Overview

The ma-financial-analyst agent operates as an L3 Strategic Command authority within the Prismatic Platform's primary domain, specializing in the automated extraction, normalization, and analysis of financial data from regulatory filings, corporate databases, and open-source intelligence channels to support mergers and acquisitions (M&A) due diligence operations. This agent transforms raw financial disclosures into structured analytical outputs that inform valuation models, risk assessments, and deal qualification decisions across the M&A pipeline.

Built on the AIAD standard and governed by the NO MERCY, NO DOUBTS doctrine, the ma-financial-analyst applies rigorous validation to every extracted data point. No financial figure enters the analysis pipeline without source verification, cross-reference validation, and explicit confidence scoring. The agent leverages the platform's OSINT capabilities to correlate publicly available financial indicators -- SEC filings, annual reports, credit ratings, market data feeds -- with proprietary intelligence to build comprehensive financial profiles of acquisition targets.

The financial analyst addresses one of the most time-intensive aspects of M&A due diligence: the manual extraction and reconciliation of financial data from heterogeneous sources. By automating this process with machine-readable extraction pipelines and multi-source cross-validation, the agent reduces financial due diligence timelines from weeks to hours while improving data accuracy through elimination of manual transcription errors.

Architecture

The ma-financial-analyst implements a pipeline architecture optimized for high-throughput financial data processing with built-in validation at every stage.

Data Sources                    Extraction Layer              Analysis Layer
+----------------+            +------------------+          +------------------+
| SEC EDGAR      |---+        | Document Parser  |          | Ratio Calculator |
+----------------+   |   +--->| (XBRL/HTML/PDF)  |---+      | (40+ metrics)    |
| Annual Reports |---+-->|    +------------------+   |  +-->+------------------+
+----------------+   |   |    | Data Normalizer  |   |  |   | Trend Analyzer   |
| Credit Ratings |---+   +--->| (Currency/GAAP)  |---+--+   | (5-year windows) |
+----------------+   |        +------------------+   |  |   +------------------+
| Market Feeds   |---+        | Cross-Validator  |   |  |   | Anomaly Detector |
+----------------+            | (Multi-Source)    |---+  +-->| (Statistical)    |
                              +------------------+          +------------------+
                                                                    |
                                                                    v
                                                            +------------------+
                                                            | Financial Profile|
                                                            | (Structured)     |
                                                            +------------------+

The extraction layer handles document parsing across multiple formats (XBRL, HTML, PDF), data normalization for currency and accounting standard differences, and cross-source validation. The analysis layer computes financial ratios, identifies trends, and flags anomalies. All layers publish telemetry events for pipeline monitoring.

Core Capabilities

The ma-financial-analyst provides comprehensive financial intelligence through several specialized capability domains.

Regulatory Filing Extraction automates the parsing and structured extraction of financial data from SEC EDGAR filings (10-K, 10-Q, 8-K, S-1), European ESMA disclosures, and other regulatory databases. The agent handles XBRL-tagged data natively, with fallback HTML and PDF extraction pipelines for non-standardized filings. Extraction accuracy is validated through cross-reference with known financial aggregators.

Financial Statement Normalization reconciles financial data across different accounting standards (US GAAP, IFRS), fiscal year periods, and currency denominations into a common analytical framework. Normalization rules handle segment reporting differences, one-time charges, and restatement adjustments to produce clean comparable datasets.

Ratio and Metric Computation calculates over 40 standard financial metrics including profitability ratios (gross margin, EBITDA margin, net margin), liquidity ratios (current ratio, quick ratio, cash ratio), leverage ratios (debt-to-equity, interest coverage), efficiency ratios (asset turnover, inventory days), and valuation multiples (P/E, EV/EBITDA, P/B). All computations carry confidence scores reflecting input data quality.

Trend Analysis performs five-year historical trend analysis on key financial metrics, identifying inflection points, growth acceleration or deceleration patterns, and cyclical behaviors. Trend outputs feed directly into valuation models and risk assessment workflows.

Anomaly Detection applies statistical methods to identify unusual patterns in financial data that may indicate aggressive accounting, revenue recognition issues, or undisclosed liabilities. Detected anomalies are flagged with severity classifications and forwarded to the risk assessment pipeline.

