Compare technology and communications spending efficiency for JPMorgan Chase and Bank of America for FY-2024

failed demo-tech-comms-efficiency-jpm-bac-fy2024 21.2s 5 LLM calls 153.5k in / 2.5k out ~$0.166
JobRequest (constructed by intake)

Question: Compare technology and communications spending efficiency for JPMorgan Chase and Bank of America for FY-2024
analysisId: demo-tech-comms-efficiency-jpm-bac-fy2024
Period: FY-2024
Sources: sec-edgar
Entities

JPMorgan Chase & Co. (JPM, JPMorgan Chase)
Bank of America Corporation (BAC, Bank of America)
Target metrics (source concepts)

technology_communications_equipment_expense USD
Total expenses for technology, communications, and equipment as reported in the noninterest expense section of the income statement in annual filings.
total_noninterest_expense USD
Total noninterest expenses as reported in the income statement in annual filings, representing all operating costs excluding interest expense.
Derived metrics (computed)

technology_communications_efficiency_ratio percent
Technology and communications spending as a percentage of total noninterest expense, calculated as technology_communications_equipment_expense divided by total_noninterest_expense.
methodology: tech_opex_efficiency_banking
Pipeline

baseline source-extraction ok
Std 2 validate-input validated request: 2 entity(ies), 2 metric(s), period=FY-2024, sources=[sec-edgar]
Std 5 retrieve delegating retrieval to LLM (claude-haiku-4-5) with 10 SEC tool(s) available: [sec_edgar_companies, sec_financials, sec_submissions, sec_filing_document, sec_filing_index, sec_filing_sections, sec_full_text_search, sec_company_concept, sec_xbrl_frames, sec_insider_form4]
Std 3 parse-and-extract starting tool-use extraction over 2 entity(ies) × 2 metric(s)
Std 5 tool-call sec_edgar_companies(searchTerms="JPMorgan Chase & Co., JPM, Bank of America Corporation, BAC") → 2 match(es): JPM, BAC
Std 5 tool-call sec_financials(cik="0000019617") → JPMORGAN CHASE & CO — 0 concept(s) across []
Std 5 tool-call sec_financials(cik="0000070858") → BANK OF AMERICA CORP /DE/ — 0 concept(s) across []
Std 5 tool-call sec_company_concept(cik="0000019617", taxonomy="us-gaap", tag="NoninterestExpense", unit="USD") → NoninterestExpense (Noninterest Expense) — 232 row(s) across units [USD]
Std 5 tool-call sec_company_concept(cik="0000019617", taxonomy="us-gaap", tag="CommunicationsAndInformationTechnology", unit="USD") → CommunicationsAndInformationTechnology (Communications and Information Technology) — 178 row(s) across units [USD]
Std 5 tool-call sec_company_concept(cik="0000070858", taxonomy="us-gaap", tag="NoninterestExpense", unit="USD") → NoninterestExpense (Noninterest Expense) — 233 row(s) across units [USD]
Std 5 tool-call sec_company_concept(cik="0000070858", taxonomy="us-gaap", tag="CommunicationsAndInformationTechnology", unit="USD") → CommunicationsAndInformationTechnology (Communications and Information Technology) — 93 row(s) across units [USD]
Std 4 structure structured 4 value(s) with provenance from 7 tool call(s)
Std 7 validate-output validation: coverage=100% blocking=0 confidence=high
Std 11 handoff handoff → baseline.normalization (validation=passed confidence=high)
baseline normalization ok
Std 2 validate-input received 4 value(s); 1 comparability note(s)
Std 8 resolve-duplicates dedup complete; 0 contradiction(s)
Std 10 validate-output 2 new rule(s) drained for write-back
Std 11 handoff handoff → baseline.resolution (validation=passed confidence=high)
baseline resolution ok
Std 2 review-issue reviewing 4 record(s) + 0 unresolved issue(s)
Std 3 resolve-conflict 4 record(s) packaged after conflict resolution
Std 9 attempt-remediation triaged 0 issue(s); 0 escalation(s) raised
Std 10 package-outcome 0 learned rule(s) for write-back
Std 7 revalidate revalidated; agent-level confidence high (0.99)
Std 11 package-outcome baseline pillar complete; 4 resolved, 0 escalated
intelligence analytical-table fail
Std 2 receive-pillar1-output received 4 Pillar 1 record(s); upstream lineage refs=4
Std 5 determine-table-structure delegating structuring to LLM (claude-haiku-4-5) with 2 methodology tool(s) available: [find_methodologies, get_methodology]
intelligence performance-metrics idle
(no trace; never reached)
intelligence comparisons-synthesis idle
(no trace; never reached)
intelligence insight-synthesis idle
(no trace; never reached)
Run failed

