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Debt Collection Software Market to Grow by USD 2.31 Billion (2024-2028), Driven by Rising Non-Performing Loans (NPLs), with AI Driving Market Transformation – Technavio

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NEW YORK, Nov. 19, 2024 /PRNewswire/ — Report with the AI impact on market trends – The global debt collection software market size is estimated to grow by USD 2.31 billion from 2024-2028, according to Technavio. The market is estimated to grow at a CAGR of 8.92% during the forecast period. Rise in non-performing loans (npls) is driving market growth, with a trend towards integration of advanced technologies in debt collection software. However, high cost of debt collection software poses a challenge.Key market players include AgreeYa Solutions Inc., Analog Legalhub Technology Solutions Pvt. Ltd., CDS Software, Chetu Inc., Comtech Systems Inc., Comtronic Systems LLC, DAKCS Software Systems Inc., Debt Pay Inc., DebtCol Software Pty. Ltd., Debtrak, Experian Plc, ezyCollect Pty. Ltd., Fair Isaac Corp., Fidelity National Information Services Inc., Gaviti Akyl Ltd., Indigo Cloud Ltd., MarketXpander Services Pvt. Ltd., Nestack Technologies Pvt. Ltd., PDCflow, PrimeSoft Solutions Inc., Quantrax Corp. Inc., Radixweb, receeve GmbH, Sila Inc., Totality Software Inc., A4dable Software, Ameyo Pvt Ltd., DBA PaySimple Inc., and Simplicity Collection Software.

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Debt Collection Software Market Scope

Report Coverage

Details

Base year

2023

Historic period

2018 – 2022

Forecast period

2024-2028

Growth momentum & CAGR

Accelerate at a CAGR of 8.92%

Market growth 2024-2028

USD 2.31 billion

Market structure

Fragmented

YoY growth 2022-2023 (%)

7.48

Regional analysis

North America, Europe, APAC, South America, and Middle East and Africa

Performing market contribution

APAC at 31%

Key countries

US, Japan, China, Germany, and UK

Key companies profiled

AgreeYa Solutions Inc., Analog Legalhub Technology Solutions Pvt. Ltd., CDS Software, Chetu Inc., Comtech Systems Inc., Comtronic Systems LLC, DAKCS Software Systems Inc., Debt Pay Inc., DebtCol Software Pty. Ltd., Debtrak, Experian Plc, ezyCollect Pty. Ltd., Fair Isaac Corp., Fidelity National Information Services Inc., Gaviti Akyl Ltd., Indigo Cloud Ltd., MarketXpander Services Pvt. Ltd., Nestack Technologies Pvt. Ltd., PDCflow, PrimeSoft Solutions Inc., Quantrax Corp. Inc., Radixweb, receeve GmbH, Sila Inc., Totality Software Inc., A4dable Software, Ameyo Pvt Ltd., DBA PaySimple Inc., and Simplicity Collection Software

Market Driver

The Debt Collection Software market is witnessing significant trends, including automation, multichannel communication, and affordability for organizations of all sizes. Large enterprises segment seeks economies of scale through deployment of advanced debt collection solutions. Services and solutions segments dominate, offering debt collection services and modern applications for effective loan recovery. Implementation of debt collection software involves business-specific needs, training, and implementation work. Legacy systems are being replaced with modern applications for productivity and effective debt recovery. Borrower data, overdue invoice reminders, phone calls, and online payment collection are essential components of the debt collection ecosystem. Banks and financial organizations prioritize debt collection journeys and money collection process, addressing complexities through automation, notifications, alerts, and compliance with consumer protection laws and debt collection regulations. Costs, bankruptcy status, and litigious consumers pose challenges. InterProse Corporation’s InterProse ACE offers debt collection software for government organizations, with components including text messaging, voice mail drops, dialers, and compliance with debt collection regulations. Deployment options include on-premises and cloud-based, catering to enterprise size. 

