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CSV Singapore Department of Statistics

Companies In Compulsory Liquidation, Monthly

Description

Monthly counts of companies in compulsory liquidation in Singapore from January 2016 through April 2026, sourced from the Insolvency Office and published via SingStat. Credit-risk and business-cycle analysts track formal company wind-ups as a stress indicator. Adapted from SingStat TableBuilder TS/M891451.

Official description

Source: INSOLVENCY OFFICE Data Last Updated: 25/05/2026 Update Frequency: Monthly Adapted from: https://tablebuilder.singstat.gov.sg/table/TS/M891451

Download CSV View on data.gov.sg
Last updated
Coverage
2016-01-01 – 2026-04-01
Rows
2
Columns
125

Chart

Values are summed where multiple rows share the same category.

Data

Data Series 2026 Apr 2026 Mar 2026 Feb 2026 Jan 2025 Dec 2025 Nov 2025 Oct 2025 Sep 2025 Aug 2025 Jul 2025 Jun 2025 May 2025 Apr 2025 Mar 2025 Feb 2025 Jan 2024 Dec 2024 Nov 2024 Oct 2024 Sep 2024 Aug 2024 Jul 2024 Jun 2024 May 2024 Apr 2024 Mar 2024 Feb 2024 Jan 2023 Dec 2023 Nov 2023 Oct 2023 Sep 2023 Aug 2023 Jul 2023 Jun 2023 May 2023 Apr 2023 Mar 2023 Feb 2023 Jan 2022 Dec 2022 Nov 2022 Oct 2022 Sep 2022 Aug 2022 Jul 2022 Jun 2022 May 2022 Apr 2022 Mar 2022 Feb 2022 Jan 2021 Dec 2021 Nov 2021 Oct 2021 Sep 2021 Aug 2021 Jul 2021 Jun 2021 May 2021 Apr 2021 Mar 2021 Feb 2021 Jan 2020 Dec 2020 Nov 2020 Oct 2020 Sep 2020 Aug 2020 Jul 2020 Jun 2020 May 2020 Apr 2020 Mar 2020 Feb 2020 Jan 2019 Dec 2019 Nov 2019 Oct 2019 Sep 2019 Aug 2019 Jul 2019 Jun 2019 May 2019 Apr 2019 Mar 2019 Feb 2019 Jan 2018 Dec 2018 Nov 2018 Oct 2018 Sep 2018 Aug 2018 Jul 2018 Jun 2018 May 2018 Apr 2018 Mar 2018 Feb 2018 Jan 2017 Dec 2017 Nov 2017 Oct 2017 Sep 2017 Aug 2017 Jul 2017 Jun 2017 May 2017 Apr 2017 Mar 2017 Feb 2017 Jan 2016 Dec 2016 Nov 2016 Oct 2016 Sep 2016 Aug 2016 Jul 2016 Jun 2016 May 2016 Apr 2016 Mar 2016 Feb 2016 Jan
Applications Filed 28.000000 25.000000 24.000000 28.000000 29.000000 34.000000 32.000000 59.000000 50.000000 53.000000 31.000000 44.000000 49.000000 40.000000 38.000000 34.000000 35.000000 33.000000 38.000000 48.000000 36.000000 34.000000 25.000000 41.000000 17.000000 27.000000 31.000000 34.000000 21.000000 34.000000 21.000000 33.000000 24.000000 23.000000 18.000000 21.000000 17.000000 22.000000 19.000000 20.000000 19.000000 20.000000 25.000000 7.000000 24.000000 21.000000 17.000000 29.000000 18.000000 26.000000 29.000000 22.000000 25.000000 37.000000 26.000000 27.000000 16.000000 22.000000 23.000000 13.000000 17.000000 17.000000 14.000000 23.000000 18.000000 12.000000 19.000000 7.000000 4.000000 15.000000 19.000000 6.000000 22.000000 28.000000 35.000000 39.000000 38.000000 58.000000 45.000000 25.000000 27.000000 50.000000 34.000000 41.000000 29.000000 25.000000 14.000000 20.000000 23.000000 33.000000 31.000000 25.000000 35.000000 32.000000 31.000000 23.000000 18.000000 19.000000 17.000000 25.000000 25.000000 30.000000 23.000000 13.000000 20.000000 19.000000 24.000000 25.000000 16.000000 24.000000 20.000000 17.000000 23.000000 20.000000 38.000000 23.000000 29.000000 24.000000 16.000000 17.000000 29.000000 19.000000 21.000000 21.000000
Companies Wound-Up 21.000000 19.000000 22.000000 20.000000 35.000000 20.000000 24.000000 35.000000 50.000000 40.000000 31.000000 36.000000 32.000000 29.000000 22.000000 38.000000 17.000000 23.000000 40.000000 19.000000 27.000000 35.000000 18.000000 28.000000 26.000000 28.000000 22.000000 24.000000 17.000000 18.000000 24.000000 18.000000 15.000000 14.000000 10.000000 16.000000 15.000000 25.000000 13.000000 16.000000 10.000000 25.000000 5.000000 16.000000 23.000000 24.000000 15.000000 17.000000 20.000000 22.000000 21.000000 17.000000 21.000000 21.000000 28.000000 10.000000 16.000000 17.000000 10.000000 7.000000 15.000000 17.000000 16.000000 13.000000 14.000000 5.000000 8.000000 10.000000 13.000000 17.000000 31.000000 1.000000 4.000000 23.000000 27.000000 48.000000 35.000000 27.000000 18.000000 21.000000 44.000000 24.000000 25.000000 24.000000 19.000000 16.000000 21.000000 13.000000 14.000000 31.000000 16.000000 17.000000 21.000000 20.000000 13.000000 9.000000 11.000000 22.000000 18.000000 15.000000 11.000000 16.000000 11.000000 19.000000 11.000000 15.000000 13.000000 12.000000 17.000000 16.000000 13.000000 14.000000 20.000000 19.000000 15.000000 21.000000 13.000000 14.000000 10.000000 11.000000 22.000000 15.000000 10.000000 17.000000