Agent: intelligence.analytical-table
Category: analytical-table-incomplete
Reason: 429 {"type":"error","error":{"type":"rate_limit_error","message":"This request would exceed your organization's rate limit of 50,000 input tokens per minute (org: 38002006-24f1-4b7e-b005-6c6d6f91d10c, model: claude-haiku-4-5-20251001). For details, refer to: https://docs.claude.com/en/api/rate-limits. You can see the response headers for current usage. Reduce the prompt length or the maximum tokens requested, or try again later. View your current limits at https://console.anthropic.com/settings/limits. To raise this limit, purchase credits to advance to the next usage tier at https://console.anthropic.com/settings/billing."},"request_id":"req_011CbNcM8SBL6zotX95JzC61"}
Anthropic usage (Haiku 4.5 list pricing)

Agent	Model	Calls	In tok	Out tok	~Cost
`intake`	claude-haiku-4-5	1	990	380	$0.00289
`baseline.source-extraction`	claude-haiku-4-5	4	152.5k	2.1k	$0.163
TOTAL		5	153.5k	2.5k	$0.166
Full audit JSON

(56,005 chars)
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    "lineage": {
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    "context": {
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      },
      "input": {
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  "escalations": [
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        "agent": "baseline.source-extraction",
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        "payload": {
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            }
          ]
        },
        "metadata": {
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          "toolCalls": [
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              "ok": true,
              "input": {
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              },
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              "at": "2026-05-25T03:53:16.189Z"
            },
            {
              "toolName": "sec_financials",
              "ok": true,
              "input": {
                "cik": "0000019617"
              },
              "resultSummary": "JPMORGAN CHASE & CO — 0 concept(s) across []",
              "at": "2026-05-25T03:53:19.883Z"
            },
            {
              "toolName": "sec_financials",
              "ok": true,
              "input": {
                "cik": "0000070858"
              },
              "resultSummary": "BANK OF AMERICA CORP /DE/ — 0 concept(s) across []",
              "at": "2026-05-25T03:53:20.356Z"
            },
            {
              "toolName": "sec_company_concept",
              "ok": true,
              "input": {
                "cik": "0000019617",
                "taxonomy": "us-gaap",
                "tag": "NoninterestExpense",
                "unit": "USD"
              },
              "resultSummary": "NoninterestExpense (Noninterest Expense) — 232 row(s) across units [USD]",
              "at": "2026-05-25T03:53:24.572Z"
            },
            {
              "toolName": "sec_company_concept",
              "ok": true,
              "input": {
                "cik": "0000019617",
                "taxonomy": "us-gaap",
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                "unit": "USD"
              },
              "resultSummary": "CommunicationsAndInformationTechnology (Communications and Information Technology) — 178 row(s) across units [USD]",
              "at": "2026-05-25T03:53:24.766Z"
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    },
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      "at": "2026-05-25T03:53:19.883Z"
    },
    {
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      "at": "2026-05-25T03:53:25.160Z"
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      "agent": "baseline.source-extraction",
      "standard": 4,
      "step": "structure",
      "detail": "structured 4 value(s) with provenance from 7 tool call(s)",
      "at": "2026-05-25T03:53:33.604Z"
    },
    {
      "agent": "baseline.source-extraction",
      "standard": 7,
      "step": "validate-output",
      "detail": "validation: coverage=100% blocking=0 confidence=high",
      "at": "2026-05-25T03:53:33.604Z"
    },
    {
      "agent": "baseline.source-extraction",
      "standard": 11,
      "step": "handoff",
      "detail": "handoff → baseline.normalization (validation=passed confidence=high)",
      "at": "2026-05-25T03:53:33.604Z"
