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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
Observations

Focus will be on additional analytics and more fraud automation.

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
Observations

BFSI have the most superior capabilities in fraud management–in speed of detection, accuracy, and contextualization.

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
Observations

Spurt in digital activity in the recent past has initiated investment in new technologies (i.e., robotics, AI, machine learning, biometrics) for better fraud detection and improved contextual marketing. The industry is working in collaboration with third-party agencies on alternative data sources, and is open to work with fintech companies.

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
Observations

BFSI seeks to increase consumer trust by investing in data quality and data management issues, and in new technologies (e.g., AI, biometrics).

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
Observations

The rapid deployment of fiber to the home and LTE mobile broadband is accelerating the need for customer analytics and collections and fraud management by telcos; retailers are most concerned about employee fraud, because ofiine is a larger sales channel.

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
Observations

Companies are generally weak in fraud management, but could be influenced by customers being more tolerant of fraud.

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
Observations

Spurt in digital activity in the recent past has initiated investment in new technologies (i.e., robotics, AI, machine learning, biometrics) for better fraud detection and improved contextual marketing. The industry is working in collaboration with third-party agencies on alternative data sources, and is open to work with fintech companies.

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
Observations

Majority of companies realize that they have moderate capabilities in fraud detection.

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
Observations

Companies have moderate capabilities in fraud detection, but majority believe that improvements are required in areas of fraud resolution for better assistance to victims of fraud as consumers increasingly face more fraud risks.

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
Observations

Spurt in digital activity in the recent past has initiated investment in new technologies (i.e., robotics, AI, machine learning, biometrics) for better fraud detection and improved contextual marketing. The industry is working in collaboration with third-party agencies on alternative data sources, and is open to work with fintech companies.

May 24 2019 /

Experian

Millennial Moods

  • Experian Millennial Moods - Kidults Profile Image

    Choosing to live in the family home to reduce living expenses

    Kidults

    Choosing to live in the family home to reduce living expenses

  • Experian Millennial Moods - Gentrifiers Profile Image

    Finding affordable pockets of major cities to live in

    Gentrifiers

    Finding affordable pockets of major cities to live in

  • Experian Millennial Moods - New Age Metros Profile Image

    Inner city singles and couples working hard, playing hard

    New Age Metros

    Inner city singles and couples working hard, playing hard

  • Experian Millennial Moods - New Estate Lifestyles Profile Image

    Escaping the inner city squeeze for their first homes

    New Estate Lifestyles

    Escaping the inner city squeeze for their first homes

  • Experian Millennial Moods - Working Hard Profile Image

    Working in blue collar jobs with a high propensity to spend

    Working Hard

    Working in blue collar jobs with a high propensity to spend

  • Experian Millennial Moods - Gap Year Profile Image

    Enjoying time off to decide on study and career choices

    Gap Year

    Enjoying time off to decide on study and career choices

  • Experian Millennial Moods - Young Aussie Battlers Profile Image

    Young couples and families living in the suburbs

    Young Aussie Battlers

    Young couples and families living in the suburbs

  • Experian Millennial Moods - Studying Hard Profile Image

    International students completing tertiary qualifications

    Studying Hard

    International students completing tertiary qualifications

  • Experian Millennial Moods - Regional Youth Profile Image

    Single parents with lower than average income

    Regional Youth

    Single parents with lower than average income

 

In a world of fast paced change, people born twenty years apart won’t all behave the same.

 

The world was different in 1980 compared to 2000, and as such, communicating to an 18 and a 35-year-old in the same way is a pitfall many brands still fall into.

 

Experian has developed nine unique Millennial segments to provide deeper insights into the lifestyle, behaviour and attitudes of a significant and complex part of our population.

 

Complete your information below to access our Millennial Moods Information and discover how you can segment your own customer base into these 9 distinct Millennial groups.

 

 

 

Read full article

Experian

By Experian 05/24/2019

G030 Millenial Moods Paper - update_WS_v3

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Mosaic in Action

Explorea other group and audience descriptions.

Central Prosperity

Central Prosperity

Middle-older aged empty nester couples renting very expensive properties in inner-urban areas, with high income.
Selfless & Hardworking

Selfless & Hardworking

Blue-collar families from multicultural backgrounds, living in outer-suburban areas, with average to high income.
Mature Modernites

Mature Modernites

Middle-aged couples without children, renting in inner suburban apartments and terraces.
Determined Suburbans

Determined Suburbans

Professional couples and singles with high income, owning their first home in high growth inner suburbs.
Farming Reliance

Farming Reliance

Rural farmers and farm owners with below average income, living 10-40km away from the nearest town.
Power Couples

Power Couples

Young diverse couples, well-educated, transient, city centre renters with high income and no children.
Spirit Questers

Spirit Questers

Millennial singles renting in coastal tourist areas, with below average income.
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