Following the drastic increase directly after the COVID-19 pandemic, the delinquency rate started to gradually decline, falling below *** percent in the second quarter of 2023. In the second half of 2023, the delinquency rate picked up but remained stable throughout 2024. In the second quarter of 2025, **** percent of mortgage loans were delinquent. That was significantly lower than the **** percent during the onset of the COVID-19 pandemic in 2020 or the peak of *** percent during the subprime mortgage crisis of 2007-2010. What does the mortgage delinquency rate tell us? The mortgage delinquency rate is the share of the total number of mortgaged home loans in the U.S. where payment is overdue by 30 days or more. Many borrowers eventually manage to service their loan, though, as indicated by the markedly lower foreclosure rates. Total home mortgage debt in the U.S. stood at almost ** trillion U.S. dollars in 2024. Not all mortgage loans are made equal ‘Subprime’ loans, being targeted at high-risk borrowers and generally coupled with higher interest rates to compensate for the risk. These loans have far higher delinquency rates than conventional loans. Defaulting on such loans was one of the triggers for the 2007-2010 financial crisis, with subprime delinquency rates reaching almost ** percent around this time. These higher delinquency rates translate into higher foreclosure rates, which peaked at just under ** percent of all subprime mortgages in 2011.

In 2023, the delinquency rates of all types of mortgage lenders in Canada increased. As of the fourth quarter of the year, approximately 1.05 percent of loans in the loan portfolios of mortgage investment entities (MIEs) were classified as delinquent, which was a decrease from the 0.78 percent delinquency rate a year ago. A loan is reported by lenders as being delinquent after 270 days of late payments.

Graph and download economic data for Delinquency Rate on Single-Family Residential Mortgages, Booked in Domestic Offices, Banks Not Among the 100 Largest in Size by Assets (DRSFRMOBN) from Q1 1991 to Q2 2025 about domestic offices, delinquencies, 1-unit structures, mortgage, family, residential, domestic, assets, banks, depository institutions, rate, and USA.

Delinquency rates for credit cards picked up in 2025 in the United States, leading to the highest rates observed since 2008. This is according to a collection of one of the United States' federal banks across all commercial banks. The high delinquency rates were joined by the highest U.S. credit card charge-off rates since the Financial Crisis of 2008. Delinquency rates, or the share of credit card loans overdue a payment for more than ** days, can sometimes lead into charge-off, or a writing off the loan, after about six to 12 months. These figures on the share of credit card balances that are overdue developed significantly between 2021 and 2025: Delinquencies were at their lowest point in 2021 but increased to one of their highest points by 2025. This is reflected in the growing credit card debt in the United States, which reached an all-time high in 2023. As of Q2 2025, the delinquency rate stands at 3.05%.

Graph and download economic data for Delinquency Rate on Commercial Real Estate Loans (Excluding Farmland), Booked in Domestic Offices, All Commercial Banks (DRCRELEXFACBS) from Q1 1991 to Q3 2025 about farmland, domestic offices, delinquencies, real estate, commercial, domestic, loans, banks, depository institutions, rate, and USA.

Loans to households includes both consumer debt and mortgage loans. In February 2023, the share of delinquent household loans, excluding credit card debt, in South Korea stood at *** percent. The delinquency rate has remained stable since November 2022.

United States - Delinquency Rate on Single-Family Residential Mortgages, Booked in Domestic Offices, Banks Not Among the 100 Largest in Size by Assets was 1.37% in October of 2024, according to the United States Federal Reserve. Historically, United States - Delinquency Rate on Single-Family Residential Mortgages, Booked in Domestic Offices, Banks Not Among the 100 Largest in Size by Assets reached a record high of 4.56 in October of 2009 and a record low of 0.98 in April of 2023. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Delinquency Rate on Single-Family Residential Mortgages, Booked in Domestic Offices, Banks Not Among the 100 Largest in Size by Assets - last updated from the United States Federal Reserve on November of 2025.

