The Consumer Complaint Database is a collection of complaints about consumer financial products and services that we sent to companies for response. Complaints are published after the company responds, confirming a commercial relationship with the consumer, or after 15 days, whichever comes first. Complaints referred to other regulators, such as complaints about depository institutions with less than $10 billion in assets, are not published in the Consumer Complaint Database. The database generally updates daily.

These are complaints we’ve received about financial products and services.

Context

Understanding factors that support consumer financial well-being can help practitioners and policymakers empower more families to lead better financial lives to serve their own goals.

A person’s financial well-being comes from their sense of financial security and freedom of choice—both in the present and when considering the future. We measured it using our 10-item Financial Well-Being Scale.

The survey dataset includes respondents’ scores on that scale, as well as measures of individual and household characteristics that research suggests may influence adults’ financial well-being.

Content

Variables relating to question in this dataset include Income and employment, Savings and safety nets, Past financial experiences, and Financial behaviors, skills, and attitudes.

For reference on specific fields, a codebook is available online here.

Acknowledgements

This survey was originally conducted by the US Consumer Finance Protection Bureau and published online in October 2017 here.

As required by the Credit CARD Act of 2009, we collect information annually from credit card issuers who have marketing agreements with universities, colleges, or affiliated organizations such as alumni associations, sororities, fraternities, and foundations.

The Credit Card Agreements (CCA) database includes credit card agreements from more than 600 card issuers. These agreements include general terms and conditions, pricing, and fee information and are collected quarterly pursuant to requirements in the CARD Act.

This dataset provides access to data about general purpose credit cards, which are open-end loans used by consumers to pay for day-to-day expenses, finance purchases, or provide cash advances.

The 2017 National Financial Well-Being in America Survey, conducted for the CFPB Offices of Financial Education and Financial Protection for Older Americans, was an online survey conducted to measure the financial well-being of adults in the United States. These data were created as a foundation for internal and external research into financial well-being and are relevant to work being done by researchers in the Office of Research who have access to the (deidentified) data.

HMDA requires many Financial Institutions (FI)s to maintain, report, and publicly disclose information about applications for and originations of mortgage loans. HMDA s purposes are to provide the public and public officials with sufficient information to enable them to determine whether institutions are serving the housing needs of the communities and neighborhoods in which they are located, to assist public officials in distributing public sector investments in a manner designed to improve the private investment environment, and to assist in identifying possible discriminatory lending patterns and enforcing antidiscrimination statutes. This publicly-available data asset contains HMDA data collected in or after 2017 and has been modified to protect the privacy of individuals whose information is present in the dataset.

The Home Mortgage Disclosure Act (HMDA) requires many financial institutions to maintain, report, and publicly disclose information about mortgages

The Home Mortgage Disclosure Act (HMDA) database (Consumer Financial Protection Bureau, 2022) has compiled mortgage lending data since 1981, but the collection and dissemination methods have changed over time (Federal Financial Institutions Examination Council, 2018), creating barriers to conducting longitudinal analyses. This HMDA Longitudinal Dataset (HLD) organizes and standardizes information across different eras of HMDA data collection between 1981 and 2021, enabling such analysis. This collection contains two types of datasets: 1) HMDA aggregated data by census tract for each decade and 2) HMDA aggregated data by census tract for individual years. Items for analysis include borrower income values, mortgages by loan type (e.g., conventional, Federal Housing Administration (FHA), Veterans Affairs (VA), refinances), and mortgages by borrower race and gender.

Abstract

The 2017 Global FICP Survey tracks the prevalence of key policy, legal, regulatory, and supervisory efforts to advance financial inclusion and financial consumer protection, including: national financial inclusion strategies, nonbank e-money issuers, agent-based delivery models, simplified customer due diligence, legal frameworks and institutional arrangements for financial consumer protection, disclosure and transparency, fair treatment of consumers, dispute resolution, and financial capability. Financial sector authorities in 124 jurisdictions responded to the 2017 Global FICP Survey. The survey covers regulated financial service providers offering retail credit, deposit, and/or payment products and services. The reporting period was from November 2016 to June 2017.

Geographic coverage

The 2017 Global FICP Survey includes responses from 124 jurisdictions, representing 141 economies and over 90 percent of the world’s unbanked adult population.

Analysis unit

• Jurisdiction as defined by the remit of a financial sector authority.
• Country

Universe

Surveys were sent primarily to central banks and other lead financial sector authorities, and respondents were asked to consult with relevant agencies and submit a joint response.