    },
    {
      "agent": "baseline.normalization",
      "standard": 2,
      "step": "validate-input",
      "detail": "received 4 value(s); 1 comparability note(s)",
      "at": "2026-05-25T03:53:33.605Z"
    },
    {
      "agent": "baseline.normalization",
      "standard": 8,
      "step": "resolve-duplicates",
      "detail": "dedup complete; 0 contradiction(s)",
      "at": "2026-05-25T03:53:33.607Z"
    },
    {
      "agent": "baseline.normalization",
      "standard": 10,
      "step": "validate-output",
      "detail": "2 new rule(s) drained for write-back",
      "at": "2026-05-25T03:53:33.608Z"
    },
    {
      "agent": "baseline.normalization",
      "standard": 11,
      "step": "handoff",
      "detail": "handoff → baseline.resolution (validation=passed confidence=high)",
      "at": "2026-05-25T03:53:33.608Z"
    },
    {
      "agent": "baseline.resolution",
      "standard": 2,
      "step": "review-issue",
      "detail": "reviewing 4 record(s) + 0 unresolved issue(s)",
      "at": "2026-05-25T03:53:33.609Z"
    },
    {
      "agent": "baseline.resolution",
      "standard": 3,
      "step": "resolve-conflict",
      "detail": "4 record(s) packaged after conflict resolution",
      "at": "2026-05-25T03:53:33.610Z"
    },
    {
      "agent": "baseline.resolution",
      "standard": 9,
      "step": "attempt-remediation",
      "detail": "triaged 0 issue(s); 0 escalation(s) raised",
      "at": "2026-05-25T03:53:33.610Z"
    },
    {
      "agent": "baseline.resolution",
      "standard": 10,
      "step": "package-outcome",
      "detail": "0 learned rule(s) for write-back",
      "at": "2026-05-25T03:53:33.610Z"
    },
    {
      "agent": "baseline.resolution",
      "standard": 7,
      "step": "revalidate",
      "detail": "revalidated; agent-level confidence high (0.99)",
      "at": "2026-05-25T03:53:33.610Z"
    },
    {
      "agent": "baseline.resolution",
      "standard": 11,
      "step": "package-outcome",
      "detail": "baseline pillar complete; 4 resolved, 0 escalated",
      "at": "2026-05-25T03:53:33.610Z"
    },
    {
      "agent": "intelligence.analytical-table",
      "standard": 2,
      "step": "receive-pillar1-output",
      "detail": "received 4 Pillar 1 record(s); upstream lineage refs=4",
      "at": "2026-05-25T03:53:33.610Z"
    },
    {
      "agent": "intelligence.analytical-table",
      "standard": 5,
      "step": "determine-table-structure",
      "detail": "delegating structuring to LLM (claude-haiku-4-5) with 2 methodology tool(s) available: [find_methodologies, get_methodology]",
      "at": "2026-05-25T03:53:33.611Z"
    }
  ],
  "standards": [
    {
      "n": 1,
      "name": "Objective",
      "gist": "Single clear responsibility with explicit boundaries."
    },
    {
      "n": 2,
      "name": "Inputs",
      "gist": "Structured, machine-readable; lineage + confidence persist."
    },
    {
      "n": 3,
      "name": "Decision logic",
      "gist": "Explicit, deterministic where possible, every decision recorded."
    },
    {
      "n": 4,
      "name": "Rules & constraints",
      "gist": "Preserve raw, lineage, audit; no fabrication; approved tools only."
    },
    {
      "n": 5,
      "name": "Methods & tools",
      "gist": "Capability-based; approved + connected; lineage-preserving. The system prompt for each LLM invocation carries the discipline the current operation actually engages — the 12 standards remain the framework's invariants and are always honored by agent behavior, but the full standards recital is reserved for steps that engage them."
    },
    {
      "n": 6,
      "name": "Processing",
      "gist": "Modular, repeatable, replayable; numbered runbook. Each runbook step is executed at the appropriate cost level — when a step's input has been deterministically established by upstream agents, schema, or unambiguous data, the agent records the inherited determination and proceeds without LLM call. LLM reasoning is reserved for genuine interpretation, judgment, or resolution of ambiguity."
    },
    {
      "n": 7,
      "name": "Validation & confidence",
      "gist": "Every output carries validation status + confidence tier. Confidence can be inherited from upstream when the upstream agent's confidence is high and the current agent's processing introduces no new uncertainty. Re-validation via LLM is reserved for cases where the agent introduces uncertainty or where the runbook explicitly requires independent verification."