Graph and download economic data for Delinquency Rate on Consumer Loans, All Commercial Banks (DRCLACBS) from Q1 1987 to Q3 2025 about delinquencies, commercial, loans, consumer, banks, depository institutions, rate, and USA.

quarter 30 DLQ (% Vol) 60+ DLQ (% Vol) Q4 2023 0.876% 0.563% Q1 2024 0.875% 0.491% Q2 2024 0.510% 0.605% Q3 2024 0.499% 0.685% Q4 2024 0.938% 0.783% Q1 2025 1.034% 0.534% Q2 2025 0.531% 0.736%

2023-Q4 2024-Q1 2024-Q2 2024-Q3 2024-Q4 2025-Q1 2025-Q2 1st Lien 60+ DLQ % 0.66% 0.53% 0.66% 0.75% 0.84% 0.52% 0.76% 2nd lien 60+ DLQ% 0.43% 0.42% 0.47% 0.51% 0.56% 0.48% 0.54%

The delinquency rates on commercial and industrial loans at commercial banks in the United States has remained relatively stable in the years leading to 2024. As of the second quarter 2021, the delinquency rate on business loans at commercial banks in the United States stood at **** percent, a figure that decreased to **** percent by the third quarter of 2023, only to rise to *** percent in the last quarter of 2024.

In the second quarter of 2025, roughly **** percent of all consumer loans at commercial banks in the United States were delinquent. The delinquency rate on this type of credit has been rising again since 2021. Loans are delinquent when the borrower does not pay their obligations on time. One of the reasons for the delinquency rate decreasing during the first years of the COVID-19 pandemic was that the personal saving rate in the U.S. soared during that period. What is the trend in consumer credit levels in the United States? Consumer credit refers to the various types of loans and credit extended to individuals for personal use, often to fund everyday purchases or larger expenses. When credit levels rise, it often signals that consumers are more confident in their ability to manage debt and make future payments. After a period of strong growth between 2021 and early 2023, consumer credit in the United States has been growing at a slower pace. By early 2024, consumer credit levels reached over **** trillion U.S. dollars. What is the main channel for acquiring consumer credit? In 2024, the leading type of consumer credit among consumers in the U.S. was credit card bills. Credit card usage in the North American country was substantial and credit card penetration was expected to reach over **** percent by 2029. Car loans ranked next as a common source of consumer credit, while other types of debt, such as medical bills, home equity lines of credit, and personal educational loans, had lower percentages.

Cleveland-Elyria-Mentor, OH, was the metropolitan area with the highest share of distressed hotel real estate debt in the United States in April 2023. Distressed real estate loans, or the share of debt which was delinquent or in special servicing, was over ** percent. The hotel sector was severely impacted by the travel restrictions during the coronavirus pandemic. Despite having the second-highest delinquency rates across the different types of commercial real estate, lodging saw a substantial improvement in delinquencies since March 2021, when it almost hit ** percent.

Greece, Cyprus, and Hungary were the countries with the highest share of non-performing mortgage loans in the second quarter of 2023. In Greece, *** percent of the gross carrying amount of mortgage loans to households was considered non-performing. In Spain, which was the country with the highest value of non-performing mortgages, this share was *** percent.

Problem Statement In today's financial landscape, an accurate prediction of customer loan default can reduce the risk and maintain a healthy lending portfolio. The challenge requires the participants to develop machine learning models to determine the likelihood of a customer defaulting on a loan.

Contestants will be provided with credit history, payment behaviour, and account details to build the model. This challenge mirrors a huge real-world problem faced by financial institutions, thus making it extremely relevant.

Dataset Description

The dataset provided to the participants will contain:

Customer Information:

customer_id: Unique identifier for each customer application. firstname: First name of the customer. lastname: Last name of the customer. Credit Record Information:

record_number: Sequence number of the credit product in the credit history. days_since_opened: Days from credit opening date to data collection date. days_since_confirmed: Days from credit information confirmation date till data collection date. primary_term: Planned number of days from credit opening date to closing date. final_term: Actual number of days from credit opening date to closing date. days_till_primary_close: Planned number of days from data collection date until loan closing date. days_till_final_close: Actual number of days from data collection date until loan closing date. loans_credit_limit: Credit limit for the customer's loans. loans_next_payment_summary: Amount of the next loan payment. loans_outstanding_balance: Outstanding balance amount. loans_max_overdue_amount: Maximum overdue amount. loans_credit_cost_rate: Cost rate associated with loans. Loan Overdue Information:

loans_within_5_days to loans_over_90_days: Number of loans overdue within different time frames. is_zero_loans_within_5_days to is_zero_loans_over_90_days: Binary indicators for zero loans overdue within different time frames. Credit Utilization and Limit Information:

