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

Unlocking the Power of Data for a Better Future – Insights From Singapore Fintech Festival 2018

Unlocking the Power of Data for a Better Future – Insights From Singapore Fintech Festival 2018

James Coffey, Head of Channels and Alliances, South East Asia, and Gaurav Kumar, Head of Data Labs, Asia Pacific speaking on “Embedded Machine Learning in the New Age Products” at the Singapore Fintech Festival 2018


A staggering 2.5 quintillion bytes of data is produced each day. Today, some ninety percent of the world’s data is thought to have been generated in just the last two years. Whether online or offline, rural or urban, our digital-first world has given rise to a vast number of touchpoints - each yielding large amounts of data which form the backbone for strategic decision making for organisations.


However, as the world digitalises, how can these companies boost their ability to process even more amounts of data, and what are some of the use cases of big data beyond consumer insights?


These were among the topics addressed by Experian’s James Coffey, Head of Channels and Alliances, South East Asia, and Gaurav Kumar, Head of Data Labs, Asia Pacific at the 2018 Singapore Fintech Festival, the world’s largest fintech event.


Speaking to a packed room, James and Gaurav shared insights on how emerging technologies such as Machine Learning and Artificial Intelligence could help organisations boost their data analysis capabilities. The session also covered details on how data-driven solutions created at Experian are making a difference in the lives of consumers in Asia Pacific.


Innovative Answers for Complex Problems

The sheer amount of data modern organisations face each day can be challenging. This is an obstacle that Experian’s DataLabs, a research facility with offices all around the world, is working tirelessly to overcome with technology. The DataLabs aids in the creation of innovative solutions characterised by a unique blend of best in class data, advanced analytics and digital decision strategies, allowing for more effective management of big data scenarios.


Experian also collaborates with start-ups, lending its technology and resources to enable complementary firms to scale more efficiently or deliver better services. Aside from these partnerships, Experian is formulating a Venture Program focused on growth stage minority investment opportunities and a ‘service for equity’ program designed to give start-ups access to Experian services in exchange for equity.


Machine Learning – Why it Matters for Big Data

While it might be daunting to think that Machine Learning provides computers with the ability to learn without being explicitly programmed to do so, when implemented correctly, the automation enabled by Machine Learning is a highly effective tool that vastly enhances the capability of human teams to process massive amounts of data. At Experian, we believe in the potential to harness this technology to make a positive difference in the lives of billions of consumers across Asia Pacific.


Data processing models augmented with Machine Learning capabilities have proven to have strong predictive power, being able to process non-standard data sources for more optimal results.


Use cases benefitting from this include fraud detection, delivery of personalised and targeted product recommendations, and risk score analysis on a national and regional scale. On average, Machine Learning has delivered 20 per cent more accuracy in preventing fraud for Experian. In addition, the combination of different models that Experian deploys has reduced false positives significantly: 80 per cent of valid transactions that traditional models reject as fraud, are successfully passed, increasing customer satisfaction and business outcomes.


In the near term, Experian foresees a growing adoption of Machine Learning augmented data processing models in the near term as organisations deal with an increasingly large number of data-sets and digital touchpoints that necessitate more efficient ways of processing data rapidly.


Empowering Consumers with Data Driven Financial Access

Experian has long recognised the transformational potential of data, harnessing its power to create opportunities, improve lives, and make a difference to society. A key focus for Experian revolves around the use of data to drive financial inclusion in regions such as Southeast Asia, where only 48 per cent of more than 600 million people have access to traditional banking services.


Experian’s approach to enhancing financial accessibility is centred around the use of non-traditional data for credit scoring, empowering organisations to determine the credit worthiness of individuals in regions where bureau data is limited or unavailable. For instance, telecommunication network providers often represent great sources of alternative data. User behaviour such as calling patterns and app usage may all be utilised to build a credit profile of an individual, which may then be used as a reference for financial institutions.


Experian has recently inked partnerships with the likes of C88 Financial Technologies and BankBazaar. Both collaborations are envisioned to extend financial accessibility to millions of consumers across Indonesia, Philippines, and India. Moving ahead, the next step for Experian is to work with banks to overhaul client processing, speeding up the process through the use of alternative data.


Experian’s Venture and ‘service for equity’ programs are due to be introduced at a later date. In the meantime, start-ups keen on working with Experian can contact us here. 


Read full article


By Experian 11/20/2018

Related Articles

Creating Opportunities and Innovating in the New Age of Data
Creating Opportunities and Innovating in the New Age of Data

An insatiable desire to innovate has given rise to the modern economy. In 2018, the link between innovation and progress remains strong as ever. Successful organisations are often those which…

Learn more
Is It Time to Rethink Your Credit Risk Strategies Amid Supply Chain Disruptions?
Is It Time to Rethink Your Credit Risk Strategies Amid Supply Chain Disruptions?

Global supply chain disruptions have exposed critical vulnerabilities in how you interact with suppliers and customers across the globe.

Learn more
Malaysia is Set for the Next Leap in Credit Decisioning
Malaysia is Set for the Next Leap in Credit Decisioning

Key use cases and recommendation from IDC where data and analytical techniques have been able to assist Malaysian financial institutions and digital lender in their credit decisioning process.

Learn more
  • Submit

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