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Sample Report_Europe Buy Now Pay Later Industry and Trends 2021_by yStats.comyStats.com
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Sample Report_Global Blockchain and Cryptocurrency Market 2021_by yStats.comyStats.com
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Sample Report_Europe Buy Now Pay Later Industry and Trends 2021_by yStats.comyStats.com
-What is the Share of Consumers Who Would Like BNPL Added to the Credit Card or Current Account?
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Sample Report: 2021 Key Trends of the Payment Industry: Global Real-Time Paym...yStats.com
- What is the share of daily Real-Time Payments via the Bankgirot System in Sweden?
- What are the top reasons for using real-time payments for corporate decision-makers in the USA?
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- How did the payments via the real-time gross settlement system change during the COVID-19 in Chile?
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Sample Report_Global Buy Now Pay Later Industry and Trends 2021_by yStats.comyStats.com
-What are the Buy Now Pay Later Trends and Benefits for Merchants in 2021?
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- Which technologies are most relevant for B2B payments and how are they transforming the industry?
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Sample Report_Global B2B Payment Market and Trends 2021_by yStats.comyStats.com
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Sample Report: Global Online Payment Methods: First Half 2016yStats.com
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Sample Report_Global Subscriptions and Recurring Payments Market 2021_by ySta...yStats.com
-What are the Top E-Commerce Subscriptions Business Models globally?
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Sample Report_Global Online Payment Methods 2021 Post COVID-19_by yStats.comyStats.com
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Empowering the Data Analytics Ecosystem: A Laser Focus on Value
The data analytics ecosystem thrives when every component functions at its peak, unlocking the true potential of data. Here's a laser focus on key areas for an empowered ecosystem:
1. Democratize Access, Not Data:
Granular Access Controls: Provide users with self-service tools tailored to their specific needs, preventing data overload and misuse.
Data Catalogs: Implement robust data catalogs for easy discovery and understanding of available data sources.
2. Foster Collaboration with Clear Roles:
Data Mesh Architecture: Break down data silos by creating a distributed data ownership model with clear ownership and responsibilities.
Collaborative Workspaces: Utilize interactive platforms where data scientists, analysts, and domain experts can work seamlessly together.
3. Leverage Advanced Analytics Strategically:
AI-powered Automation: Automate repetitive tasks like data cleaning and feature engineering, freeing up data talent for higher-level analysis.
Right-Tool Selection: Strategically choose the most effective advanced analytics techniques (e.g., AI, ML) based on specific business problems.
4. Prioritize Data Quality with Automation:
Automated Data Validation: Implement automated data quality checks to identify and rectify errors at the source, minimizing downstream issues.
Data Lineage Tracking: Track the flow of data throughout the ecosystem, ensuring transparency and facilitating root cause analysis for errors.
5. Cultivate a Data-Driven Mindset:
Metrics-Driven Performance Management: Align KPIs and performance metrics with data-driven insights to ensure actionable decision making.
Data Storytelling Workshops: Equip stakeholders with the skills to translate complex data findings into compelling narratives that drive action.
Benefits of a Precise Ecosystem:
Sharpened Focus: Precise access and clear roles ensure everyone works with the most relevant data, maximizing efficiency.
Actionable Insights: Strategic analytics and automated quality checks lead to more reliable and actionable data insights.
Continuous Improvement: Data-driven performance management fosters a culture of learning and continuous improvement.
Sustainable Growth: Empowered by data, organizations can make informed decisions to drive sustainable growth and innovation.
By focusing on these precise actions, organizations can create an empowered data analytics ecosystem that delivers real value by driving data-driven decisions and maximizing the return on their data investment.
Explore our comprehensive data analysis project presentation on predicting product ad campaign performance. Learn how data-driven insights can optimize your marketing strategies and enhance campaign effectiveness. Perfect for professionals and students looking to understand the power of data analysis in advertising. for more details visit: https://bostoninstituteofanalytics.org/data-science-and-artificial-intelligence/
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
4. 4
GENERAL METHODOLOGY OF MARKET REPORTS
Secondary Market Research
The reports are compiled based on secondary market research. Secondary research is information gathered from previously published sources. Our reports are
based on information and data acquired from national and international statistical offices, industry and trade associations, business reports, business and
company databases, journals, company registries, news portals and many other reliable sources. By using various sources we ensure maximum objectivity for
reported data. As a result, companies gain a precise and unbiased impression of the market situation.
