FIRST MERCHANTS CORP: 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 2009-01-01 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

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

Inspect the source

Entity

FIRST MERCHANTS CORP / CIK 0000712534

Captured

2026-09-19T14:58:36.211Z

SEC response SHA-256

36f09e232f503ed3ff51281e04a234ebe387fd97d7aff4d1a435769f6707d2ed

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/0000712534.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"])))