Graph and download economic data for Total Revenue for Collection Agencies, All Establishments, Employer Firms (REVEF56144ALLEST) from 1998 to 2022 about collection, agency, employer firms, accounting, revenue, establishments, services, and USA.

Resources represent descriptions of collections and detail the Creators, dates, historical/biographical description, extent and formats available (boxes, folders, photographs, maps, volumes, digital objects, etc.). The data represents collections described at the collection level for improved accessibility.

Graph and download economic data for Household Debt Service Payments as a Percent of Disposable Personal Income (TDSP) from Q1 1980 to Q1 2025 about disposable, payments, debt, personal income, percent, personal, households, services, income, and USA.

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Debt Collection Software Market Size 2025-2029

The debt collection software market size is forecast to increase by USD 3.01 billion, at a CAGR of 8.8% between 2024 and 2029.

The market is experiencing significant growth due to the increasing trend of non-performing loans (NPLs) in various industries. The integration of advanced technologies, such as artificial intelligence and machine learning, into debt collection software solutions is a key driver in this market. These technologies enable more efficient and effective debt collection processes, reducing the time and resources required to recover outstanding debts. However, the high cost of implementing and maintaining these advanced technologies remains a challenge for many organizations, particularly smaller businesses and startups.
Despite this, the potential benefits of utilizing debt collection software, including improved cash flow, reduced administrative burden, and enhanced customer relationships, make it an attractive investment for businesses seeking to optimize their debt collection processes. Companies looking to capitalize on market opportunities should focus on offering cost-effective, user-friendly solutions that leverage the latest technologies to streamline debt collection processes and provide value to their clients. Virtual assistant technology offers assistance in dunning letters, debt recovery solutions, debt settlement, and account reconciliation.

What will be the Size of the Debt Collection Software Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
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The market continues to evolve, driven by the growing need for efficient and effective debt recovery solutions across various sectors. Secure data storage and GDPR compliance are paramount in today's regulatory landscape, ensuring third-party collection agencies can manage debt portfolios with confidence. Collection workflow automation, credit score integration, and payment gateway integration streamline processes and enhance collection efficiency. An example of this market's continuous dynamism is the implementation of an automated collection system by a leading telecommunications company, resulting in a 25% increase in debt recovery. The industry anticipates a growth rate of 12% annually, fueled by the integration of advanced features like agent performance tracking, SMS notification systems, and collection strategy optimization.

Legal compliance features, collection agency management, and first-party collection solutions are essential components of a comprehensive debt recovery system. Payment processing integration, automated email sequences, and debt recovery systems further strengthen the offering. Customer data security, IVR system integration, and fraud detection systems ensure the protection of sensitive information. Moreover, regulatory compliance engines, dunning management processes, data encryption methods, case management systems, risk assessment scoring, debt aging reports, debt buyback platforms, compliance audit trails, PCI DSS compliance, and account receivable management solutions are all integral parts of the evolving debt collection software landscape.

How is this Debt Collection Software Industry segmented?

The debt collection software industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Deployment

  On-premises
  Cloud-based


Industry Application

  Small and medium enterprises
  Large enterprises


Component

  Software
  Services


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    Italy
    UK


  APAC

    China
    India
    Japan
    South Korea


  Rest of World (ROW)

By Deployment Insights

The On-premises segment is estimated to witness significant growth during the forecast period. On-premises debt collection software solutions are a prominent choice in the global market for debt collection software, addressing the demands of businesses seeking to manage their debt collection operations with internal control, enhanced data security, and customizability. These solutions are installed and operated within an organization's premises, offering users the flexibility to manage and maintain their debt collection processes autonomously. In heavily regulated industries, such as finance and healthcare, large enterprises prefer on-premises software to securely store and manage sensitive debtor information, ensuring compliance with stringent data privacy regulations. For instance, DAKCS Software Systems Inc.

The Debt Collection Software Market is driven by automation, security, and regulatory needs. Key functionalities i

Comprehensive dataset of 13 Mapping services in Kansas, United States as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Comprehensive dataset of 25 Mapping services in South Carolina, United States as of August, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Graph and download economic data for Sources of Revenue: Directories, Databases, and Other Collections of Information - Subscriptions and Sales for Directory and Mailing List Publishers, All Establishments, Employer Firms (REVDSSEF51114ALLEST) from 2013 to 2022 about postal, collection, printing, information, employer firms, accounting, revenue, establishments, sales, services, and USA.

Comprehensive dataset of 616 Social services organizations in Arkansas, United States as of August, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Graph and download economic data for Use of Financial Services, Assets: Outstanding Loans to Households at Credit Unions and Financial Cooperatives for United States (USAFCSODUHXDC) from 2004 to 2023 about credit unions, financial, assets, loans, households, services, depository institutions, and USA.

