Daloopa Review: Automate Financial Models for Swift Equity Analysis

Manual financial data entry is exhausting, right?

If you’re an analyst or investment professional, evaluating software for automating financial data collection often means sifting through clunky tools that can’t keep up with real-time demands.

What really stings is losing hours every week just copying numbers while critical deadlines pile up and your research takes a backseat.

Daloopa promises a smarter way, using AI to automate data extraction from SEC filings and earnings reports, hyperlinked for instant verification—so you actually get back your most valuable resource: time. Their Excel Add-in and flexible data delivery options help you update financial models within minutes, not hours.

In this review, I’ll dive into how Daloopa helps you finish with speed and confidence, letting you focus more on true analysis and less on data grunt work.

You’ll see, in this Daloopa review, a detailed breakdown of its features, pricing, limitations, and how it compares to similar tools—making your evaluation as straightforward as possible.

You’ll walk away knowing if Daloopa offers the features you need to stop wasting time and actually get ahead in your research and modeling.

Let’s dive into the analysis.

Daloopa Overview

I found Daloopa is laser-focused on solving one major headache for financial analysts. Based in New York City, they’ve been tackling the painful grind of manual data entry since 2019.

They almost exclusively target the institutional investment community. I see their sweet spot as serving demanding financial professionals at hedge funds, private equity firms, and investment banks who require deeper, more accurate historical data than what standard providers offer.

Their recent $18 million funding round in 2024 shows serious market momentum. Through this Daloopa review, you’ll notice how this investment is directly fueling their product innovation and ambitious plans for global expansion.

Unlike massive, all-in-one terminals like Bloomberg, Daloopa feels refreshingly specialized. Their key difference is automating tedious financial data work with an incredible obsession for accuracy and providing one-click, source-linked auditability for every single data point.

They work with the firms you’d expect: sophisticated hedge funds, private equity investors, and corporations whose financial models simply cannot tolerate errors or delays. These are high-stakes clients.

From my perspective, their strategy is clear: use proprietary AI to deliver hyper-accurate, auditable numbers much faster than legacy providers. This directly addresses your team’s need to stop copying data and start generating real insights.

Now let’s examine their core capabilities.

Daloopa Features

Is manual financial data entry slowing you down?

Daloopa features are designed to automate financial data extraction and model updates, which can significantly boost your team’s efficiency. Here are the five main Daloopa features that transform financial analysis.

1. Automated Data Extraction

Tired of manually sifting through financial reports?

Hours spent on manual data entry can steal valuable time from critical analysis. This often leads to missed opportunities and slower decision-making.

Daloopa’s AI-driven extraction processes SEC filings, earnings reports, and more, turning them into an auditable database. From my testing, this feature significantly cuts down data gathering time, allowing you to focus on high-value tasks. It constantly improves its accuracy too.

This means you can get accurate data faster, freeing your analysts to do actual analysis, not just data entry.

2. One-Click Model Updates

Does earnings season leave you scrambling for updates?

Manually updating financial models during earnings releases can be incredibly stressful and time-consuming. This delays your ability to react quickly to new information.

Daloopa’s Excel Add-in links your models directly to their database, updating figures with just a single click. What I love about this feature is how new data is delivered within minutes of earnings releases, often within 90 minutes for all updates.

The result is your team can incorporate new data rapidly, enabling faster insights and more timely investment notes without the manual grind.

3. Auditable Data with Hyperlinking

Can you always trust your financial data’s source?

Unverified data points can undermine confidence in your financial models and lead to costly errors. You need absolute transparency for sound analysis.

This Daloopa feature hyperlinks every single data point back to its original source document. Here’s the thing – one-click verification ensures transparency and builds trust in your analysis. This integrated verifiability is simply indispensable.

So, you get complete confidence in your numbers, knowing you can instantly verify any data point directly from its source, which is critical for compliance.

4. Comprehensive Historical Data & KPIs

Struggling to get deep historical financial insights?

Limited historical data from standard sources can prevent thorough analysis and a complete understanding of company performance. You need the full picture.

Daloopa provides extensive historical data, often 4-10 times more than competitors, including hard-to-find KPIs. This is where Daloopa shines; its depth of historical coverage supports in-depth analyses and broader market trend views.

This means you can conduct more robust, long-term analyses and build stronger cases for your investment strategies.

5. Flexible Data Delivery and Integration

Are data delivery options limiting your workflow?

Rigid data access methods can force you to adapt your workflows to the software, instead of the other way around. This can really slow you down.

