Financial data and automation specialist Daloopa has incorporated the latest artificial intelligence technology into tech from last century to accelerate the search from alpha among equity investors.
The US-based startup has built Daloopa Scout, an agent that bolts onto researchers’ Excel software and builds investment models from scratch. Further, the agent is designed to work within the modeling conventions and workflows researchers already use.
The benefit to organisations including banks, hedge funds and asset managers, is that it can generate investment ideas in a tiny fraction of the time it would ordinarily have taken organisations to simply build the thesis-generating models. That it is built for a software package that was first introduced by Microsoft 41 years ago is besides the point, said Daloopa Chief Executive Thomas Li.“We want to meet our clients where their problems are with our data… and our customers are in Excel more than any other piece of software,” Li told Data Management Insight. “It is far and above the most commonly used piece of software because it is how investments are penciled down.”
Data Layer
Scout harnesses Daloopa’s structured, verified data layer to enable analysts to build models, update existing models and compare companies across an industry using plain-language prompts.
The company enlisted former analysts to design Scout and have it run on analysts’ existing Excel workflows. The add-on can pull financial data from filings and verify each figure. It also features “skills” that can be applied to give workflows additional capabilities.
The agent was tested in the field by a select number of Daloopa clients and is now available across its eligible customer base.
Li said that Scout can be configured to encompass the nuances, data and “many moving parts” that need to be incorporated into analysts’ models.
Accuracy is essential, he said, because “the model is actually a piece of software, the model is a simulation of a business”.
Global Reach
Scout models all have access to Daloopa’s verified, structured database that covers more than 6,000 public companies globally. Data is hyperlinked to its original source, enabling analysts to review models without searching through the underlying filings and leaving their workflow, the company said.“This combines the speed of AI-generated modeling with the data traceability and accuracy analysts require,” Daloopa explained in a statement.
One of the key features, according to Li, is the Scout agent’s ability to use its skills to replicate the approach of individual users.
“Scout can incorporate the knowledge you have, and start acting like you the next time it builds a model for you,” Li said. “It’s not just an analyst that knows how to build a model. It’s an analyst who, over time, will learn how to build a model in your way. It becomes your pocket analyst that serves you only.”
New Capabilities
Scout is the latest development by Daloopa. After launching its data services, the company built an API to accelerate smart data delivery and more recently added model context protocol (MCP) connectivity to enable the integration of its data with that from multiple other sources in clients’ systems.
“The deterministic Excel add-in will provide clients not only powerful new analytical capabilities,” said Li.
“Getting high-quality ideas takes a lot of time in raw human hours, and some of the larger companies will have thousands of analysts just sitting there churning out ideas,” he said.
“So if I could say you no longer have to build a model, you just have to consume a model, it dramatically increases the amount of time you have to consume analysis, therefore increasing the number of ideas you can have.”
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