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A-Team Insight Blogs

Canoe Extends Data Ops Capability, Plans Geographic Expansion

Despite the coronavirus pandemic, 2020 has been a promising year for Canoe, a data ops vendor that takes manual effort out of alternative investment processes by using machine learning and AI to automate the digitisation of unstructured PDF reporting documents and provide actional data and intelligence for institutional investors, allocators and asset servicing firms.

To track the company’s progress and future plans, we caught up with recently appointed CEO, Jason Eiswerth, who replaced founding CEO Seth Brotman a couple of months ago. Eiswerth has the remit to to further expand the company’s footprint within North America and beyond, while Brotman becomes president and focuses on product development, operations and building out the company’s client services team.

Reflecting Canoe’s decision to strengthen its management team, Eiswerth says: “Alternatives allocation is growing, but it still has data management and reporting challenges. Handled manually, the alternative investment process is time consuming and expensive. Some firms get to a minimal data set they can survive with. This is not a good solution, they need to really understand investments to make good decisions.

“The genesis of Canoe is in making data ops that are a big expense for large companies more efficient and able to provide more accurate data and broader value. With better data, firms in alternatives don’t have to worry about extraction and validation, and can move on to analytics and making better decisions.” He acknowledges that there are generic extraction tools from the likes of Google in the market, but says: “Our solution is specific to alternative investment data. You need to understand the data and get it right.”

In terms of Canoe’s initial capability delivered by its solution Canoe Intelligence, Eiswerth says: “We are very good at extracting and validating data from documents on a client by client basis. Large clients can use our service to slice and dice data at scale with less resources and more accuracy. At one large client, we accelerated its ability to report to its clients by 30 days. This changes the game.”

Extending this capability, the company has this year implemented an intelligent software layer across its solution that provides efficiencies through scale. Once documentation is digitised and validated for one fund – this is the heavy lifting, multiple clients in the same fund can access accurate data in less time.

Canoe is also expanding the range of documents and datasets it manages, as with more and broader data sets, clients can understand funds at a more granular level. Eiswerth says: “We have a huge database of documents clients can draw from. Using machine learning on large historical data sets they can see patterns and trends in alternatives, and with our UI they can select whatever data points they want.”

Since Canoe was set up in 2013, it has attracted more than 50 customers and built a team of about 30 people that it is looking to expand with more experts in data engineering and product development. With headquarters in New York City, it is also keen to set up shop in Europe, most likely through an initial office in London, and then, perhaps, extend its reach into the Middle East.

Meantime, Eiswerth concludes: “It has taken us seven years to evolve Canoe Intelligence and in 2020 we got it right. We now have a scalable infrastructure that we can expand and technology that we can develop us to the next level.”

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