Today's fintechs are putting its strength in automatically collecting and analyzing data without the user entering a transaction. This level of analysis may be useful to understand roughly how much your total income and expenses are, and how much you spend in each category.
There are two reasons why whooing doesn't support automatic typing.
One is the real difficulty of collecting. There are still administrative/economic barriers to collecting banknote transaction data in Korea. Fintech companies are also faced with obstacles to collection from time to time and are changing to workforce to solve them. This problem is showing signs of gradually being solved, and if direct collection is not possible, it will be possible to solve it by supplementing with methods such as indirect collection.
The second is the difficulty in classifying the collected data. Currently, automatic apps are classified based on affiliate information. It is the same method as a credit card company For example, if the place where the card payment was made is a coffee shop operator, it is classified as food expenses. However, whooing is useful because it is not simply classified based on business information. This is because, in the case of coffee, it is useful information to classify whether you drank coffee with a book for cultural life or whether you drank coffee for company work. And these still lack information that can be estimated outside of the user himself. Payment information is being collected more and more, starting with PayApp and Fintech apps, but even if all the information is collected, it is judged that classification by this purpose is not easy.