The debt collection software market is undergoing a transformation through the integration of advanced technologies such as artificial intelligence (AI), machine learning (ML), and data analytics. These technologies are streamlining debt collection processes by enhancing decision-making capabilities, automating repetitive tasks, and improving overall efficiency. AI specifically, is revolutionizing the financial industry by enabling automated decision-making processes, predictive analytics, and personalized customer interactions. For instance, AI algorithms analyze historical debtor data to forecast payment behaviors and suggest tailored collection strategies, resulting in more effective interventions. This technological integration is a game-changer for the debt collection industry. 

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Market Challenges

The Debt Collection Software market faces challenges in automating debt collection processes for organizations, particularly in the large enterprises segment. Affordability and economies of scale are key considerations, as debt collection software solutions must effectively meet business-specific needs without straining budgets. Automation of loan recovery processes, online payment collection, and multichannel communication are essential for productivity and effective debt recovery. Services and solutions segments offer debt collection services and deployment of software for organizations. Debt collection journeys include overdue invoice reminders, phone calls, text messaging, voice mail drops, and dialers. Borrower data, debt collection regulations, bankruptcy status, and litigious consumers add complexities to the debt collection ecosystem. InterProse Corporation’s InterProse ACE software addresses these challenges with automatic monitoring, notifications, and alerts. Deployment options include on-premises and cloud-based solutions, catering to various enterprise sizes. Training and implementation work are crucial for successful deployment and integration with core business systems, such as legacy systems and modern applications. Consumer protection laws and debt collection regulations must be adhered to, ensuring compliance and effective debt collection. Costs, productivity, and effective debt recovery are the primary objectives for financial and banking organizations. The debt collection software market continues to evolve, providing innovative solutions to streamline the money collection process.The debt collection software market is facing a significant challenge due to the high cost of the software. This issue poses a barrier for smaller debt collection agencies and businesses with limited financial resources, potentially reducing competition and increasing prices for consumers. The average cost of the software ranges from USD480 to USD1200 yearly per user, with enterprise solutions costing more based on specific requirements. This high expense can hinder market growth and limit access to effective debt collection solutions for many organizations.

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Segment Overview

This debt collection software market report extensively covers market segmentation by

Deployment1.1 On-premises1.2 Cloud-basedIndustry Application2.1 Small and medium enterprises2.2 Large enterprisesGeography3.1 North America3.2 Europe3.3 APAC3.4 South America3.5 Middle East and Africa

1.1 On-premises- On-premises debt collection software solutions hold a substantial position in the global debt collection software market, addressing the demands of businesses that value internal infrastructure management, data security, and customizability. These software solutions are installed and operated within an organization’s premises, granting users a significant degree of autonomy over their debt collection operations. Large enterprises, particularly those in regulated industries like finance and healthcare, prefer on-premises debt collection software to safeguard sensitive debtor information and adhere to stringent data privacy regulations. Companies such as DAKCS Software Systems Inc. (DAKCS) provide tailored on-premises debt collection solutions, catering to the unique security and regulatory needs of large enterprises. This level of customization is particularly appealing to complex debt collection operations within large enterprises. On-premises debt collection software enables organizations to maintain full control over their data and operations, which is essential for large enterprises adhering to strict IT policies and security protocols. Providers like CDS Software offer extensive on-premises debt collection software, empowering large enterprises to manage their debt collection processes while ensuring data security and integrity. The need for direct control over data and operations, combined with the ability to customize software to align with specific business processes, is expected to fuel the growth of the on-premises segment in the global debt collection software market.

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Research Analysis

The Debt Collection Software market is witnessing significant growth due to the automation of debt collection processes, providing large enterprises with economies of scale and affordability. This market caters to both services and solutions segments, offering debt collection services and software solutions to organizations. The deployment of debt collection software streamlines the loan recovery process, enabling effective communication through multichannel methods. Borrower data management is crucial, and these systems provide features like overdue invoice reminders, phone calls, and online payment collection. Banking and financial organizations benefit greatly from these solutions, increasing productivity and improving the effectiveness of debt recovery. However, implementing debt collection software comes with complexities, including business-specific needs, training, and implementation work. Legacy systems and modern applications must be considered during strategy development. The debt collection ecosystem requires a well-thought-out plan for successful implementation.