Cross referencing of data is conducted in order to ensure validity and reliability.
The source of information and its release date are provided on every chart. It is possible that the information contained in one chart is derived from several
sources. If this is the case, all sources are mentioned on the chart.
The reports include mainly data from the last 12 months prior to the date of report publication. Exact publication dates are mentioned in every chart.
Definitions
A list of definitions is provided at the beginning of this market report. As definitions may vary among sources, exact definition used by the source (if available) is
included at the bottom of the chart.
Chart Types
Our reports include text charts, pie charts, bar charts, rankings, line graphs and tables. Every chart contains an Action Title, which summarizes the main
idea/finding of the chart and a Subtitle, which provides necessary information about the country, the topic, units or measures of currency, and the applicable time
period(s) to which the data refers. With respect to rankings, it is possible that the summation of all categories amounts to more than 100%. In this case, multiple
answers were possible, which is noted at the bottom of the chart.
Report Structure
Reports are comprised of the following elements, in the following order: Cover page, preface, legal notice, methodology, definitions, table of contents,
management summary (summarizing main information contained in each section of report) and report content (divided into sections and chapters). When
available, we also include forecasts in our report content. These forecasts are not our own; they are published by reliable sources. Within Global and Regional
reports, we include all major developed and emerging markets, ranked in order of importance by using evaluative criteria such as sales figures.
Notes and Currency Values
If available, additional information about the data collection, for example the time of survey and number of people surveyed, is provided in the form of a note. In
some cases, the note (also) contains additional information needed to fully understand the contents of the respective data.
When providing information about amounts of money, local currencies are most often used. When referencing currency values in the Action Title, the EUR
values are also provided in brackets. The conversions are made using the average currency exchange rate for the respective time period. Should the currency
figure be in the future, the average exchange rate of the past 12 months is used.
5. 5
METHODOLOGY OF THE CURRENT REPORT
Report Coverage
This report covers the global Open Banking. In this report, Open Banking is defined as a banking practice that provides third-party financial service providers
open access to consumer banking, transaction, and other financial data from banks and non-bank financial institutions through the use of application
programming interfaces (APIs). The report offers insights into the state of Open Banking in different regions across the globe, recent and possible future
developments, consumer preferences, regulatory requirements and more.
In addition to the global data, major global regions in worldwide Open Banking were covered in the report, including Europe, Asia-Pacific, North America, Latin
America and the Middle East. Open Banking itself and data availability therefore varied by region and country.
Report Structure
The report opens with a global chapter. It includes information on the global Open Banking market developments and projections, top market trends and market
players’ and consumers’ preferences.
The rest of the report is divided by regions, with each regional section containing county chapters and/or regional information, where available. The regions and
countries are ranked by the state of Open Banking market development and includes related data points, such as the status of Open Banking legislation, service
providers, consumer attitude and other.
Depending on data availability, the following types of information were included: overview of Open Banking market drivers, state of development, regulations,
Open Banking number of users and market values. Not all types of data mentioned were included for each section due to varying information availability.
6. 6
DEFINITIONS
Open Banking (OB)
A banking practice that provides third-party financial service providers open access to consumer banking, transaction,
and other financial data from banks and non-bank financial institutions through the use of application programming
interfaces (APIs).
Revised Payment Services
Directive (PSD2)
An EU Directive, administered by the European Commission to regulate payment services and payment service
providers throughout the European Union and European Economic Area.
Application Programming
Interface (API)
A set of functions and procedures allowing the creation of applications that access the features or data of an operating
system, application, or other service.
Third-Party Providers (TPPs) An external person or company who provides a service or technology as part of a contract
Banking-as-a-Service (BaaS)
Describes a model in which licensed banks integrate their digital banking services directly into the products of other non-
bank businesses.
Know-Your-Customer (KYC)
A standard in the investment industry that ensures investment advisors know detailed information about their clients' risk
tolerance, investment knowledge, and financial position.