Columns

Column Type Categorical
Data Series Text No
2026 Apr Numeric No
2026 Mar Numeric No
2026 Feb Numeric No
2026 Jan Numeric No
2025 Dec Numeric No
2025 Nov Numeric No
2025 Oct Numeric No
2025 Sep Numeric No
2025 Aug Numeric No
2025 Jul Numeric No
2025 Jun Numeric No
2025 May Numeric No
2025 Apr Numeric No
2025 Mar Numeric No
2025 Feb Numeric No
2025 Jan Numeric No
2024 Dec Numeric No
2024 Nov Numeric No
2024 Oct Numeric No
2024 Sep Numeric No
2024 Aug Numeric No
2024 Jul Numeric No
2024 Jun Numeric No
2024 May Numeric No
2024 Apr Numeric No
2024 Mar Numeric No
2024 Feb Numeric No
2024 Jan Numeric No
2023 Dec Numeric No
2023 Nov Numeric No
2023 Oct Numeric No
2023 Sep Numeric No
2023 Aug Numeric No
2023 Jul Numeric No
2023 Jun Numeric No
2023 May Numeric No
2023 Apr Numeric No
2023 Mar Numeric No
2023 Feb Numeric No
2023 Jan Numeric No
2022 Dec Numeric No
2022 Nov Numeric No
2022 Oct Numeric No
2022 Sep Numeric No
2022 Aug Numeric No
2022 Jul Numeric No
2022 Jun Numeric No
2022 May Numeric No
2022 Apr Numeric No
2022 Mar Numeric No
2022 Feb Numeric No
2022 Jan Numeric No
2021 Dec Numeric No
2021 Nov Numeric No
2021 Oct Numeric No
2021 Sep Numeric No
2021 Aug Numeric No
2021 Jul Numeric No
2021 Jun Numeric No
2021 May Numeric No
2021 Apr Numeric No
2021 Mar Numeric No
2021 Feb Numeric No
2021 Jan Numeric No
2020 Dec Numeric No
2020 Nov Numeric No
2020 Oct Numeric No
2020 Sep Numeric No
2020 Aug Numeric No
2020 Jul Numeric No
2020 Jun Numeric No
2020 May Numeric No
2020 Apr Numeric No
2020 Mar Numeric No
2020 Feb Numeric No
2020 Jan Numeric No
2019 Dec Numeric No
2019 Nov Numeric No
2019 Oct Numeric No
2019 Sep Numeric No
2019 Aug Numeric No
2019 Jul Numeric No
2019 Jun Numeric No
2019 May Numeric No
2019 Apr Numeric No
2019 Mar Numeric No
2019 Feb Numeric No
2019 Jan Numeric No
2018 Dec Numeric No
2018 Nov Numeric No
2018 Oct Numeric No
2018 Sep Numeric No
2018 Aug Numeric No
2018 Jul Numeric No
2018 Jun Numeric No
2018 May Numeric No
2018 Apr Numeric No
2018 Mar Numeric No
2018 Feb Numeric No
2018 Jan Numeric No
2017 Dec Numeric No
2017 Nov Numeric No
2017 Oct Numeric No
2017 Sep Numeric No
2017 Aug Numeric No
2017 Jul Numeric No
2017 Jun Numeric No
2017 May Numeric No
2017 Apr Numeric No
2017 Mar Numeric No
2017 Feb Numeric No
2017 Jan Numeric No
2016 Dec Numeric No
2016 Nov Numeric No
2016 Oct Numeric No
2016 Sep Numeric No
2016 Aug Numeric No
2016 Jul Numeric No
2016 Jun Numeric No
2016 May Numeric No
2016 Apr Numeric No
2016 Mar Numeric No
2016 Feb Numeric No
2016 Jan Numeric No