Market Research Overview

The Debt Collection Software market is witnessing significant growth due to the automation of debt collection processes, which helps organizations streamline their loan recovery process and improve productivity. The large enterprises segment is a major contributor to the market’s growth, as they can leverage economies of scale and affordability. The market offers both solutions and services segments, with debt collection services being a popular choice for organizations seeking expert assistance in managing their debt collection journeys. The deployment of debt collection software involves careful strategy and implementation, taking into account business-specific needs and the complexities of the debt collection ecosystem. Modern applications replace legacy systems, offering online payment collection, overdue invoice reminders, and multichannel communication options like phone calls, text messaging, voice mail drops, and dialers. Implementation work includes training and adherence to debt collection regulations, consumer protection laws, bankruptcy status, and litigious consumers. The market caters to banking organizations, financial institutions, government organizations, and other entities, providing effective debt recovery and cost savings through automatic monitoring, notifications, and alerts.

Table of Contents:

1 Executive Summary
2 Market Landscape
3 Market Sizing
4 Historic Market Size
5 Five Forces Analysis
6 Market Segmentation

DeploymentOn-premisesCloud-basedIndustry ApplicationSmall And Medium EnterprisesLarge EnterprisesGeographyNorth AmericaEuropeAPACSouth AmericaMiddle East And Africa

7 Customer Landscape
8 Geographic Landscape
9 Drivers, Challenges, and Trends
10 Company Landscape
11 Company Analysis
12 Appendix

About Technavio

Technavio is a leading global technology research and advisory company. Their research and analysis focuses on emerging market trends and provides actionable insights to help businesses identify market opportunities and develop effective strategies to optimize their market positions.

With over 500 specialized analysts, Technavio’s report library consists of more than 17,000 reports and counting, covering 800 technologies, spanning across 50 countries. Their client base consists of enterprises of all sizes, including more than 100 Fortune 500 companies. This growing client base relies on Technavio’s comprehensive coverage, extensive research, and actionable market insights to identify opportunities in existing and potential markets and assess their competitive positions within changing market scenarios.

Contacts

Technavio Research
Jesse Maida
Media & Marketing Executive
US: +1 844 364 1100
UK: +44 203 893 3200
Email: media@technavio.com
Website: www.technavio.com/

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Technology

Chef Robotics Physical AI Models Can Now Automate Baked Goods Packing

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SAN FRANCISCO, April 29, 2026 /PRNewswire/ — Chef Robotics, a leader in physical AI for the food industry, today announced that Chef robots can now automate tray assembly for baked goods packing. The application places baked products, such as burger buns, chocolate chip cookies, biscotti, butter cookies, biscuits, fortune cookies, granola bars, rusks, and shortbreads into trays and packaging containers before sealing.

Watch Chef robots in action.

Baked goods packing has historically been difficult to automate for high-mix production. Each item behaves differently on the production line—a granola bar compresses under the wrong grip, while a biscotti or rusk can crack if placed at the wrong angle. Surface textures range from glazed and smooth to crumbly and irregular, and strict presentation requirements leave little room for error. This variability has made it challenging for automation systems to reliably handle baked goods at production speeds, leaving food manufacturers dependent on manual labor and traditional bakery equipment.

To address this, Chef built its baked goods packing application on its existing piece-picking capability, which uses Chef’s AI-powered computer vision and physical AI models trained across diverse real-world production environments. This allows Chef robots to assess each item’s position, shape, and orientation in real time and determine how to pick the items from the pan and place them quickly and precisely without damaging them.

The baked goods packing application supports four distinct placement capabilities.

First, Chef’s vision system detects the angle at which each item sits in the pan and reorients it after picking, placing it on the tray at the exact angle required, regardless of its original position, enabling retail-ready presentation for SKUs that require precise angular placement.