Daloopa offers flexible data delivery via Excel datasheets and API integration, allowing seamless integration with your existing models. From my evaluation, data is delivered as hard-coded figures, which prevents formula issues and keeps your models fast.

What you get instead is the ability to access and utilize financial data in the format that best suits your specific needs and tools.

You’ll actually appreciate how these Daloopa features work together to create a robust, integrated financial data solution that accelerates decision-making for investment professionals.

Daloopa Pricing

What will Daloopa pricing cost your business?

Daloopa pricing follows a custom quote model, which means you’ll need to contact sales but also get pricing tailored to your specific needs.

1. Pricing Model & Cost Factors

Understanding the cost structure.

Daloopa’s pricing is subscription-based but customized, meaning no public tiers or fixed rates. Your final cost hinges on factors like company size, specific data requirements, and whether you need custom integrations. They tailor pricing to your diverse financial needs, serving various financial sector clients from hedge funds to investment banks.

From my cost analysis, this means your monthly costs stay aligned with your business’s scale and precise operational demands.

2. Value Assessment & ROI

Is this a smart investment?

While Daloopa’s services come at a “premium price,” their AI-driven automation significantly reduces manual data entry, saving countless analyst hours. From my cost analysis, this delivers substantial ROI through increased efficiency and accelerated decision-making, far outweighing the traditional costs of manual data compilation.

The result is your budget gains a highly efficient data solution, freeing up valuable human capital for high-value tasks.

3. Budget Planning & Implementation

Consider all your budget needs.

Beyond the core subscription, budget for project-based costs if you need extensive customization or integrations. What I found regarding pricing is that your first-year budget should account for these tailored services to ensure seamless deployment and integration into your existing workflows.

So for your business size, you can expect to allocate budget upfront for comprehensive implementation support.

My Take: Daloopa’s pricing prioritizes a tailored approach, making it ideal for enterprises within the financial sector that need precise, high-quality data solutions scalable to complex operations.

The overall Daloopa pricing reflects premium value for critical financial data automation.

Daloopa Reviews

What do actual customers think?

This section dives into Daloopa reviews, analyzing real user feedback to provide balanced insights into what customers truly experience with the software.

1. Overall User Satisfaction

Users are highly satisfied.

From my review analysis, Daloopa users consistently report high satisfaction, particularly regarding time savings and data accuracy. What I found in user feedback is how the platform effectively solves a major pain point for financial analysts, making their work significantly more efficient.

This indicates you can expect substantial improvements in your data handling workflows.

2. Common Praise Points

Time efficiency is a consistent winner.

Users repeatedly praise Daloopa for dramatically reducing manual data entry and model update times. From the reviews I analyzed, the one-click model updates are a game-changer during earnings season, allowing analysts to focus on higher-value analysis rather than tedious data input.

This means you’ll gain valuable hours back for strategic tasks.

3. Frequent Complaints

Some learning curve and cost considerations.

While largely positive, some Daloopa reviews mention an initial learning curve to master all functionalities. Review-wise, what stands out is how the premium cost might be a consideration for smaller firms or individual analysts seeking to adopt the platform.

These appear to be manageable trade-offs for the significant benefits offered.

The overall Daloopa reviews reflect strong user satisfaction for core functionalities, with minor notes on onboarding and cost.

Best Daloopa Alternatives

Seeking the perfect financial data platform?

The best Daloopa alternatives include several robust platforms, each catering to distinct needs for data breadth, analysis depth, and specific financial workflows.

1. Bloomberg Terminal

Need an all-encompassing financial ecosystem?

Bloomberg Terminal is ideal if you require a complete, integrated solution for real-time data, news, trading, and comprehensive market analysis. From my competitive analysis, Bloomberg is the industry standard for broad functionality, though its significantly higher cost makes it suitable primarily for large institutions.

Choose Bloomberg if your organization needs a single, integrated platform for diverse financial functions beyond data extraction.

2. FactSet

Prioritizing extensive data, analytics, and portfolio tools?

FactSet provides a wide array of financial data, advanced analytics, and portfolio management tools, integrated for investment professionals. What I found comparing options is that FactSet offers deep research and analysis capabilities, though like Bloomberg, it’s a high-cost enterprise alternative.

Consider this alternative when you need comprehensive financial data and a broad suite of integrated research and portfolio tools.

3. S&P Capital IQ

Focusing on in-depth company research and credit analysis?

S&P Capital IQ offers extensive financial data, research, and analytics, with particular strength in detailed company financials and industry analysis. From my analysis, Capital IQ excels in vast company-specific databases and robust screening, though Daloopa automates more granular data extraction from unstructured sources.