Berlin Group Standard
a pan-European payments interoperability standards and harmonization initiative with the primary objective of defining
open and common scheme- and processor-independent standards in the interbanking domain between Creditor Bank
(Acquirer) and Debtor Bank (Issuer), complementing the work carried out by e.g., the European Payments Council. As
such, the Berlin Group has been established as a pure standardization body, focusing on detailed technical and
organizational requirements to achieve this primary objective.
STET framework
STET is a major European Automated Clearing House servicing the payment industry and providing processing services
for SEPA and domestic instruments such as direct debits, credit transfers, cards and ATMs transactions, cheques, bills
of exchange and other.
Open Banking Implementation
Entity (OBIE)
A UK concept, which creates software standards and industry guidelines to drive competition, innovation and
transparency in retail banking.
The following expressions and definitions are used in this market report*:
Note: *the definitions used by the original sources might differ from the ones stated on this chart; the exact definition used by each source, where available, is included on the respective
charts
7. 7
TABLE OF CONTENTS (1 OF 3)
1. Management Summary
2. Global Market Overview
• Number of Cashless Transactions, in billions, by Region, 2020 & 2025f & 2030f
• Countries Where Open Banking Survives are Offered, incl. State of Development, June 2021
• Share of Financial Institutions that Currently Considering/Have Started the Process/Have Opened APIs, in % of Financial
Professionals, 2021
• Open Banking Structural Overview, November 2020
• Key Tenets of Open Banking, January 2021
• Open Banking Market Size Valuation, in USD million, 2020 & 2027f
• Number of Open Banking Users, in millions, 2020 – 2024f
• Share of Consumers Who Do not Use Open Banking, and Who Do not Use Financial Apps, in %, March 2021
• Impact of Open Banking on Organizations, in % of Financial Professionals, June 2021
• Impact of Open Banking on Organizations, in % of Financial Professionals, 2020 & 2021
• Consumer Attitude Toward Data Sharing in Open Banking, in %, March 2021
• Consumer Attitude Toward Banks’ Approach to Offer Open Banking, in %, March 2021
• Reasons to Join Open Banking after the COVID-19 Pandemic, in % of Consumers, March 2021
• Share of Banking Executives Who are Unsure How to Embrace Open Banking and Orchestrate Ecosystem, in %, 2021
• Share of Banking Executives Who are Unsure How to Embrace Open Banking and Orchestrate Ecosystem, in %, 2021
• Open Banking Funding Value, in USD million, 2018 - 2021
• Overview of Service Platforms in Open Banking, incl. Company Examples, April 2021
3. Europe
3.1. Regional
• Countries Ranking by Open Banking Ecosystem Development, June 2021
• Breakdown of Value Propositions of PSD2 Licensed Third-Party Providers’ Types, in %, September 2020
• Number of Third-Party Providers in Open Banking, September 2020 & March 2021 (1 of 2)
• Number of Third-Party Providers in Open Banking, September 2020 & March 2021 (2 of 2)
• Cash Preference for Shopping and Services Payments, in % of Respondents, 2018 & 2020
• General Willingness to Share Data in Exchange for Benefits, in % of Respondents, 2018 & 2020
8. 8
TABLE OF CONTENTS (2 OF 3)
3.2. Advanced Open Banking Markets
3.2.1. United Kingdom
• Overview of the Open Banking Developments, August 2021
• Number of Open Banking Users, in millions, January 2020 & April 2021
• Reasons Why Open Banking was Adopted, in % of Lenders, Q1 2021
• Out of 10 Score Given by Lenders for the Outcome of Using OB for Credit Decisions, and Income & Employment Verification, in %
of Lenders, Q1 2021
3.2.2. Germany
• Overview of the Open Banking Developments, August 2021
• General Willingness to Share Data in Exchange for Benefits Compared to the EU Average, in % of Respondents, September 2020
3.3. Developing Open Banking Markets
3.3.1 Regional
• Overview of the Open Banking System, by Country, incl. Improvements, June 2021
3.3.2. Turkey
• General Willingness to Share Data in Exchange for Benefits, in % of Respondents, 2020
3.3.3. Russia
• Overview of the Open Banking System, August 2021
• Summary of Banks Included in Open Banking, incl. Markets, AIS, and PIS, 2021
4. Asia-Pacific
4.1. Regional
• Overview of the Open Banking System, August 2021
4.2. China
• Summary of Banks Included in Open Banking, incl. Markets, AIS, and PIS, 2021
4.3. India
• Bank Customer Propensity to Share Data, in %, January 2021
9. 9
TABLE OF CONTENTS (3 OF 3)