utilization: Credit utilization rate. over_limit_count: Count of instances where the customer went over the credit limit. max_over_limit_count: Maximum count of instances where the customer exceeded the credit limit. is_zero_utilization: Binary indicator if credit utilization rate is zero. is_zero_over_limit_count: Binary indicator if the count of over limit instances is zero. is_zero_max_over_limit_count: Binary indicator if the maximum over limit count is zero. Encoded Features:

encoded_payment_X: Encoded information about payment X (categorical features converted to numerical values). encoded_loans_account_holder_type: Encoded information about the type of account holder for loans. encoded_loans_credit_status: Encoded information about the credit status of loans. encoded_loans_credit_type: Encoded information about the type of credit for loans. encoded_loans_account_currency: Encoded information about the currency used for loans. Close Flags:

primary_close_flag: Binary indicator for primary term close. final_close_flag: Binary indicator for final term close.

Snapshot img

Home Equity Lending Market Size 2025-2029

The home equity lending market size is forecast to increase by USD 48.16 billion, at a CAGR of 4.7% between 2024 and 2029.

The market is experiencing significant growth, fueled primarily by the massive increase in home prices and the resulting rise in residential properties with substantial equity. This trend presents a lucrative opportunity for lenders, as homeowners with substantial equity can borrow against their homes to fund various expenses, from home improvements to debt consolidation. However, this market also faces challenges. Lengthy procedures and complex regulatory requirements can hinder the growth of home equity lending, making it essential for lenders to streamline their processes and ensure compliance with evolving regulations.
Additionally, economic uncertainty and potential interest rate fluctuations may impact borrower demand, requiring lenders to adapt their strategies to remain competitive. To capitalize on market opportunities and navigate challenges effectively, lenders must focus on enhancing the borrower experience, leveraging technology to streamline processes, and maintaining a strong regulatory compliance framework.

What will be the Size of the Home Equity Lending 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, shaped by various economic and market dynamics. Fair lending practices remain a crucial aspect, with entities ensuring borrowers' creditworthiness through rigorous risk assessments. Economic conditions, employment history, and credit score are integral components of this evaluation. Mortgage insurance (PMIs) and mortgage-backed securities (MBS) are employed to mitigate risk in the event of default. Verification of income, property value, and consumer protection are also essential elements in the home equity lending process. Housing prices, Homeowners Insurance, and property value are assessed to determine the loan-to-value ratio (LTV) and interest rate risk. Prepayment penalties, closing costs, and loan term are factors that influence borrowers' financial planning and decision-making.

The regulatory environment plays a significant role in shaping market activities. Consumer confidence, financial literacy, and foreclosure prevention initiatives are key areas of focus. real estate market volatility and mortgage rates impact the demand for home equity loans, with cash-out refinancing and debt consolidation being popular applications. Amortization schedules, mortgage broker involvement, and escrow accounts are essential components of the loan origination process. Market volatility and housing market trends continue to unfold, requiring ongoing risk assessment and adaptation.

How is this Home Equity Lending Industry segmented?

The home equity lending 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.

Source

  Mortgage and credit union
  Commercial banks
  Others


Distribution Channel

  Offline
  Online


Purpose

  Home Improvement
  Debt Consolidation
  Investment


Loan Type

  Fixed-Rate
  Variable-Rate


Geography

  North America

    US
    Mexico


  Europe

    France
    Germany
    Italy
    UK


  Middle East and Africa

    UAE


  APAC

    Australia
    China
    India
    Japan
    South Korea


  South America

    Brazil


  Rest of World (ROW)

By Source Insights

The mortgage and credit union segment is estimated to witness significant growth during the forecast period.

In the realm of home equity lending, mortgage and credit unions emerge as trusted partners for consumers. These financial institutions offer various services beyond home loans, including deposit management, checking and savings accounts, and credit and debit cards. By choosing a mortgage or credit union for home equity lending, consumers gain access to human advisors who can guide them through the intricacies of finance. Mortgage and credit unions provide competitive rates on home equity loans, making them an attractive option. Consumer protection is a priority, with fair lending practices and rigorous risk assessment ensuring creditworthiness. Economic conditions, employment history, and credit score are all taken into account during the loan origination process.

Home equity loans can be used for various purposes, such as home improvement projects, debt consolidation, or cash-out refinancing. Consumer confidence plays a role in loan origination, with interest rates influenced by market volatility and economic conditions. Fixed-rate and adjustable-rate loans are available, each with its advantag

New York-Northern New Jersey-Long Island, NY-NJ-PA, was the metropolitan area with the highest value of distressed hotel real estate debt in the United States in April 2023. Distressed real estate loans, or the share of debt which was delinquent or in special servicing, amounted to over *********** U.S. dollars. The hotel sector was severely impacted by the travel restrictions during the coronavirus pandemic. Despite having the second-highest delinquency rates across the different types of commercial real estate, lodging saw a substantial improvement in delinquencies since **********, when it almost hit ** percent.

