, in order to conduct research fundamental to large-scale, real-world questions in risk and liability management.

RiskEcon® Lab enables, facilitates and coordinates academic research focusing on these patterns and trends, through the development of commercially-viable, analytic applications employing computational statistical tools in conjunction with innovative and non-traditional data structures. In addition, the lab’s activities involve the advancement of applied mathematical statistics and computational economics, through interdisciplinary post-doctoral, postgraduate, graduate research and education in data science and social computing.

RiskEcon® Lab for Decision Metrics was established in 2011 at Courant Institute of Mathematical Sciences, an independent division of New York University (NYU). Courant is considered to be one of the world’s leading mathematics educational and scientific research centers, and has been ranked first in research in applied mathematics. RiskEcon® Lab is the cornerstone of the Computational Economics and Algorithmic Data Analytics (CEcADA) cooperative at New York University, established concurrently in 2011.