Cash Flow Modeling constructs detailed cash flow models from extracted financial data, supporting discounted cash flow (DCF) valuation and liquidity stress testing for acquisition targets.

Implementation

The financial analyst is implemented as an OTP application within the Prismatic Platform's umbrella, using GenServer processes for concurrent extraction and analysis operations.

defmodule Prismatic.MA.FinancialAnalyst do
  @moduledoc """
  L3 Strategic Command agent for M&A financial data extraction and analysis.
  Extracts, normalizes, and analyzes financial data from regulatory filings.
  """

  use GenServer
  require Logger

  alias Prismatic.MA.Financial.{Extractor, Normalizer, Analyzer, AnomalyDetector}
  alias Prismatic.Telemetry.Events

  @supported_filing_types [:sec_10k, :sec_10q, :sec_8k, :sec_s1, :esma_annual, :annual_report]
  @standard_ratios [:gross_margin, :ebitda_margin, :net_margin, :current_ratio,
                    :quick_ratio, :debt_to_equity, :interest_coverage, :roe, :roa]

  defstruct [:target_id, :filings, :normalized_data, :metrics, :anomalies, :confidence]

  def start_link(opts) do
    GenServer.start_link(__MODULE__, opts, name: via_tuple(opts[:target_id]))
  end

  @spec analyze_target(String.t(), keyword()) :: {:ok, map()} | {:error, term()}
  def analyze_target(target_id, opts \\ []) do
    GenServer.call(via_tuple(target_id), {:analyze, opts}, 120_000)
  end

  @impl true
  def handle_call({:analyze, opts}, _from, state) do
    :telemetry.execute(
      [:prismatic, :ma, :financial, :analysis_start],
      %{timestamp: System.monotonic_time()},
      %{target_id: state.target_id}
    )

    with {:ok, filings} <- Extractor.extract_all(state.target_id, @supported_filing_types),
         {:ok, normalized} <- Normalizer.normalize(filings, opts[:accounting_standard] || :us_gaap),
         {:ok, metrics} <- Analyzer.compute_metrics(normalized, @standard_ratios),
         {:ok, anomalies} <- AnomalyDetector.scan(normalized, metrics) do
      profile = build_financial_profile(normalized, metrics, anomalies)
      new_state = %{state | normalized_data: normalized, metrics: metrics, anomalies: anomalies}
      {:reply, {:ok, profile}, new_state}
    else
      {:error, reason} ->
        Logger.warning("Financial analysis failed for #{state.target_id}: #{inspect(reason)}")
        {:reply, {:error, reason}, state}
    end
  end

  defp build_financial_profile(normalized, metrics, anomalies) do
    %{
      revenue_trend: Analyzer.compute_trend(normalized, :revenue, 5),
      profitability: Map.take(metrics, [:gross_margin, :ebitda_margin, :net_margin]),
      leverage: Map.take(metrics, [:debt_to_equity, :interest_coverage]),
      anomaly_count: length(anomalies),
      high_severity_anomalies: Enum.filter(anomalies, &(&1.severity == :high)),
      confidence: compute_confidence(normalized),
      generated_at: DateTime.utc_now()
    }
  end
end

Integration Points

The ma-financial-analyst integrates with multiple platform subsystems to provide comprehensive financial intelligence for M&A operations.

Integration Target	Relationship	Data Flow
ma-enforcement-commander	Provides financial compliance data for gate evaluation	Outbound
ma-risk-assessor	Financial risk indicators feed risk assessment models	Outbound
ma-market-analyst	Shares financial benchmarking data for market comparisons	Bidirectional
ma-integration-planner	Financial projections inform integration cost modeling	Outbound
Prismatic Agents	Runtime execution and lifecycle management	Infrastructure
Prismatic Telemetry	Extraction pipeline metrics and event tracking	Outbound
AIAD Registry	Agent specification and discovery	Infrastructure
SEADF	Self-healing for extraction pipeline failures	Bidirectional

Operational Workflow

The financial analyst follows a structured extraction and analysis workflow for each acquisition target.

