New Zealand
New Zealand New Zealand
Consumers make most of their payments by internet banking
  • 74%
  • 70.5%
  • 54.5%
  • 46.5%
  • 39.6%
  • 40.7%
  • 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
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
Consumers that encountered most fraud incidents in the past 12 months

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
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
Consumers encountered most fraud incidents in retail and telco during the past 12 months
  • 55%
  • 54.5%
  • 32.8%
  • 35.2%
  • 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
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 as standalone
Consumers have the largest number of shopping app accounts in the region
  • 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
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
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

How data is helping disadvantaged Australians access credit

How data is helping disadvantaged Australians access credit

Andrew Black, Managing Director of Experian A/NZ


“Without a fridge, you can’t store fresh food. Without textbooks, kids can be left behind at school. And if you can’t afford to fix your car, even travelling to work can be a real struggle.” These are the words of Lisa Carroll, Chief Operating Officer at Good Shepherd Microfinance, a social enterprise striving to reach one million Australians with safe, fair and affordable finance options. Because, as Carroll notes, “too many people living on low incomes experience additional financial stress after resorting to finance options like renting appliances and furniture and high cost loans.”


Good Shepherd Microfinance offers fair credit solutions to Australia’s most financially disadvantaged communities to prevent them from turning to high cost finance options that further detriment their wellbeing. Whilst the work of Good Shepherd Microfinance, and other not-for-profits, is making a tangible impact on the lives of disadvantaged communities across the country, there is a piece of the puzzle that has long been missing: namely, how can companies find out exactly who needs their services most?


It’s the next step up from generic market research: who will benefit most from what we have to offer? How can we communicate with these people? Have we overlooked someone in need? The answers lie in big data.


Data for demonstrated progress

There are more mobile phones in Australia than there are people. And while that doesn’t necessarily mean that every person has a smartphone, it is only one indicator of the enormous troves of data floating about the country. In fact, Experian is a company entrusted with over 15 million consumers’ personal data in Australia, and one billion worldwide. Our Mosaic tool lets companies combine their own customer insights with next-level detail into consumers across the country. It classifies the whole Australian population and allows segmentation not just at mesh block level, but right down to individual households. With access to valuable information like this, not-for-profits and governments alike could be putting this intel to good use.


While applied data analytics techniques have long been utilised by banks to understand ATM use, or by major retailers to predict store demand and supply, the push to use data profiling for the betterment of society is rife with opportunity.


It’s not just local communities benefiting either. Overseas, detailed data modelling is being used to eradicate poverty, improve child welfare, impact climate change, respond to natural disasters, address water crises, understand hospital admission trends and even proffer alternative improvements to counterterrorism efforts. Many of these initiatives employ detailed geographic data analysis, anonymised mobile phone records (CDRs) and even satellite data.


Back home, Good Shepherd Microfinance partnered with Experian to overlay its own information with insights from Mosaic, also integrating postcode-specific data with regional characteristics such as home ownership rates and socio-economic status. This comprehensive customer profile was merged using leading demographic targeting and geographic profiling tools to better predict where Good Shepherd Microfinance’s services would be most valuable. This enriched the understanding of funding versus demand for microfinance in the population, and as a result, Good Shepherd Microfinance can offer its fair and affordable financial programs to up to 20% more people.


Impacting financial literacy across Australia

Experian’s pro-bono work revealed that one in five households could use the Good Shepherd Microfinance No Interest Loan Scheme (NILS) to help avoid financial hardship. The Northern Territory was most in need (37 per cent), with South Australia and Queensland (30 per cent) in pursuit. As a result of the data analytics work undertaken by Experian, Good Shepherd Microfinance is “using these insights to help identify local communities that need programs like our No Interest Loan Scheme (NILS) so we can reach more people,” Carroll said.


But a major benefit of this work has also been the potential for its use in other financial inclusion efforts. In other words, the insights gained aren’t solely valuable to Good Shepherd Microfinance NILS offering. For example, the data revealed that The Murray Mallee region in South Australia, Outer Gippsland in Victoria and the region outside Darwin stood out as having the poorest access to microfinance. Access also varied significantly across the metropolitan areas of major cities.


This information is vital in terms of dictating opportunities for government and other not-for-profits to step in and lend a helping hand in new ways – with greater confidence that they’re impacting the right people, right from the outset.


To learn more about our work with Good Shepherd Microfinance, please click through to our animation.

Read full article

Andrew Black

By Andrew Black 03/08/2018

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