Second, Chef robots can place multiple baked goods into the same packaging container in a single automated pass, completing full tray assembly without manual intervention.

Third, for packaging containers with multiple small compartments, Chef robots can precisely place items into each designated section, including multiple items in the same compartment, using Chef’s AI vision model to detect compartment positions and orientations in real time.

Fourth, Chef’s vision system identifies the exact center of each tray and places every item at a predefined offset from that center, ensuring a uniform, consistent arrangement across every pack regardless of how trays arrive on the conveyor.

For food manufacturers evaluating bakery systems and baked goods packaging automation, the application offers higher throughput, reduced labor dependency, and consistent presentation across shifts. The capability runs on Chef’s existing robotic hardware and software, allowing manufacturers to deploy it without requiring any changes to their production lines.

Chef’s baked goods packing application is available in the U.S., Canada, Germany, and the UK and is included as part of Chef’s robotics-as-a-service (RaaS) pricing model.

About Chef Robotics
Chef is the first company to have commercialized a scalable AI-driven food robotics solution. With over 104 million servings made in production, Chef leverages ChefOS, an AI platform for food manipulation, to offer a Robotics-as-a-Service solution that helps industry-leading food companies increase production volume and meet demand. Headquartered in San Francisco, CA, Chef aims to empower humans to do what humans do best by accelerating the advent of intelligent machines. Visit https://chefrobotics.ai to learn more.

View original content:https://www.prnewswire.com/news-releases/chef-robotics-physical-ai-models-can-now-automate-baked-goods-packing-302756923.html

SOURCE Chef Robotics

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Technology

Chef Robotics Physical AI Models Can Now Automate Baked Goods Packing

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SAN FRANCISCO, April 29, 2026 /PRNewswire/ — Chef Robotics, a leader in physical AI for the food industry, today announced that Chef robots can now automate tray assembly for baked goods packing. The application places baked products, such as burger buns, chocolate chip cookies, biscotti, butter cookies, biscuits, fortune cookies, granola bars, rusks, and shortbreads into trays and packaging containers before sealing.

Watch Chef robots in action.

Baked goods packing has historically been difficult to automate for high-mix production. Each item behaves differently on the production line—a granola bar compresses under the wrong grip, while a biscotti or rusk can crack if placed at the wrong angle. Surface textures range from glazed and smooth to crumbly and irregular, and strict presentation requirements leave little room for error. This variability has made it challenging for automation systems to reliably handle baked goods at production speeds, leaving food manufacturers dependent on manual labor and traditional bakery equipment.

To address this, Chef built its baked goods packing application on its existing piece-picking capability, which uses Chef’s AI-powered computer vision and physical AI models trained across diverse real-world production environments. This allows Chef robots to assess each item’s position, shape, and orientation in real time and determine how to pick the items from the pan and place them quickly and precisely without damaging them.

The baked goods packing application supports four distinct placement capabilities.

First, Chef’s vision system detects the angle at which each item sits in the pan and reorients it after picking, placing it on the tray at the exact angle required, regardless of its original position, enabling retail-ready presentation for SKUs that require precise angular placement.

Second, Chef robots can place multiple baked goods into the same packaging container in a single automated pass, completing full tray assembly without manual intervention.

Third, for packaging containers with multiple small compartments, Chef robots can precisely place items into each designated section, including multiple items in the same compartment, using Chef’s AI vision model to detect compartment positions and orientations in real time.

Fourth, Chef’s vision system identifies the exact center of each tray and places every item at a predefined offset from that center, ensuring a uniform, consistent arrangement across every pack regardless of how trays arrive on the conveyor.

For food manufacturers evaluating bakery systems and baked goods packaging automation, the application offers higher throughput, reduced labor dependency, and consistent presentation across shifts. The capability runs on Chef’s existing robotic hardware and software, allowing manufacturers to deploy it without requiring any changes to their production lines.

Chef’s baked goods packing application is available in the U.S., Canada, Germany, and the UK and is included as part of Chef’s robotics-as-a-service (RaaS) pricing model.