4. Asia-Pacific (cont.)
4.4. South Korea
• Open Banking Transactions Value, in KRW trillion, 2019 & 2020
• Open Banking Number of Users, and Number of Use Cases, by Financial Institution, March 2021
5. North America
5.1. United States
• Ways Consumers Open New Accounts, by Type of Account, 2020
• Share of Adults Who Know What Open Banking is or Have Heard About It, in %, 2021
• Top Reasons Why Adults Feel that Growing Movement Toward Open Banking is not a Positive Development, in %, 2021
• Share of Adults Who Feel that Growing Movement Toward Open Banking is a Positive Development, in %, 2021
• Share of Adults Who Agree with a Central Principle of Open Banking, in %, 2021
5.2. Canada
• Preferences to Share Data with Big Banks, by Type of Data, in % of Banking Customers, 2021
6. Latin America
6.1. Regional
• Share of Fintech Professionals who Believe that Companies Should Get Ahead of Regulation for Open Finance Implementation, in
%, 2021
• Top Challenges for Open Finance in 2021, in % of Fintech Professionals, 2021
• Fintech Verticals that will Benefit the Most from Open Finance in 2021, in % of Fintech Professionals, 2021
• Value of Fintech Investment Activity, in USD million, and Breakdown of the Number of Deals, in %, by Country, 2020
6.2. Mexico
• Overview of the Open Banking Developments, August 2021
6.3. Brazil
• Overview of the Open Banking Developments, August 2021
7. Middle East and Africa
7.1. Regional
• Overview of the Open Banking System, August 2021
10. 10
1. Management Summary 10 – 13
2. Global 14 – 31
3.
3.1.
3.2.
3.2.1.
3.2.2.
3.3.
3.3.1.
3.3.2
3.3.3
Europe
Regional
Advanced Open Banking Markets
United Kingdom
Germany
Developing Open Banking Markets
Regional
Turkey
Russia
32 – 52
33 – 38
39 – 45
40 – 43
44 – 45
46 – 52
47 – 49
50 – 50
51 – 52
4.
4.1.
4.2.
4.3.
4.4.
Asia-Pacific
Regional
China
India
South Korea
53 – 58
54 – 54
55 – 55
56 – 56
57 – 58
5.
5.1.
5.2.
North America
United States
Canada
59 – 65
60 – 64
65 – 65
6.
6.1.
6.2.
6.3
Latin America
Regional
Mexico
Brazil
66 – 72
67 – 70
71 – 71
72 – 72
7.
7.1
Middle East and Africa
Regional
73 – 74
11. 11
Yes, we are currently
concidering/have started the
process/have opened APIs
78%
Other
22%
4 in 5 (78%) of global financial professionals are looking to use APIs to
drive or enable Open Banking in the next 12 months.
Survey: based on a survey of 785 professionals (at managerial level) at financial institutions and banks across France, Germany, Hong Kong, Singapore, the UAE, the UK and the
US, conducted in 2021; these financial institutions represent a gross total of just over USD 34 billion in turnover over the last 12 months, employ approximately 2.4 million
staff and have approximately 237 million client/customer/member relationships question asked: “What has been the impact of Open Banking for your organization?”
Source: Finastra, June 2021
Global: Share of Financial Institutions that Currently Considering/Have Started the Process/Have Opened
APIs, in % of Financial Professionals, 2021
12. 12
3.71
114.98
0
40
80
120
2019 2020
in
KRW
trillion
+3000%
In South Korea, the value of transactions via Open Banking has surged
since its launch in 2019 to reach KRW 115 trill. (EUR 86 bill.) in 2020.
South Korea: Open Banking Transactions Value, in KRW trillion, 2019 & 2020
Note: exchange rate used in the action title is the average for 2020: KRW 1 = EUR 0.000744
Source: Korea Financial Telecommunication and Clearings Institute, February 2021