BUSINESS PLAN TO DEVELOP SMART LENDING IN CONSUMER FINANCE COMPANIES IN VIETNAM
Chung, Chan Hai (2020)
2020
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2020052714357
https://urn.fi/URN:NBN:fi:amk-2020052714357
Tiivistelmä
The thesis is developed with the main research question of how to develop a smart lend- ing system for consumer finance companies in Vietnam?”. Currently, consumer lending in Vietnam has been blooming recently. The next stage of development in Vietnam con- sumer lending market is the application of new technologies to reduce KYC and ap- proval time from days to minutes. This system also allows consumer finance companies to expand the market share by acquiring more customers without the need of opening physical branches or sale channels.
However, smart lending solution is still in early development in Vietnam and not so many consumer financial companies have heavily invested into this solution. In the con- trast, they are still relying on manual and traditional lending process whether the cus- tomers still have to connect to branches or transaction offices in order to fill application forms and submit.
To develop a smart lending system, it requires strong joint-effort between different gov- ernment bodies, the strengthen in human resource quality, the advancement of know- how, smoother integration between smart lending system and other banking system, the application of advanced biometric technologies and the leverage of using artificial in- telligence and machine learning in credit risk modelling as well as in detecting fraudu- lent intentions.
However, smart lending solution is still in early development in Vietnam and not so many consumer financial companies have heavily invested into this solution. In the con- trast, they are still relying on manual and traditional lending process whether the cus- tomers still have to connect to branches or transaction offices in order to fill application forms and submit.
To develop a smart lending system, it requires strong joint-effort between different gov- ernment bodies, the strengthen in human resource quality, the advancement of know- how, smoother integration between smart lending system and other banking system, the application of advanced biometric technologies and the leverage of using artificial in- telligence and machine learning in credit risk modelling as well as in detecting fraudu- lent intentions.