ELI Lilly and Company: net finite-lived intangible assets
ELI Lilly and Company net finite-lived intangible assets: $5.33 billion at 2022-12-31, down 7.5% on the year. 11 values since 2012. In original units.
All ELI Lilly and Company financial histories
At a glance
ELI Lilly and Company reported net finite-lived intangible assets of $5.33 billion at 2022-12-31, down 7.5% from $5.77 billion a year earlier. From 2012 to 2022 it grew at a compound 5.3% a year, from $3.19 billion to $5.33 billion. Across the last five reported years it ranged from $1.07 billion (2018-12-31) to $6.35 billion (2020-12-31). That was 10.8% of total assets ($49.5 billion) at the same date.
Computed from the values in the table below, in USD; each links to the filing it came from.
What this measure means
Finite-lived intangible assets after amortization. This excludes goodwill and should not be combined with indefinite-lived intangible assets without checking scope.
Exact concept: us-gaap:FiniteLivedIntangibleAssetsNet. Each value is a balance at the reporting date, not a flow earned over a year. Different units remain separate; no currency conversion or interpolation is applied.
Coverage of this history
Selected reporting periods run from 2012-12-31 to 2022-12-31. 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
| Period start | Period end | Value | Unit | Filed | Source filing |
|---|---|---|---|---|---|
| - | 2022-12-31 | 5,334,800,000 | USD | 2023-02-22 | 10-K · 0000059478-23-000082 SEC |
| - | 2021-12-31 | 5,766,900,000 | USD | 2023-02-22 | 10-K · 0000059478-23-000082 SEC |
| - | 2020-12-31 | 6,349,000,000 | USD | 2022-02-23 | 10-K · 0000059478-22-000068 SEC |
| - | 2019-12-31 | 1,948,000,000 | USD | 2021-02-17 | 10-K · 0000059478-21-000083 SEC |
| - | 2018-12-31 | 1,068,000,000 | USD | 2020-02-19 | 10-K · 0000059478-20-000057 SEC |
| - | 2017-12-31 | 3,932,000,000 | USD | 2019-02-19 | 10-K · 0000059478-19-000082 SEC |
| - | 2016-12-31 | 4,177,700,000 | USD | 2018-02-20 | 10-K · 0000059478-18-000089 SEC |
| - | 2015-12-31 | 4,857,200,000 | USD | 2017-02-21 | 10-K · 0000059478-17-000098 SEC |
| - | 2014-12-31 | 2,872,800,000 | USD | 2016-02-19 | 10-K · 0000059478-16-000321 SEC |
| - | 2013-12-31 | 2,780,700,000 | USD | 2015-02-19 | 10-K · 0000059478-15-000100 SEC |
| - | 2012-12-31 | 3,186,400,000 | USD | 2014-02-19 | 10-K · 0000059478-14-000078 SEC |
Related ELI LILLY AND COMPANY histories
Inspect the source
- Entity
- ELI LILLY AND COMPANY / CIK 0000059478
- Captured
- SEC response SHA-256
3fe29099e6efaef9acac95711c271de1a644602939ea18487e29708310985942
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.
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Read the published dataset with Python
import json
from urllib.request import urlopen
with urlopen("https://canlicapital.com/company-data/0000059478.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"])))