Bank Lending Standards

Senior Loan Officer Opinion Survey — Federal Reserve

The Fed asks banks if they’re tightening credit. Banks answer. We chart it. Riveting.

Data source: Federal Reserve Senior Loan Officer Opinion Survey (SLOOS) — Table 1 (C&I loans) and Table 2 (Consumer loans). Quarterly survey. Net percentage = % tightening minus % easing. See Data Sources for methodology.

Four times a year, the Federal Reserve asks senior loan officers at major banks whether they’ve been tightening or loosening lending standards. The result is reported as a “net percentage” — banks tightening minus banks easing. Positive means more banks are tightening than easing. Historically, sustained readings above +20% have preceded things worth paying attention to.

This is survey data. It measures intent and perception, not actual loan volumes. Keep that in mind before drawing any strong conclusions. Or don’t — your call.

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Net Tightening by Loan Type

Net percentage of banks reporting tighter lending standards. A value above zero means more banks are tightening than easing. The horizontal line at zero is there so you know where zero is.

import { DuckDBClient } from "npm:@duckdb/duckdb-wasm"
db_sloos = DuckDBClient.of({})
r2Base = params["r2-base-url"]

sloosData = {
  if (!r2Base || r2Base === "") return null
  try {
    const result = await db_sloos.query(`
      SELECT
        survey_date,
        question_label,
        loan_type,
        net_pct_tightening
      FROM read_parquet('${r2Base}/sloos/curated/source=fed_sloos_table_1/*.parquet')
      WHERE loan_type IN ('C&I - Large', 'C&I - Small', 'Consumer - Auto', 'Consumer - Credit Card')
        AND survey_date IS NOT NULL
      ORDER BY survey_date, loan_type
    `)
    return result
  } catch(e) {
    return { error: e.message }
  }
}

{
  if (!r2Base || r2Base === "") {
    const el = document.createElement("div")
    el.className = "chart-error"
    el.innerHTML = `<span>⚠</span><span>R2 data source not configured.</span>`
    return el
  }

  if (!sloosData || sloosData.error) {
    const el = document.createElement("div")
    el.className = "chart-error"
    el.innerHTML = `<span>⚠</span><span>Data unavailable — ${sloosData?.error ?? "unknown error"}.</span>`
    return el
  }

  const maxDate = d3.max(sloosData, d => new Date(d.survey_date))
  const asOfStr = maxDate
    ? maxDate.toLocaleDateString("en-US", { month: "short", year: "numeric" })
    : "unknown"

  // Color palette — 4 muted series colors
  const loanColors = {
    "C&I - Large":            "#4A6FA5",
    "C&I - Small":            "#7BA3C8",
    "Consumer - Auto":        "#C8A058",
    "Consumer - Credit Card": "#8A7A5A"
  }

  const loanTypes = [...new Set(sloosData.map(d => d.loan_type))]

  return Plot.plot({
    title: "Net % of Banks Tightening Lending Standards",
    subtitle: "Positive = more banks tightening than easing",
    width: 800,
    height: 380,
    marginLeft: 55,
    marginBottom: 50,
    color: {
      domain: loanTypes,
      range: loanTypes.map(t => loanColors[t] ?? "#8A8A8A"),
      legend: true
    },
    x: {
      type: "time",
      label: null,
      tickFormat: d => d.toLocaleDateString("en-US", { month: "short", year: "2-digit" })
    },
    y: {
      label: "Net % Tightening",
      tickFormat: d => `${d > 0 ? "+" : ""}${d}%`,
      grid: true,
      gridColor: "var(--border-color, #D8D3C8)"
    },
    marks: [
      Plot.ruleY([0], { stroke: "#8A8A8A", strokeWidth: 1.5, strokeDasharray: "4,3" }),
      Plot.line(sloosData, {
        x: d => new Date(d.survey_date),
        y: "net_pct_tightening",
        stroke: "loan_type",
        strokeWidth: 2,
        curve: "monotone-x"
      })
    ],
    caption: `Source: Federal Reserve SLOOS Table 1 | Units: net % | Survey-based | As of ${asOfStr}`
  })
}

---

What Tightening Means in Practice

Net tightening is reported as: (% tightening standards) − (% easing standards).

• +40% or above: Significant tightening — happened during the GFC (2008–2009) and the early COVID period (2020).
• +20% to +40%: Elevated tightening — historically associated with late-cycle credit slowdowns.
• Near zero: Roughly neutral — banks aren’t materially changing standards.
• Negative: Net easing — more banks loosening than tightening. Less common.

This is a diffusion index, not a volume measure. It doesn’t tell you how much standards tightened — only how many banks said they did.

For full source documentation, see Data Sources →