The Financial Analyst — Agentic analysis for CFO-level decisions
Corporate finance teams face a structural tension: the decisions that matter most — credit exposure, capital allocation, portfolio performance — demand analysis that is both fast and rigorous. This is not a problem of talent or intent. It is a problem of analytical infrastructure.
This page presents a fully operational agentic system I designed and built for decision-making in corporate finance. It is not a product; it is a demonstration of how agentic analysis — designed with the right frameworks and the right quality controls — can remove friction from executive decisions.
The binding constraint is rarely access to the data.
It is the friction that sits between asking the right questions and finding relevant answers.
The Financial Analyst does not replace the CFO's judgment; it concentrates and systematises the analysis that judgment relies on — producing decision briefs across three domains from a single, consistent workflow.
Three CFO Domains
The Problem
A CFO authorising credit exposure — to a counterparty, a borrower, or a joint venture partner — needs more than a financial summary. They need a structured view of debt serviceability, covenant headroom, liquidity under stress, and the structural conditions that could accelerate or contain default. That analysis is time-consuming to produce consistently, and quality varies depending on who runs it and when.
What It Produces
A structured credit brief with an executive summary built around four blocks — credit profile, key risks, structural protections, and recommendation — followed by a full assessment covering capital structure, debt capacity, stress scenarios, and qualitative probability of default. Appendices hold the technical data; the brief is executive-ready.
The Standard It Applies
Credit analysis grounded in public financials, live market data, and a stress framework designed to surface the scenarios that matter — not the base case, but the conditions under which the exposure becomes a problem.
The Problem
Before a finance team commits weeks of bandwidth to due diligence, a prior question needs answering: is this target worth the cost of looking closely? That screening judgment — is this a good business, at what price, with what structural risks — is often made informally, inconsistently, or not at all. The result is either wasted due diligence capacity or missed opportunities that never made it to the table.
What It Produces
A structured investment brief covering business quality, competitive position, financial performance, and valuation against sector benchmarks. Designed to answer the two questions that matter before committing time and resources: is this a good business, and what is the right engagement structure? A pre-diligence screening instrument, not a substitute for it.
The Standard It Applies
Relevant valuation frameworks, live peer multiples, sector margin and WACC benchmarks — applied rigorously at the screening stage, so that the decision to commit due diligence resources is anchored in valuation reality rather than made after the fact.
The Problem
A CFO reviewing a portfolio of business units needs to answer two questions that internal reporting rarely surfaces cleanly: first, which units are creating value above their cost of capital and which are destroying it, and second, what does the external sector benchmark say about whether that is structural or recoverable? Most BU reviews answer the first question with precision and the second not at all — which makes it hard to distinguish units that need fixing from units that should be exited.
What It Produces
A business unit brief combining internal financial performance with external sector benchmarking — margin position, ROIC versus WACC, and peer comparison. The brief tells decision-makers whether each unit is performing in line with its strategic track. The internal and external lenses sit in the same document, against the same analytical standard.
The Standard It Applies
Sector data for margins, multiples, WACC, and beta — the external reference frame that converts an internal performance view into a value creation assessment.
One workflow.
Consistent inputs.
Three analytical outputs.
The system is fully agentic and operates end-to-end from a single email command. A run is triggered by sending a one-line instruction to the system's inbox — ticker, domain, and optional scope. Stage 1 fires automatically: it discovers which of the company's investor relations filings may be relevant and sends them for human review before anything is downloaded. After selection of which documents enter the pipeline, Stage 2 then ingests those filings alongside market data and sector benchmarks and passes the full package to a reasoning engine operating under domain-specific instructions. The completed brief is delivered by email as both a formatted document and a styled HTML output, accompanied by a summary of key metrics.
The human review step at document selection is deliberate. Investor relations pages vary widely by company; automated selection would occasionally pull the wrong documents into a high-stakes analytical output. Keeping a human in the loop at this step is quality control by design — not a limitation of the technology, but a considered judgement about where autonomous execution is appropriate and where it is not.
The architecture was designed with CFO decisions in mind — and building it end-to-end was a deliberate choice, not a necessity. A finance executive does not need to write code — but to commission analytical infrastructure well, to evaluate whether the output is good enough to act on, and to hold a team accountable for what it produces, they need to understand the architecture at the level of design. This is what I practise here: treating AI-powered analysis as an executive design problem, not a technical experiment.
The Outputs
Three decision-ready briefs — one per CFO domain. Company references anonymised.
The Financial Analyst was designed, built, and tested by Andreas Cavalca Neumann as a fully operational demonstration that agentic analysis — applied with the right frameworks and the right restraint — can remove friction from executive decisions.
Connect on LinkedIn →