The credit card penetration in Canada was forecast to continuously increase between 2024 and 2029 by in total 1.4 percentage points. After the seventh consecutive increasing year, the credit card penetration is estimated to reach 84.55 percent and therefore a new peak in 2029. The penetration rate refers to the share of the total population who use credit cards.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the credit card penetration in countries like United States and Mexico.

The credit card penetration in the United States was forecast to continuously increase between 2024 and 2029 by in total *** percentage points. After the seventh consecutive increasing year, the credit card penetration is estimated to reach ***** percent and therefore a new peak in 2029. The penetration rate refers to the share of the total population who use credit cards.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to *** countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the credit card penetration in countries like Canada and Mexico.

Forecast: Number of Payments by Cards with a Credit Function in Canada 2022 - 2026 Discover more data with ReportLinker!

Introduction

This Canadian French Call Center Speech Dataset for the BFSI (Banking, Financial Services, and Insurance) sector is purpose-built to accelerate the development of speech recognition, spoken language understanding, and conversational AI systems tailored for French-speaking customers. Featuring over 30 hours of real-world, unscripted audio, it offers authentic customer-agent interactions across a range of BFSI services to train robust and domain-aware ASR models.

Curated by FutureBeeAI, this dataset empowers voice AI developers, financial technology teams, and NLP researchers to build high-accuracy, production-ready models across BFSI customer service scenarios.

Speech Data

The dataset contains 30 hours of dual-channel call center recordings between native Canadian French speakers. Captured in realistic financial support settings, these conversations span diverse BFSI topics from loan enquiries and card disputes to insurance claims and investment options, providing deep contextual coverage for model training and evaluation.

Topic Diversity

This speech corpus includes both inbound and outbound calls with varied conversational outcomes like positive, negative, and neutral, ensuring real-world BFSI voice coverage.

This variety ensures models trained on the dataset are equipped to handle complex financial dialogues with contextual accuracy.

Transcription

All audio files are accompanied by manually curated, time-coded verbatim transcriptions in JSON format.

These transcriptions are production-ready, making financial domain model training faster and more accurate.

Metadata

Rich metadata is available for each participant and conversation:

Introduction

This Canadian English Call Center Speech Dataset for the BFSI (Banking, Financial Services, and Insurance) sector is purpose-built to accelerate the development of speech recognition, spoken language understanding, and conversational AI systems tailored for English-speaking customers. Featuring over 30 hours of real-world, unscripted audio, it offers authentic customer-agent interactions across a range of BFSI services to train robust and domain-aware ASR models.

Curated by FutureBeeAI, this dataset empowers voice AI developers, financial technology teams, and NLP researchers to build high-accuracy, production-ready models across BFSI customer service scenarios.

Speech Data

The dataset contains 30 hours of dual-channel call center recordings between native Canadian English speakers. Captured in realistic financial support settings, these conversations span diverse BFSI topics from loan enquiries and card disputes to insurance claims and investment options, providing deep contextual coverage for model training and evaluation.

Topic Diversity

This speech corpus includes both inbound and outbound calls with varied conversational outcomes like positive, negative, and neutral, ensuring real-world BFSI voice coverage.

This variety ensures models trained on the dataset are equipped to handle complex financial dialogues with contextual accuracy.

Transcription

All audio files are accompanied by manually curated, time-coded verbatim transcriptions in JSON format.

These transcriptions are production-ready, making financial domain model training faster and more accurate.

Metadata

Rich metadata is available for each participant and conversation:

From 1990-1995, National Angus Reid Polls measure the opinions of Canadians on topics such as politics and current events. The Ipsos-Reid, National Angus Reid Poll, October 1992 [Canada] focuses on the Charlottetown agreement, the economy, use of force, credit cards, electric and magnetic fields, energy, and new vehicles. This dataset is part of the Ipsos Canadian Public Affairs Data Collection archived at Wilfrid Laurier University Archives and Special Collections. The original record is at https://libarchives.wlu.ca/index.php/national-angus-reid-poll-october-1992 This dataset contains the original SPSS data file in a number of formats and an accompanying codebook/data dictionary.

The Energy, Mines and Resources (EMR) Library owns over 100,000 aerial photographs of the Yukon. You can photocopy or scan (600x600 dpi) aerial photographs in the library. If you wish to scan aerial photos, please bring a new, unformatted USB flash drive. Photocopies are limited to 25 per client, per day. Scanning is unlimited. You can borrow aerial photographs overnight. You must leave your credit card (Visa, MasterCard, or American Express) information with the library's staff as security. The EMR Library catalogue also lists aerial photographs held by Highways and Public Works (HPW). To access HPW's aerial photographs, contact the EMR Library. Phone 867-667-3111 or email emrlibrary@yukon.ca. Many aerial photographs have been scanned and are now available on GeoYukon. For more information on using GeoYukon, contact the EMR Library at 867-667-3111 or email emrlibrary@yukon.ca.