Kind of data

Event/Transaction data [evn]

Mode of data collection

Internet [int]

Research instrument

The 2017 questionnaire covers selected issues within the following subtopics: - National Financial Inclusion Strategies (NFIS), - regulation and supervision of providers relevant to financial inclusion, - risk-based anti-money laundering and combating finnancing of terrorism (AML/CFT), - institutional and supervisory arrangements for financial consumer protection, - disclosure and transparency, - fair treatment, - dispute resolution, and financial capability.

The survey was conducted in English.

Abstract

The purpose of the SEPHER data set is to allow for testing, assessing and generating new analysis and metrics that can address inequalities and climate injustice. The data set was created by Tedesco, M., C. Hultquist, S. E. Char, C. Constantinides, T. Galjanic, and A. D. Sinha.

Methodology

SEPHER draws upon four major source datasets: CDC Social Vulnerability Index, FEMA National Risk Index, Home Mortgage Disclosure Act, and Evictions datasets. The data from these source datasets have been merged, cleaned, and standardized and all of the variables documented in the data dictionary.

CDC Social Vulnerability Index

CDC Social Vulnerability Index (SVI) dataset is a dataset prepared for the Centers for Disease Control and Prevention for the purpose of assessing the degree of social vulnerability of American communities to natural hazards and anthropogenic events. It contains data on 15 social factors taken or derived from Census reports as well as rankings of each tract based on these individual factors, groups of factors corresponding to four related themes (Socioeconomic, Household Composition & Disability, Minority Status & Language, and Housing Type & Transportation) and overall. The data is available for the years 2000, 2010, 2014, 2016, and 2018.

FEMA National Risk Index

The National Risk Index (NRI) dataset compiled by the Federal Emergency Management Agency (FEMA) consists of historic natural disaster data from across the United States at a tract-level. The dataset includes information about 18 natural disasters including earthquakes, tsunamis, wildfires, volcanic activity and many others. Each disaster is detailed out in terms of its frequency, historic impact, potential exposure, expected annual loss and associated risk. The dataset also includes some summary variables for each tract including the total expected loss in terms of building loss, human loss and agricultural loss, the population of the tract, and the area covered by the tract. It finally includes a few more features to characterize the population such as social vulnerability rating and community resilience.

Home Mortgage Disclosure Act

The Home Mortgage Disclosure Act (HMDA) dataset contains loan-level data for home mortgages including information on applications, denials, approvals, and institution purchases. It is managed and expanded annually by the Consumer Financial Protection Bureau based on the data collected from financial institutions. The dataset is used by public officials to make decisions and policies, uncover lending patterns and discrimination among mortgage applicants, and investigate if lenders are serving the housing needs of the communities. It covers the period from 2007 to 2017.

Evictions

The Evictions dataset is compiled and managed by the Eviction Lab at Princeton University and consists of court records related to eviction cases in the United States between 2000 and 2016. Its purpose is to estimate the prevalence of court-ordered evictions and compare eviction rates among states, counties, cities, and neighborhoods. Besides information on eviction filings and judgments, the dataset includes socioeconomic and real estate data for each tract including race/ethnic origin, household income, poverty rate, property value, median gross rent, rent burden, and others.

K-12 schools are increasingly offering families the option to pay school-related expenses online via third-party payment processors, presenting new costs and challenges for users.

Dataset contains the reason for home mortgage applications denials in LA City disaggregated by race. Data pulled from the Consumer Financial Protection Bureau, collected by the Home Mortgage Disclosure Act, which requires many financial institutions to maintain, report, and publicly disclose information about mortgages.

The data displayed in this theme of the Florida’s Roadmap to Living Healthy are quantitative measures that present the economic condition of Florida’s communities. The data sets contained in this themed map provide the business community and policymakers with relevant and useful statistics needed to make informed decisions to positively affect Florida’s economy. The Florida Department of Agriculture and Consumer Services has used the most current economic statistics from trusted sources such as the United States Census Bureau, U.S. Department of Labor Bureau of Labor Statistics, Consumer Financial Protection Bureau, U.S. Department of the Treasury Community Development Financial Institutions Fund, Social Security Administration, Florida Department of Children and Families, CareerSource Florida, and Esri to build this custom visualization. The economic data used for this themed map includes topics, such as unemployment rates, rural and underserved communities, New Market Tax Credits (NMTC), poverty indicators, career centers, and other related topics. The economic data shown in this themed map is useful for data-driven planning and decision making at the local and state level that could influence growth in various economic sectors.For technical assistance, contact Ronnie Blanco at ronaldo.blanco@freshfromflorida.com