United States ASS: Revenue: FI: Credit Intermediation & Related Activities data was reported at 1,165.830 USD bn in 2016. This records an increase from the previous number of 1,104.812 USD bn for 2015. United States ASS: Revenue: FI: Credit Intermediation & Related Activities data is updated yearly, averaging 1,108.081 USD bn from Dec 2009 (Median) to 2016, with 8 observations. The data reached an all-time high of 1,255.002 USD bn in 2009 and a record low of 1,074.966 USD bn in 2014. United States ASS: Revenue: FI: Credit Intermediation & Related Activities data remains active status in CEIC and is reported by US Census Bureau. The data is categorized under Global Database’s USA – Table US.H020: Annual Services Survey: Employer Firms Revenue.

ASS: Exp: FI: SCOR: Commodity Contracts Brokerage data was reported at 3.399 USD bn in 2016. This records a decrease from the previous number of 3.602 USD bn for 2015. ASS: Exp: FI: SCOR: Commodity Contracts Brokerage data is updated yearly, averaging 3.602 USD bn from Dec 2003 (Median) to 2016, with 11 observations. The data reached an all-time high of 5.100 USD bn in 2008 and a record low of 2.960 USD bn in 2003. ASS: Exp: FI: SCOR: Commodity Contracts Brokerage data remains active status in CEIC and is reported by US Census Bureau. The data is categorized under Global Database’s USA – Table US.H021: Annual Services Survey: Employer Firms Expense.

United States US: BoP: Current Account: Services: Other Business: Credit data was reported at 154.313 USD bn in 2017. This records an increase from the previous number of 143.769 USD bn for 2016. United States US: BoP: Current Account: Services: Other Business: Credit data is updated yearly, averaging 25.386 USD bn from Dec 1970 (Median) to 2017, with 48 observations. The data reached an all-time high of 154.313 USD bn in 2017 and a record low of 910.000 USD mn in 1970. United States US: BoP: Current Account: Services: Other Business: Credit data remains active status in CEIC and is reported by International Monetary Fund. The data is categorized under Global Database’s USA – Table US.IMF.BOP: BPM6: Balance of Payments: Detailed Presentation: Annual.

This datasets contains information about NYC Resident Economic Empowerment and Sustainability (REES) service, a service offered by the New York City Housing Authority (NYCHA) that connects residents to services and opportunity through a formal place-based network. Each row in the dataset represents the number of public housing residents on a Borough-level who receive or utilize this service.

For datasets related to other services provided to NYCHA residents, view the data collection “Services available to NYCHA Residents - Local Law 163”.

Abstract

The World Bank Enterprise Survey (WBES) is a firm-level survey of a representative sample of an economy's private sector. The surveys cover a broad range of topics related to the business environment including access to finance, corruption, infrastructure, competition, and performance.

Geographic coverage

National

Analysis unit

The primary sampling unit of the study is the establishment. An establishment is a physical location where business is carried out and where industrial operations take place or services are provided. A firm may be composed of one or more establishments. For example, a brewery may have several bottling plants and several establishments for distribution. For the purposes of this survey an establishment must make its own financial decisions and have its own financial statements separate from those of the firm. An establishment must also have its own management and control over its payroll.

Universe

All formal (i.e., registered) private sector businesses (with at least 1% private ownership) and with at least five employees. In terms of sectoral criteria, all manufacturing businesses (ISIC Rev 4. codes 10-33) are eligible; for services businesses, those corresponding to the ISIC Rev 4 codes 41-43, 45-47, 49-53, 55-56, 58, 61-62, 69-75, 79, and 95 are included in the Enterprise Surveys. Cooperatives and collectives are excluded from the Enterprise Surveys. All eligible establishments must be registered with the registration agency. In the case of the United States, registration was considered as being registered with the Business Registry and/or the Internal Revenue Service, as a business entity.

The universe table is the total number of eligible establishments, and the table is partitioned by the stratification groups (industry classification, establishment size, and subnational region) in a country.

Note: The universe table can be found in Table 1 of the "United States 2024 World Bank Enterprise Survey Implementation Report, Tables".

Kind of data

Sample survey data [ssd]

Sampling procedure

The WBES use stratified random sampling, where the population of establishments is first separated into non-overlapping groups, called strata, and then respondents are selected through simple random sampling from each stratum. The detailed methodology is provided in the Sampling Note (https://www.enterprisesurveys.org/content/dam/enterprisesurveys/documents/methodology/Sampling_Note-Consolidated-2-16-22.pdf). Stratified random sampling has several advantages over simple random sampling. In particular, it:

• produces unbiased estimates of the whole population or universe of inference, as well as at the levels of stratification
• ensures representativeness by including observations in all of those categories
• produces more precise estimates for a given sample size or budget allocation, and
• may reduce implementation costs by splitting the population into convenient subdivisions.

The WBES typically use three levels of stratification: industry classification, establishment size, and subnational region (used in combination). Starting in 2022, the WBES bases the industry classification on ISIC Rev. 4 (with earlier surveys using ISIC Rev. 3.1). For regional coverage within a country, the WBES has national coverage.

