Credit Suisse

Credit Suisse Leads Investment of $20 Million in Daloopa

Credit Suisse has led a $20 million Series A round of funding in the data extraction startup Daloopa and it was joined by the existing investors like Nexus Venture Partners, Hack VC, and others.

The company would be utilising the funds to upgrade the technology and increase the set of features on its platform which helps to remove the need for data entry by identifying and extracting financial data from structured and unstructured documents and files.

“This was a big enough problem for one company to support all of the data analysis and forecasting without having to manually convert the data,” said company CEO Thomas Li. “This frees up analysts to then do what they are supposed to do.”

Li was actually working in a hedge fund where he witnessed firsthand the amount of documentation that needed to be done and also saw that the users were spending about a third of their time in filling out and reading financial data and in documentation as well. Once the right technology came up, Li and his partners got to work on the platform which uses an advanced form of AI which helps to give more than 99% accuracy in the financial data. As is well know in financial circles, the accuracy of the data is very important and this is one of the reasons why such ideas did not get too much traction in the past as even the AI-based models could not exceed 99% in their accuracy.

The company has not revealed any of its revenue numbers but it is reported that it has over 40 enterprise customers so far. The new funds that have been received in likely to be used for more sales and growth globally in the coming months.

The platform was initially used for extracting public company financials but of late, it is being used even for private documents like what financial entities like banks give to their customers to collect data and for other purposes. This product needs to be further developed and expanded so that it can take in and deal with other kinds of documents as the financial firms always grapple with a huge amount of financial data that cannot be easily extracted or analysed by a human mind. So, a platform that does this with almost 100% accuracy is likely to do well in financial circles.