Old National Bancorp: interest expense

What this measure means

Borrowing costs recognized as interest expense. This is distinct from cash interest paid and may not include every capitalized borrowing cost.

Exact concept: us-gaap:InterestExpense. Each value covers an annual-duration reporting interval, shown with both start and end dates. Different units remain separate; no currency conversion or interpolation is applied.

Coverage of this history

Selected reporting periods run from 2008-01-01 to 2023-12-31. The SEC response was captured on 2026-09-19.

This selected history ends more than two years before capture. Do not treat its final value as a current balance or current annual result. More recent filings may use another accounting tag; inspect the filings before drawing conclusions about the company.

Selected filing history

Related financial histories

• Old National Bancorp: total assets
• Old National Bancorp: total liabilities
• Old National Bancorp: stockholders equity
• Old National Bancorp: cash and cash equivalents
• Old National Bancorp: net income or loss
• Old National Bancorp: operating cash flow
• Old National Bancorp: capital expenditure payments
• Old National Bancorp: contract revenue excluding tax
• Old National Bancorp: financing cash flow
• Old National Bancorp: investing cash flow
• Old National Bancorp: retained earnings or deficit
• Old National Bancorp: basic weighted-average shares
• Old National Bancorp: diluted weighted-average shares
• Old National Bancorp: basic earnings per share
• Old National Bancorp: diluted earnings per share
• Old National Bancorp: income tax expense or benefit
• Old National Bancorp: net property, plant and equipment
• Old National Bancorp: share-based compensation expense
• Old National Bancorp: goodwill carrying amount
• Old National Bancorp: net finite-lived intangible assets
• Old National Bancorp: common-stock repurchase payments

Inspect the source

Entity

Old National Bancorp / CIK 0000707179

Captured

2026-09-19T14:58:10.941Z

SEC response SHA-256

ef32fff77b0e8d610629bb964e9574d6019b6684425c6b6d1ec7e328788fecae

Current SEC company facts · Download the original response snapshot (gzip) · Download the selected JSON

Latest-filed annual-report facts per unit and reporting period at capture time. Duration facts cover 300 to 400 days. This selection can include restatements and is not a point-in-time backtest dataset. Missing concepts are omitted, never zero-filled. Values retain original units and are not currency converted. Extended concepts require compatible unit shapes and at least three reporting ends with changing values within one unit. Constant or incompatible added histories are omitted.

Public company accounting reference, not market prices, returns, an investment recommendation, or ALPHAC performance. Validate a separately constructed return series with the validation API; accounting values are not returns.

Use this in research

A financial period ends before its results become public. Use the filing date as a minimum availability boundary, inspect amendments, and retain the original filing vintage when testing historical signals. This latest-filed selection can contain information unavailable at the time.

These pages do not supply prices, total-return histories, corporate-action adjustments or a tradable universe. Build those inputs separately before evaluating a strategy. A profitable backtest can still reflect selection bias or costs that were left out.

Research methodology · Execution and cost assumptions · Check backtest overfitting

Build with the open-source tools

Use these accounting records as inspectable inputs. When you have constructed a return series, the validation tools can help test its statistical evidence and preserve the result with its limitations.

• Get an API key and run your first validation
• Connect the MCP server to your coding assistant
• Inspect the ALPHAC engine on GitHub
• Read the MCP server source and integration examples

import json
from urllib.request import urlopen

with urlopen("https://canlicapital.com/company-data/0000707179.json") as response:
    record = json.load(response)
print(record["fetched_at"])
print(record["policy"])
for concept in record["concepts"]:
    print(concept["tag"], next(iter(concept["observations"])))