Choose S&P Capital IQ for in-depth company intelligence and broad market data, especially for credit analysis needs.

4. Canalyst

Preferring pre-built, customizable financial models?

Canalyst provides ready-to-use financial models for a vast number of public companies, accelerating your analysis and model initiation. What I found comparing options is that Canalyst delivers robust, pre-populated financial models, though Daloopa focuses more on precise, auditable extraction directly into your custom models.

Choose this alternative when starting with pre-built, comprehensive financial models is a higher priority for your team.

The best Daloopa alternatives depend on your specific data needs and workflow priorities rather than just feature lists.

Daloopa Setup

How complicated is Daloopa’s setup process?

The Daloopa review reveals a streamlined deployment, particularly for financial analysts accustomed to Excel. This section breaks down what your business can expect during implementation.

1. Setup Complexity & Timeline

Not a daunting, months-long project.

Daloopa implementation is notably straightforward, leveraging familiar Excel add-ins and datasheets, minimizing complex IT overhauls. What I found about deployment is that integration with existing financial models simplifies initial setup, making the process less about installing new infrastructure and more about integrating data flows.

You’ll primarily plan for data mapping and familiarization with the tool rather than extensive system overhauls.

2. Technical Requirements & Integration

Minimal new infrastructure needed.

Your technical requirements are primarily centered on internet connectivity for cloud-based functions and compatibility with standard financial software. From my implementation analysis, Daloopa integrates seamlessly with existing Excel workflows, meaning heavy hardware or complex custom API development is generally not required.

Prepare for internet stability and ensure your existing financial modeling environment is up to date for optimal performance.

3. Training & Change Management

User adoption focuses on workflow shifts.

While Daloopa is user-friendly, new users will face a learning curve to fully utilize its automated data extraction capabilities for in-depth analysis. From my analysis, successful change management hinges on highlighting time savings and empowering analysts to leverage automated data effectively for higher-value tasks.

Invest in readily available tutorials and encourage exploration to help your team adapt to faster, more accurate data processes.

4. Support & Success Factors

Vendor support drives efficient integration.

While specific metrics are private, Daloopa’s focus on enterprise clients suggests a commitment to responsive customer success during your implementation. What I found about deployment is that leveraging their support ensures you maximize data accuracy and integrate the tool efficiently into your unique analytical frameworks.

Plan to engage with Daloopa’s resources early to streamline your integration and optimize the platform’s benefits.

Overall, Daloopa setup emphasizes integrating with existing analyst workflows rather than demanding a complex, time-consuming IT overhaul.

Bottom Line

Does Daloopa fit your financial data needs?

This Daloopa review reveals a specialized tool for financial professionals who need to escape manual data entry and elevate their analytical focus.

1. Who This Works Best For

Financial professionals buried in manual data.

Daloopa is ideal for equity research analysts, hedge funds, private equity, and investment banks that spend excessive time on data entry and model updates. From my user analysis, firms needing extreme data accuracy and auditability for public company financials will find immense value.

You’ll succeed if your team aims to shift from “monkey work” to high-value analysis and strategic decision-making.

2. Overall Strengths

Unmatched data accuracy and time-saving automation.

The software shines with over 99.9% data accuracy, one-click model updates, and unparalleled auditability via hyperlinked source data. From my comprehensive analysis, its AI-driven automation dramatically reduces manual effort, freeing analysts to focus on deeper insights rather than data scrubbing and verification.

These strengths directly translate to enhanced efficiency and more timely, confident investment decisions for your firm.

3. Key Limitations

Premium pricing requires careful budget consideration.

While powerful, Daloopa’s enterprise-grade solution comes at a premium, potentially posing a barrier for smaller firms or individual analysts. Based on this review, new users might experience a learning curve to fully exploit all the platform’s advanced functionalities and integration capabilities.

I’d say these limitations are understandable trade-offs for the high-quality, specialized service you receive.

4. Final Recommendation

Daloopa earns a strong recommendation for specific users.

You should choose Daloopa if your financial team is plagued by manual data entry, needs rapid, accurate model updates, and prioritizes auditable data. From my analysis, this solution empowers high-value analysis by automating tedious data collection, making it indispensable for specific financial roles.

My confidence is high for investment firms seeking to boost efficiency and accuracy in their data workflows.

This Daloopa review shows significant value for specific financial teams, highlighting its ability to transform data workflows and accelerate decision-making.