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

5 questions to consider when improving data quality

5 questions to consider when improving data quality

Improving data quality could be the most important aspect of your data management strategy; however, you’ll rarely see it at the top of the Board’s agenda. Crucially though, all processes, decisions and outcomes the Board makes are based on the data your organisation holds and, if that data is inaccurate, then the downstream impact on critical differentiators like customer experience, can be costly, both from a resource and expense perspective.

 

Conversely, organisations with better data can explore a wealth of insight-led opportunities over their competitors.

 

In this article, we lay out five questions to consider when thinking about data quality improvements.

 

1. What is your data requirement?

 

Are you collecting the data you need? It’s one thing not collecting the right information, it’s another to collect data that you do not actually need. Collecting more data could simply mean there’s more to manage and more opportunities for inaccuracies. Take webforms for example, many have preset capture fields out-of-the-box, so spend the time to decide what data you really need and how valuable it is to you. You should also consider how you securely store and manage any personal and sensitive data that you collect.

 

It’s worth reviewing your processes and ascertaining what data elements are required to run your organisation or build valuable insights and no longer collect the rest. Don’t forget, you can always append enrichment data later on if you need it. More on that later.

 

2. How do you capture data?

 

Typically, first party data is captured in two ways. The first is digital web forms, most commonly on your website, and the second is via call centre staff or other employees.

 

Both methods are subject to purposeful and accidental misinformation. Some typical examples are detailed below.

 

We have all entered invalid data on a webform, normally due to wariness about how the data will be used by the recipient. We enter the basic amount to achieve our goals with little concern for the quality of the rest.

 

Likewise, we have all provided personal information to call centre staff over the phone only for at some later date an irregularity or issue to surface (often details presented incorrectly in an official letter).

 

However, there is a lot that can be done these days to monitor data entering your business. Be that validation checks of digital web form data or profiling data collected in your call centres. If you have no measures in place to understand the accuracy of the data at point of capture then it is something worth addressing. If you are measuring the quality levels and your data repeatedly falls beneath your thresholds, then explore whether the data you are collecting is susceptible to inaccuracies.

 

3. How accurate is the data you already hold?

 

If you cannot answer this question then you should act fast, as your organisation currently interacts with customers, and makes decisions, based on this data.

 

We discussed profiling your data earlier, and this, combined with a better data collection methodology will go the furthest to improving the health of your data as you’re fixing many of the issues ‘upstream’.

 

You could also look to cleanse the data you already hold. For example, 17% of Australians move house every year, so regular cleansing of your data can help you keep on top of these constant changes.

 

A common issue in many organisations is duplicate contact records. Even with data monitoring in place, duplicates can still sneak through as everyone tends to mix use of email addresses and other identifiable information. To deal with historic duplicate challenges a more robust matching exercise may be called for to help create that single view golden record. The downstream impact of poor data quality can affect all aspects of your business and create a huge amount of manual correction work.

 

4. Can you add insights from third party data providers?

 

There is a limit to the amount of data you can collect from your clients simply due to the fact it will be deemed invasive, or they simply will not know the answers you are seeking.

 

Official sources of data can be an invaluable resource when profiling and segmenting your customer base.

 

There are a wealth of data sources available, as well as numerous data files made accessible by the government that can help you append crucial insights to your existing portfolio.

 

Working with accredited third parties, such as Experian, is another great way to enrich your data. We can add demographic and behavioural information that will help you interact, target and delight your customers.

 

5. How connected are your systems?

 

A common cause of data error is from the movement of data through your business. Often moving data between systems is a manual effort which, as we have discussed, is prone to human error. Improve automated ‘data flows’, and you improve the quality of the information you hold in multiple places.

 

Connecting internal systems is becoming common practice to ensure the integrity of data moving through your organisation. For example, having your CRM system speak directly to your BI instance will ensure there is a single source of truth and that multiple systems are using the same source data points.

 

Experian has a range of integration tools that work at the point of data capture to ensure your data flows through your organisation seamlessly.

 

Don’t underestimate the importance of data quality

 

It’s easy to push data quality initiatives down the pecking order due to other business priorities and limited understanding about how important it really is.

 

As we’ve discussed in this article, the downstream impact of poor data quality can affect your customer relationships, your decision making and your ability to grow.

 

Get data quality right and you could unlock a wealth of opportunities for your organisation and power your decision making going forward.

 

If you’d like to discuss your data quality initiative, then please get in touch.

Read full article

Experian

By Experian 02/01/2021

Related Articles

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
Email validation best practices
Email validation best practices

Email has been around for decades—and the channel has aged quite nicely. With billions of users per day, email is a great way to connect with consumers on-the-go, at work,…

Learn more
Data quality steps and techniques
Data quality steps and techniques

Clear data means clear business objectives—that should be the goal when it comes to your database.

Learn more

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