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Event Write-Up: SF Vegas 2022, July 2022

In July, we sponsored and attended the world’s largest capital markets conference, Structured Finance Vegas, hosted by the Structured Finance Association (SFA) at the Aria Resort & Casino.

With a schedule spanning three and a half days, SF Vegas brought together influential figures from a wide spectrum of fields including the financial sector, investors, regulators and more. The event covered a range of topics including CLOs and leveraged loans, technology developments in the structured finance space and leveraging AI to improve credit analysis. Addressing environmental, social and governance (ESG) issues was also a core focus at SF Vegas, encompassing the outlook for structured finance from a sustainability perspective.

At the Eigen booth, we had Jenay, Kyle, Jacob, Kevin, Patrick and Simone greeting attendees and taking meetings with delegates who were keen to learn more about our intelligent document processing capabilities. Our conversations gave us insights into where organizations and their structured finance teams are on their digital transformation journey, including the challenges and successes they have encountered by adopting progressive technologies. We also took the opportunity to join in discussions surrounding transformative AI and share our own insights on where advanced technologies can prevent issues before they arise.

On Day 3, our SVP of Product, Simone Bohnenberger-Rich PhD, joined a panel of experts from Canopy, FIS, TAO Solutions, MSCI and Yield Book to discuss leveraging AI to improve credit analysis. During the discussion, the panel shared ways that AI is adding value in credit analysis, the challenges associated with productionizing AI and the ways to improve data quality using innovative technologies.

To summarize, the event gave us some useful insights into challenges in the structured finance space and the ways we can help firms overcome them. These are our three key takeaways from SF Vegas:

  • We confirmed the industry is more than ready for AI adoption but there are still lingering concerns surrounding transparency., AI is often viewed as a black box where restricted visibility and auditability of data and decisions limit its usability for certain use cases. The Eigen platform has been designed to give users full visibility and control at each stage of the process.
  • We learnt that a common barrier to entry is the need to have hundreds of examples to train the AI models when typically, structured finance professionals are dealing with lower volumes of documents. The Eigen platform overcomes this problem as only small volumes of documents (0-50 examples typically) are required to train the models.
  • There is a growing demand for AI tools that put the business user in control, without needing additional tech support. By enabling models to be trained with a no-code user interface, the Eigen platform is designed to be accessible to any user for any use case.

Learn more about how our intelligent document processing platform can help business users in the financial services space and read our case study to find out how an investment management firm uses the Eigen platform to build robust datasets for risk assessment of their asset-backed securities.