    },
    {
      "n": 8,
      "name": "Conditional triggers",
      "gist": "Explicit exception categories; traceable, context-preserving."
    },
    {
      "n": 9,
      "name": "HITL escalation",
      "gist": "Defined thresholds; escalations carry full context."
    },
    {
      "n": 10,
      "name": "Repository write-back",
      "gist": "Agents declare; orchestrator persists."
    },
    {
      "n": 11,
      "name": "Handoff",
      "gist": "Standardized envelope; downstream never reconstructs context."
    },
    {
      "n": 12,
      "name": "Failure handling",
      "gist": "Fail safely; bounded retries + recursion; structured FailureObject."
    }
  ],
  "pipeline": [
    {
      "kind": "agent",
      "pillar": "baseline",
      "agent": "source-extraction"
    },
    {
      "kind": "agent",
      "pillar": "baseline",
      "agent": "normalization"
    },
    {
      "kind": "agent",
      "pillar": "baseline",
      "agent": "resolution"
    },
    {
      "kind": "agent",
      "pillar": "intelligence",
      "agent": "analytical-table"
    },
    {
      "kind": "agent",
      "pillar": "intelligence",
      "agent": "performance-metrics"
    },
    {
      "kind": "agent",
      "pillar": "intelligence",
      "agent": "comparisons-synthesis"
    },
    {
      "kind": "agent",
      "pillar": "intelligence",
      "agent": "insight-synthesis"
    }
  ],
  "jobRequest": {
    "analysisId": "demo-tech-comms-efficiency-jpm-bac-fy2024",
    "question": "Compare technology and communications spending efficiency for JPMorgan Chase and Bank of America for FY-2024",
    "entities": [
      {
        "id": "JPMorgan Chase & Co.",
        "aliases": [
          "JPM",
          "JPMorgan Chase"
        ]
      },
      {
        "id": "Bank of America Corporation",
        "aliases": [
          "BAC",
          "Bank of America"
        ]
      }
    ],
    "targetMetrics": [
      {
        "key": "technology_communications_equipment_expense",
        "definition": "Total expenses for technology, communications, and equipment as reported in the noninterest expense section of the income statement in annual filings.",
        "unit": "USD"
      },
      {
        "key": "total_noninterest_expense",
        "definition": "Total noninterest expenses as reported in the income statement in annual filings, representing all operating costs excluding interest expense.",
        "unit": "USD"
      }
    ],
    "derivedMetrics": [
      {
        "key": "technology_communications_efficiency_ratio",
        "definition": "Technology and communications spending as a percentage of total noninterest expense, calculated as technology_communications_equipment_expense divided by total_noninterest_expense.",
        "unit": "percent",
        "methodology": "tech_opex_efficiency_banking"
      }
    ],
    "sources": [
      "sec-edgar"
    ],
    "period": "FY-2024"
  },
  "elapsedMs": 21239,
  "usage": {
    "records": [
      {
        "agent": "intake",
        "model": "claude-haiku-4-5",
        "inputTokens": 990,
        "outputTokens": 380,
        "at": "2026-05-25T03:53:14.175Z"
      },
      {
        "agent": "baseline.source-extraction",
        "model": "claude-haiku-4-5",
        "inputTokens": 5321,
        "outputTokens": 121,
        "at": "2026-05-25T03:53:15.950Z"
      },
      {
        "agent": "baseline.source-extraction",
        "model": "claude-haiku-4-5",
        "inputTokens": 5507,
        "outputTokens": 283,
        "at": "2026-05-25T03:53:19.320Z"
      },
      {
        "agent": "baseline.source-extraction",
        "model": "claude-haiku-4-5",
        "inputTokens": 45321,
        "outputTokens": 510,
        "at": "2026-05-25T03:53:24.419Z"
      },
      {
        "agent": "baseline.source-extraction",
        "model": "claude-haiku-4-5",
        "inputTokens": 96342,
        "outputTokens": 1192,
        "at": "2026-05-25T03:53:33.603Z"
      }
    ],
    "byAgent": [
      {
        "agent": "intake",
        "model": "claude-haiku-4-5",
        "calls": 1,
        "inputTokens": 990,
        "outputTokens": 380
      },
      {
        "agent": "baseline.source-extraction",
        "model": "claude-haiku-4-5",
        "calls": 4,
        "inputTokens": 152491,
        "outputTokens": 2106
      }
    ],
    "totals": {
      "calls": 5,
      "inputTokens": 153481,
      "outputTokens": 2486
    }
  }
}