About Chef Robotics
Chef is the first company to have commercialized a scalable AI-driven food robotics solution. With over 104 million servings made in production, Chef leverages ChefOS, an AI platform for food manipulation, to offer a Robotics-as-a-Service solution that helps industry-leading food companies increase production volume and meet demand. Headquartered in San Francisco, CA, Chef aims to empower humans to do what humans do best by accelerating the advent of intelligent machines. Visit https://chefrobotics.ai to learn more.

View original content:https://www.prnewswire.com/news-releases/chef-robotics-physical-ai-models-can-now-automate-baked-goods-packing-302756923.html

SOURCE Chef Robotics

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Air Products to Expand Industrial Gas Supply for Samsung Electronics’ Next-Generation Semiconductor Fab in South Korea

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New investment underscores the company’s long-term commitment to Korea and its leading role in the global semiconductor industry 

LEHIGH VALLEY, Pa., April 29, 2026 /PRNewswire/ — Air Products (NYSE:APD), a world-leading industrial gases company and serving Samsung globally, today announced it has been selected by Samsung to supply industrial gases for its new advanced semiconductor fab in Pyeongtaek, Gyeonggi Province, South Korea.

Under the agreement, Air Products will build, own and operate multiple state-of-the-art production facilities and a bulk specialty gas supply system to supply nitrogen, oxygen, argon, and hydrogen for Samsung’s new semiconductor fab. The new facilities are expected to come onstream in multiple phases from 2028 through 2030.

Air Products has a long track record of executing multiple phase expansions in Pyeongtaek to support Samsung’s growing manufacturing needs. This latest project represents Air Products’ largest investment to date in the semiconductor industry and will establish Pyeongtaek as the company’s single largest operations site globally supporting the electronics industry. 

“Air Products is honored to be selected once again by Samsung and to have their continued confidence as a trusted partner supporting their strategic growth plans,” said SR Kim, President, Air Products Korea. “This significant investment reinforces Air Products’ role as a leading global supplier to the semiconductor industry and underscores our long-standing commitment to supporting our strategic customers with safety, reliability, efficiency and excellent service.”

Air Products has served the global electronics industry for more than 40 years, supplying industrial gases safely and reliably to many of the world’s leading technology companies. The company has operated in Korea for more than 50 years and has established a strong position in electronics and manufacturing sectors.

About Air Products

Air Products (NYSE: APD) is a world-leading industrial gases company in operation for over 85 years focused on serving energy, environmental, and emerging markets and generating a cleaner future. The Company supplies essential industrial gases, related equipment and applications expertise to customers in dozens of industries, including refining, chemicals, metals, electronics, manufacturing, medical and food. As the leading global supplier of hydrogen, Air Products also develops, engineers, builds, owns and operates some of the world’s largest clean hydrogen projects, supporting the transition to low- and zero-carbon energy in the industrial and heavy-duty transportation sectors. Through its sale of equipment businesses, the Company also provides turbomachinery, membrane systems and cryogenic containers globally.

Air Products had fiscal 2025 sales of $12 billion from operations in approximately 50 countries. For more information, visit airproducts.com or follow us on LinkedInXFacebook or Instagram.

This release contains “forward-looking statements” within the safe harbor provisions of the Private Securities Litigation Reform Act of 1995. These forward-looking statements are based on management’s expectations and assumptions as of the date of this release and are not guarantees of future performance. While forward-looking statements are made in good faith and based on assumptions, expectations and projections that management believes are reasonable based on currently available information, actual performance and financial results may differ materially from projections and estimates expressed in the forward-looking statements because of many factors, including the risk factors described in our Annual Report on Form 10-K for the fiscal year ended September 30, 2025 and other factors disclosed in our filings with the Securities and Exchange Commission. Except as required by law, we disclaim any obligation or undertaking to update or revise any forward-looking statements contained herein to reflect any change in the assumptions, beliefs or expectations or any change in events, conditions or circumstances upon which any such forward-looking statements are based.

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