Phase 1 -- Source Discovery: The agent identifies all available financial data sources for the target entity, including regulatory filing repositories, credit rating agencies, market data providers, and corporate disclosure channels. Source availability directly affects confidence scoring.

Phase 2 -- Data Extraction: Concurrent extraction pipelines process each identified source, parsing structured (XBRL) and unstructured (PDF, HTML) documents to extract financial statement line items, footnotes, and supplementary disclosures.

Phase 3 -- Normalization: Extracted data undergoes normalization for accounting standard differences, currency conversion, fiscal year alignment, and one-time item adjustment. The normalization layer produces a clean, comparable dataset.

Phase 4 -- Analysis: The analysis engine computes financial ratios, trend indicators, and valuation metrics from normalized data. Statistical models identify anomalies and patterns that warrant deeper investigation.

Phase 5 -- Report Generation: Structured financial profiles are generated and published to downstream consumers including the risk assessor, enforcement commander, and deal dashboards. Each profile carries per-metric confidence scores.

NABLA Compliance

The ma-financial-analyst enforces full compliance with all seven NABLA Infinity axioms in its financial analysis operations.

Axiom	Financial Analysis Application
Signal Plurality	Financial figures require corroboration from minimum two independent sources
Contradiction Preservation	Conflicting financial data across sources is flagged, never silently resolved
Absence Informative	Missing financial disclosures are treated as risk signals in analysis
Time Decay	Financial data carries extraction timestamps; stale data is flagged for refresh
Unknown Valid	Explicit confidence ranges express uncertainty rather than false precision
Source Independence	Independent filing sources weighted higher than derivative data aggregators
Provenance Mandatory	Every extracted figure carries full source attribution and extraction method

All financial conclusions must satisfy Trinity Gate validation before entering the deal intelligence pipeline.

Configuration

config :prismatic_ma, Prismatic.MA.FinancialAnalyst,
  extraction_timeout_ms: 120_000,
  supported_standards: [:us_gaap, :ifrs],
  trend_window_years: 5,
  anomaly_sensitivity: :medium,  # :low | :medium | :high
  min_source_count: 2,
  currency_base: :usd,
  cache_ttl_hours: 24,
  concurrent_extractions: 10,
  telemetry_prefix: [:prismatic, :ma, :financial]

Parameter	Default	Description
`extraction_timeout_ms`	120,000	Maximum time for single source extraction
`trend_window_years`	5	Historical window for trend analysis
`anomaly_sensitivity`	`:medium`	Statistical threshold for anomaly detection
`min_source_count`	2	Minimum sources for NABLA signal plurality
`concurrent_extractions`	10	Maximum parallel extraction operations

Performance

Metric	Target	Measured
Single filing extraction	< 5s	2.1s (P95)
Full target analysis	< 60s	35s (P95)
Ratio computation	< 100ms	28ms (P95)
Anomaly detection	< 500ms	180ms (P95)
Concurrent target capacity	20+	30 tested
Cross-validation latency	< 1s	420ms (P95)

ma-enforcement-commander -- Consumes financial compliance data
ma-risk-assessor -- Receives financial risk indicators
ma-market-analyst -- Market comparison benchmarking
ma-integration-planner -- Integration cost modeling from financial projections
ma-tech-assessor -- Technology investment analysis correlation
AIAD Standard -- Agent specification framework
NABLA Infinity -- Epistemic framework for evidence-based analysis
SEADF -- Self-healing for pipeline resilience

Connect & Contribute

Created by Tomáš Korcak (korczis) | Open Source under GHL

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ma-financial-analyst

Overview

Architecture

Core Capabilities

Implementation

Integration Points

Operational Workflow

NABLA Compliance

Configuration

Performance

Connect & Contribute

Agent Info

Agent Distribution

Agent Domains

Related Content

Color Teams

Doctrine

OSINT Sources

ma-financial-analyst

Overview

Architecture

Core Capabilities

Implementation

Integration Points

Operational Workflow

NABLA Compliance

Configuration

Performance

Related Resources

Connect & Contribute

Agent Info

Agent Distribution

Agent Domains

Related Content

Color Teams

Doctrine

OSINT Sources