VLS has built and owns data on 6,250,000 houses, accounting for 83% of the total number of houses in 88 (100%) cities in Vietnam and updates market prices as well as other fluctuating factors of these houses. weekly. To build extremely large data as above, VLS uses exclusive technology and algorithms to collect and process in conjunction with experienced appraisers across the country.
When obtaining information related to real estate through the VLS system such as: Market price, asset legality, asset liquidity, past asset value growth and future price prediction of the property, of the area where the property is located.
VLS will connect the core-banking systems of commercial banks to directly provide the above information about the mortgaged real estate of that loan.
When VLS integrates into the bank’s core-banking system, it will automatically process and provide reports on risk management indicators as well as other factors that banks wish to have. Through these management reports, banks will increase or decrease customers’ outstanding debt depending on the real estate market price at the time of receiving the report. Banks will limit or increase lending to specific areas due to the liquidity and price growth of real estate in that area.
VLS provides a large number of potential customers for banks through individual and organizational users. When the customer enters basic information about the loan requirements and real estate information to be mortgaged, VLS will provide reports for the bank to consider to approve the loan or not grant the loan completely. automatically and quickly. This is a huge competitive advantage for banks today. The current traditional sales channel of banks is still manual, requiring a lot of time, effort, and cost but is ineffective.
At VLS, the web is deployed on AWS applications along with services DynamoDB, Cognito, API Gateway, Lambda (Nodejs) and many other supporting applications. Mysql, Php data management (laravel, Nodejs,… combined with artificial intelligence and big data mining.