Clarifo vs Fiscal.ai vs Börsdata: A Research Workflow Comparison

Clarifo vs Fiscal.ai vs Börsdata is a comparison of research tasks, not a contest for the longest feature list. We combine US and Nordic filings, structured financials and source-linked research in a REST API and an MCP connection. Fiscal.ai documents global fundamentals, estimates, filings and source-linked AI research skills. Börsdata offers financial history, ratios, screening and API or spreadsheet access. A buyer should decide first whether the daily work is a sourced earnings note, a estimates-driven model or a historical stock screen.¹²³

We reviewed the providers' public product and API documentation on 4 November 2026. We did not run paid-account benchmarks against all three, so this article does not rank data accuracy, query speed or total cost. Those require a controlled trial with matching entitlements. What we can compare rigorously is what each provider explicitly documents, where a workflow has a discoverable source trail and how to test the same difficult accounting question on all three.²³

The decision matrix

Three questions matter more than raw coverage claims: can you retrieve the statements you need, can you trace important numbers back to the filing, and does the interface fit the way your team actually works? The table distinguishes documented features from capabilities not established by the specific public pages reviewed. “Not established” does not mean a vendor lacks the feature.

A better test than ticking feature boxes

We would test all three services against Target Corporation (NYSE: TGT)'s second quarter of fiscal 2026, ended 1 August 2026. Target reported USD 2,560 million of GAAP operating income, compared with USD 1,317 million a year earlier. The striking 94.4% growth is real as reported, but it includes USD 994 million of pretax benefits from tariff refunds. An application that presents the growth figure without that accounting context risks overstating the underlying operating improvement.⁴⁵

Target also quantified the tariff refund effect as USD 1.65 of diluted EPS, out of USD 4.11 reported for Q2 FY2026. Removing that stated benefit as a simple illustrative subtraction gives USD 2.46 per share. This is not an issuer-defined adjusted EPS and does not capture every possible normalization; it is an analyst sensitivity designed to force the software to retrieve the explanatory note. The provider should not silently label the result “adjusted earnings.”⁴

This is a more instructive product trial than counting company tickers. Ask each service for the same quarter and for a citation explaining the gain. Check whether it returns the original issuer table, whether the period end is explicit, and whether it distinguishes issuer-reported from analyst-calculated metrics. Then repeat with a Nordic IFRS reporter and a year-to-date cash-flow line to expose currency and period issues.

Where Fiscal.ai can be a better fit

Fiscal.ai's public API reference documents as-reported and standardized financial statements, segment data, ratios, consensus estimates, share prices, insider and institutional ownership and document sourcing. Its MCP skills are explicitly source-linked and can open filing pages inside its terminal. We should not imply that filing-page evidence is exclusive to us; the real evaluation is what source format, depth, entitlement and retrieval speed fit a buyer's workflow.²⁶

If the daily model relies on street consensus, fund ownership and regional estimates, the depth and licensing of those datasets could dominate any preference for our filing-first approach. For an institutional buyer, ask for a sample of companies across intended markets, check how estimates are timestamped and whether source images are available in the contracted API package. A source trail should be evaluated in the paid configuration actually under consideration.

Where Börsdata can be a better fit

Börsdata's website emphasizes historical ratios, screening strategies, stock-price data, Excel and Google Sheets integrations. Its API page describes downloading company information, prices, reports and key figures as JSON across Nordic and global companies. It says coded REST API access was moved to PRO+ from 1 February 2025. That is a subscription question, not a data-quality score: a spreadsheet-driven investor may have different requirements from a fintech building a multi-tenant product.³⁷

For a disciplined factor screen, test how many years of consistent reported revenue, margin, invested capital and free cash flow the user can export. Check how each service handles restatements and discontinued operations. A historical ratio that changes definition in the middle of a series can distort screening as seriously as a missing filing citation can distort a research note.

Where our workflow earns its place

Our Data API supports structured SEC and Nordic issuer retrieval, while MCP brings the same research questions into Claude and ChatGPT. We focus on moving between a financial figure and the report that supports it. The distinguishing claim we are willing to test is not that our numbers are uniquely correct; it is whether the original report remains accessible at the point of analysis. We have documented a separate US quarterly data quality checklist for that purpose.¹⁸

A team that primarily models consensus expectations may prefer Fiscal.ai, while an investor who wants familiar historical screeners and spreadsheet outputs may prefer Börsdata. A team writing source-backed investment notes across covered US and Nordic companies should test our workflow on a disclosed unusual item such as Target's tariff refund. The purchase decision depends on the actual user task and covered companies, not on a universal winner declared by a vendor.

How to run the comparison fairly

Create a small fixed evaluation set: Target Q2 FY2026, one recent Helsinki reporter and one Stockholm reporter. Define five tasks in advance: locate the freshest published report, return reported net sales, retrieve statutory operating profit, explain an unusual non-GAAP or one-off item, and export a sourced table. Record wrong periods, missing figures, unavailable source links, rate limits and the analyst time needed to repair the output. Also ask for a written quotation of the current contract and API terms.

This method has a built-in counterargument to our positioning: if another service completes the work more accurately or more economically for a given team, use it. A product comparison should help the reader choose, not ask them to infer quality from branding. We invite readers to test the same source-backed financial question with their own company universe and make the result independently reproducible.

Sources and methods

Provider sources checked 4 November 2026: Clarifo API, Clarifo MCP, Fiscal.ai API documentation, Fiscal.ai source-linked MCP skills, Börsdata API, and Börsdata website. Financial test: Target Q2 FY2026 issuer earnings release and SEC Form 10-Q for the quarter ended 1 August 2026. The ex-refund sensitivity is simple subtraction of stated amounts, not an independent earnings normalization.