NPL Management Market Outlook

The global NPL (Non-Performing Loans) Management market size was valued at approximately USD 3.2 billion in 2023 and is projected to grow at a compound annual growth rate (CAGR) of 6.8% from 2024 to 2032, reaching an estimated USD 5.9 billion by 2032. The market is experiencing significant growth due to increasing financial pressures on institutions to manage non-performing assets effectively and efficiently.

One of the primary growth factors driving the NPL Management market is the increasing volume of non-performing loans globally. Economic downturns, geopolitical tensions, and economic challenges such as inflation and unemployment have led to higher default rates, necessitating advanced systems and solutions for managing these problematic assets. Financial institutions require robust tools and services to mitigate risks and recover debts, driving demand for NPL management solutions.

Additionally, regulatory pressures are compelling banks and financial institutions to adopt more stringent frameworks for NPL management. Governments and regulatory bodies worldwide are mandating stricter controls and reporting mechanisms to ensure financial stability and transparency. This regulatory environment acts as a catalyst for the adoption of sophisticated NPL management software and services, contributing to market growth.

Technological advancements in data analytics, artificial intelligence, and machine learning are revolutionizing the NPL management market. These technologies enable more accurate risk assessments, predictive analytics, and automated processes, significantly enhancing the efficiency and effectiveness of NPL management. By leveraging advanced technologies, financial institutions can better forecast defaults, optimize recovery strategies, and improve overall decision-making processes.

Regionally, the market dynamics vary significantly. North America and Europe are the dominant regions, with a high adoption rate of advanced financial technologies and stringent regulatory frameworks. Meanwhile, the Asia Pacific region is witnessing rapid growth due to the expanding banking sector and increasing NPL volumes in emerging economies such as India and China. These regional differences highlight the need for tailored solutions to meet specific market demands and regulatory requirements.

Solution Type Analysis

The NPL Management market is segmented by solution types, including Debt Collection Software, Risk Management Software, Analytics and Reporting Tools, and Others. Debt Collection Software is a critical component, enabling institutions to streamline and automate the collections process. This software helps in tracking overdue accounts, managing communications with debtors, and ensuring compliance with regulatory requirements. The importance of efficient debt collection cannot be overstated, as it directly impacts the financial health of institutions by improving recovery rates and reducing the burden of bad debts.

Risk Management Software plays a pivotal role in identifying, assessing, and mitigating the risks associated with non-performing loans. This software uses advanced algorithms and data analytics to predict default probabilities, evaluate borrower creditworthiness, and devise proactive strategies to minimize losses. By providing a comprehensive view of risk exposure, this software helps financial institutions make informed decisions and implement effective risk mitigation measures.

Analytics and Reporting Tools are essential for providing insights into NPL portfolios. These tools enable the aggregation and analysis of vast amounts of data to generate detailed reports on loan performance, recovery rates, and other key metrics. By offering granular insights, these tools help institutions identify trends, track progress, and make data-driven decisions to enhance NPL management strategies. The ability to generate customized reports also ensures that institutions meet regulatory reporting requirements efficiently.

Other solutions in the NPL management market include specialized software for loan restructuring, asset valuation, and legal case management. These solutions cater to specific aspects of NPL management, providing targeted functionalities to address unique challenges. For example, loan restructuring software helps in renegotiating loan terms to make them more manageable for borrowers, while asset valuation tools assist in determining the fair market value of collateral assets.

Repor

New York-Northern New Jersey-Long Island, NY-NJ-PA, was the metropolitan area with the highest value of distressed industrial and logistics real estate debt in the United States in April 2023. Distressed real estate loans, or the amount of debt which was delinquent or in special servicing, was ***** million U.S. dollars. The industrial and logistics real estate sector has benefitted notably from the growth in e-commerce and the increasing importance in securing supply chains since the beginning of the pandemic. Unsurprisingly, it had delinquency rate lower than any other commercial real estate sector in 2023.

The delinquency ratio for household loans in South Korea stood at *** percent in 2023. The delinquency ratio dropped from *** percent in 2013 to *** percent in 2023.