New Zealand
New Zealand New Zealand
Consumers make most of their payments by internet banking
  • 74%
    BFSI
  • 70.5%
    TELCO
  • 54.5%
    RETAIL
  • 46.5%
    BFSI
  • 39.6%
    TELCO
  • 40.7%
    RETAIL
  • A higher percentage make payments via internet banking to banks and insurance companies, telcos, and retailers, respectively, compared to the regional average
  • Impact: Anti-fraud capabilities critical to the increased digital transaction frequency and customers’ trust in banks
Australia
Australia Australia
Consumers are most satisfied with the post-fraud service of banks and insurances companies
  • More than 70% satisfaction rate compared to 59.7% on average
  • Impact: Increased trust in BFSIs
Indonesia
Indonesia Indonesia
Consumers that encountered most fraud incidents in the past 12 months
49%
34.7%

AP Average

  • 49.8% have experienced fraud at least once compared to 34.7% on average
  • Impact: Overall anti-fraud capabilities need improvement
Singapore
Singapore Singapore
Consumers have the highest trust towards government
AP Average
  • 75.5% choose government agencies, compared with 51.7% on average
  • Impact: Trust of personal data protection is centered around government agencies
Vietnam
Vietnam Vietnam
Consumers encountered most fraud incidents in retail and telco during the past 12 months
  • 55%
    TELCO
  • 54.5%
    RETAIL
  • 32.8%
    TELCO
  • 35.2%
    RETAIL
  • 55% and 54.5% have experienced fraud at least once in retail and telco, respectively, compared to 32.8% and 35.2% on average
  • Impact: Overall anti-fraud capabilities need improvement
Thailand
Thailand Thailand
Most Thai consumers believe speed and resolution are severely lacking (response/ detection speed toward fraud incidents)
AP Average
  • 60.5% think it is most important, compared to 47.7% on average
  • Impact: Response time as one of key factors to fraud management to retain customers and gain their trust
India
India India as standalone
Consumers have the largest number of shopping app accounts in the region
India
  • Average of three accounts per person
  • Impact: Highest exposure to online fraud
Hong Kong
Hong Kong Hong Kong
The least percentage of consumers with high satisfaction level toward banks and insurance companies’ fraud management
AP Average
  • Only 9.7% are most satisfied compared to 21.1% on average
  • Impact: effective response towards fraud incidents to be improved
China
China China
Consumers are the most tolerant toward submitting and sharing of personal data
AP Average
  • 46.6% compared to the AP average of 27.5% are accepting of sharing personal data of existing accounts with other business entities
  • Impact: higher exposure of data privacy and risk of fraud
alert
Japan Japan as standalone
Consumers most cautious on digital accounts and transactions
50.7% Actively maintain digital accounts’ validity
27% AP Average
45.5% Do not do online bank transfers
13.5% AP Average
  • More than 70% did not encounter fraud incidents in past 12 months, compared to 50% on average
  • Impact: Relatively low risk of fraud

Guide to data quality management

Guide to data quality management

The more data, the better. Today’s organisations are collecting a vast amount of data from all areas of the business. Data is captured through transactions, website navigation, product development, and way more—and that’s just touching the surface. But, what value are all these insights providing your business if they are inaccurate?

 

Introducing: Data quality management. Your cornerstone to managing multiple streams of data, while ensuring high-quality insights are being leveraged for the most important business initiatives.

 

 

What is data management?

Data management is the process of acquiring, validating, storing, protecting, and processing data.

 

While a data management program is crucial to streamlining business insights, data quality becomes its right-hand. Enter: Data quality management.

 

As you start thinking about data quality management, it’s important to review how accurate your information is in each stage of the data management process. Is your data accurate at the point of collection? Are you confident in leveraging the insights found in your current database?

 

An effective data management strategy is crucial for today’s organisations who are looking to stay one step ahead of their competition. When you lay a foundation of data quality, you can empower your business to make better and faster decisions. More importantly, you can leverage that competitive edge as you shift with the everchanging market.

 

 

Why data quality is so important to data management

Data quality is a fundamental component to the success of a data management program. Think about it: How can you or your team effectively manage data that could be inaccurate and untrustworthy? Our research has found that 50 percent of organisations say their data is inaccurate due to human error.

 

What’s more, a complete and trustworthy database gives you confidence that you are leveraging accurate customer insights to drive business opportunity. You can do this through our data validation and data enrichment capabilities.

 

Learn more about data quality solutions

 

 

Top benefits of data quality management

It’s no secret data quality management is a key driver when it comes to successful business outcomes. Organisations across all industries are seeing the benefits of data management, including:

  • Improved customer experience.
  • Better insight for decision-making.
  • Allow for more innovation.
  • And, way more!

 

Data quality management solutions

As you look for the best data quality management solution for your business, it’s important to first consider what tools will be easily adopted by your team, what your business and data goals are, and most importantly, what your budget is like.

 

A well-suited data quality management solution enables you to monitor data in real time, automating your data management practices and ensuring each and every record is reliable. Here are some key functions of a data management software:

  • Data profiling and discovery
  • Data enrichment
  • Data standardisation
  • Data monitoring

Best practices for data management

 

As your organisation begins to adopt data management practices, it’s important to remember that managing data should be an ongoing discipline. Let’s dive into the best practices:

  1. Start with data quality.
  2. Build in data governance.
  3. Hire a CDO.
  4. Democratise data.
  5. Teach data skills.

Empower your business to adopt data management through these best practices. Before you know it, your data will be used across the entire enterprise to make better decisions, streamline operations, and improve customer experience, all while watching your bottom-line growth take off.

 

Experian can help you take your data to the next level with our best-in-class data quality management solution.

Read full article

Jordyn Tetler

By Jordyn Tetler 03/04/2021

Related Articles

Global Insights Report – Wave 3
Global Insights Report – Wave 3

In this third report in a longitudinal study, we continue our examination of consumer behaviour and business strategy throughout the pandemic. In January 2021 we surveyed 3,000 consumers and 900…

Learn more
Accelerating recovery with digital transformation
Accelerating recovery with digital transformation

The Covid-19 pandemic created a seismic shift in the volume of online activity and experience. Over the past 12 months we've observed consumer demand for the digital channel increase at…

Learn more
Announcing: Experian’s data quality integration with Salesforce Lightning
Announcing: Experian’s data quality integration with Salesforce Lightning

We are very excited to announce that Experian has integrated our real-time contact data verification software into Salesforce Lightning.

Learn more

  • Submit
By providing your personal information you agree that we may collect and process it in accordance with our Privacy Statement.