Daloopa

Company Overview

Daloopa is a financial technology company that provides AI-powered document automation and data extraction solutions for the financial services industry. The company was founded in 2019 and is headquartered in New York City, with additional offices in San Francisco and Noida, India.

Daloopa’s core offering is a platform that uses artificial intelligence to extract and organize financial data from company filings, investor presentations, and other sources. This allows investment professionals to access comprehensive historical financial data for over 3,000 public companies in a format that can be easily integrated into financial models and analysis.

Products Overview

Daloopa’s main product is a data platform and Excel plugin that provides:

• Comprehensive historical financial data for 3,000+ public companies
• AI-powered data extraction from SEC filings, investor presentations, earnings call transcripts, and other sources
• Excel plugin for updating existing financial models with the latest data
• Ability to audit and verify data sources
• Customizable dashboards and KPI tracking
• API access to financial data

Key features of Daloopa’s product include:

• Auditability: Every data point is linked back to its original source document
• Flexibility: Data can be used in any Excel model format
• One-click model updates: Existing financial models can be updated instantly with new quarterly data
• Deep dataset: Captures granular KPIs and metrics beyond just high-level financials
• Excel integration: Works within existing Excel-based workflows

Founding Team

Daloopa was founded by:

• Thomas Li - CEO
• Jeremy Huang - CTO
• Daniel Chen - COO

The founders previously worked together at Point72, a hedge fund in New York City. Their experience there inspired them to create Daloopa to improve the accuracy and efficiency of financial data processes.

Problem and Market Fit

Daloopa aims to solve several key pain points for investment professionals:

1. Manual data entry and financial modeling is time-consuming and error-prone
2. Existing financial data providers often have limited historical data and granularity
3. It’s difficult to audit and verify the sources of financial data
4. Updating existing models each earnings season is tedious and inefficient

By automating data extraction and model updates, Daloopa allows analysts to spend more time on high-value analysis rather than manual data entry. The company’s focus on auditability and flexibility also addresses key needs in the institutional investment space.

Business Model

Daloopa operates on a subscription model, likely charging financial institutions based on number of users and data access. The company offers both self-serve access through its marketplace as well as enterprise solutions for larger firms.

Funding and Runway

Daloopa has raised venture capital funding, including a Series B round announced in 2023. Specific funding amounts were not disclosed in the available materials.

Notable investors include: - Touring Capital - Morgan Stanley - Nexus Venture Partners

Competitive Landscape

Daloopa competes in the financial data and analytics space. Some potential competitors include:

• Traditional data providers: FactSet, S&P Capital IQ, Bloomberg
• Fintech startups: AlphaSense, Sentieo, Tegus
• Internal solutions developed by large financial institutions

Daloopa aims to differentiate through its AI-powered data extraction, focus on model updating workflows, and emphasis on auditability.

Customers

While specific customers are not named, Daloopa mentions that its users include:

• Hedge funds
• Mutual funds
• Private equity firms
• Equity research analysts
• Investment banks

The company states that many top holders of major stocks like Amazon, Disney, Uber, Meta, and others use their product.

Relevant News

In 2023, Daloopa announced the closing of its Series B funding round, though specific details were not provided. This indicates the company is in a growth phase and expanding its offerings.