Note: For detailed sampling methodology, refer to the Sampling Structure section in "The United States 2024 World Bank Enterprise Survey Implementation Report".

Mode of data collection

Face-to-face [f2f]

Research instrument

The standard WBES questionnaire covers several topics regarding the business environment and business performance. These topics include general firm characteristics, infrastructure, sales and supplies, trade, management practices, competition, innovation, capacity, land and permits, finance, business-government relations, exposure to bribery, labor, and performance. Information about the general structure of the questionnaire is available in the Enterprise Surveys Manual and Guide (https://www.enterprisesurveys.org/content/dam/enterprisesurveys/documents/methodology/Enterprise-Surveys-Manual-and-Guide.pdf).

Response rate

Overall survey response rate was 11.5%.

Abandoned, lost, or discarded fishing gear (including nets, lines, ropes, traps, seed bags, floats, and buoys used for commercial and recreational fishing and aquaculture) can have adverse impacts on coastal birds through entanglement/entrapment and habitat loss. In the Gulf of Maine region (here defined as southern Atlantic Canada to Cape Cod), these impacts have been widely reported, but poorly documented, hindering clean up and prevention efforts.As part of a project initiated by US Fish and Wildlife Service Migratory Birds and National Oceanic and Atmospheric Administration Marine Debris Program staff, and a University of Rhode Island graduate student, this system was developed for reporting information on the extent of fishing gear present in coastal habitats and associated interactions with birds. Such information can help managers, conservationists, and other stakeholders better understand and reduce impacts of such gear.The information you provide here will be compiled by the USFWS and made accessible to land and wildlife managers and other professional stakeholders upon request. In addition, brief summaries will be produced at regular intervals and served on the Marine Debris Collaborative Portal for general audiences.This reporting form (link: https://arcg.is/0njf0P0) includes a set of questions about gear you observe within a site, and associated interactions between gear and wildlife. The form should take 15-20 minutes to complete per site.Please contact caleb_spiegel@fws.gov for more information.Please note: In many jurisdictions it is unlawful to remove certain types of gear from the coast or the water without a state-issued permit, even if it appears to be discarded. Contact your local fish and wildlife agency for more information.Form designed by Meg Harrington and Helen Manning - USFWS---------------------------------------------------------------------------------------------OMB Control No. 1018-0188Expires 02/28/2026NOTICESPaperwork Reduction Act StatementIn accordance with the Paperwork Reduction Act (44 U.S.C. 3501 et seq.), the U.S. Fish and Wildlife Servicecollects information through the AGOL platform to improve our online maps, web-mapping applications, andstory maps, and to respond to requests made under the Freedom of Information Act and the Privacy Act of1974. Information requested in this form is purely voluntary. According to the Paperwork Reduction Act of1995, an agency may not conduct or sponsor and a person is not required to respond to a collection ofinformation unless it displays a currently valid OMB control number. OMB has approved this collection ofinformation and assigned Control No. 1018-0188.Estimated Burden StatementWe estimate public reporting for this collection of information to average 5 minutes per response, dependingon activity, including the time for reviewing instructions, searching existing data sources, gathering andmaintaining the data needed, and completing and reviewing the collection of information. Send commentsregarding this burden estimate or any other aspect of this collection of information, including suggestions forreducing this burden, to the Service Information Collection Clearance Officer, Division of Policy,Performance, Risk Management, and Analytics, U.S. Fish and Wildlife Service, MS: PRB (JAO/3W), 5275Leesburg Pike, Falls Church, VA 22041-3803, or via email at Info_Coll@fws.gov.

Graph and download economic data for Nonrevolving Consumer Credit Owned and Securitized by Finance Companies, Flow (DTCTLNHFXDFBANM) from Feb 1943 to May 2025 about nonrevolving, securitized, owned, finance companies, consumer credit, companies, flow, finance, financial, loans, consumer, and USA.

Graph and download economic data for Finance Companies; Consumer Credit; Asset, Transactions (BOGZ1FA613066005Q) from Q4 1946 to Q1 2025 about finance companies, consumer credit, companies, finance, transactions, financial, assets, loans, consumer, and USA.

Graph and download economic data for Credit Unions; Agency- and GSE-Backed Securities, Excluding Structured Agency- and GSE-Backed Securities; Asset, Transactions (BOGZ1FA473061795Q) from Q4 1946 to Q1 2025 about credit unions, agency, transactions, securities, assets, depository institutions, and USA.

Graph and download economic data for Life Insurance Companies, General Accounts; FHLB Advances; Liability, Level (LICTCMDODFS) from Q4 1945 to Q1 2025 about advances, FHLB, general accounts, credit market, life, accounting, companies, insurance, liabilities, sector, financial, debt, domestic, and USA.

Graph and download economic data for Credit Unions; Agency- and GSE-Backed Securities, Excluding Structured Agency- and GSE-Backed Securities; Asset, Transactions (BOGZ1FU473061795A) from 1946 to 2024 about credit unions, agency, transactions, securities, assets, depository institutions, and USA.