As with all tools, whooing also focuses on some of the inconvenient parts. Most of these are optimization issues that can be tolerated to some extent, but if you are a user who focuses on this feature, it may not suit you. The main disadvantages are as follows.
The word double entry bookkeeping is not a common concept we use. As explained in the account, each term is used in everyday life, but it is not used as a concept to refer to the flow of money in relation to each other. Whooing is based on this double-entry bookkeeping method. Therefore, some understanding of double entry bookkeeping is required. If you have difficulty in doubles bookkeeping, please refer to external data on doubles bookkeeping.
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.
For this part, whooing is not completely out of hand and is providing a way around. It is divided into two parts: [collecting transaction data] (/help/tips/outside) and a part that allows users to [easy classify and complete input] (/help/tips/outside) collected data. .
You can use whooing in full by accessing https://whooing.com, whether on desktop or mobile. However, there are no official iOS or Android apps yet. This is not because it has a special purpose, and because whooing specializes in web development, it is not possible to fully develop native apps optimized for each platform. This is also the result of the web standard strategy, which attempts to provide as much accessibility as possible with minimal force in its current state. We are thinking of developing an optimized app if native capabilities are reinforced in the future.
There are still several native apps. There are third-party apps developed by individual developers through whooing's Open API and registered in the market. A full list of these can be found in [Third Party Native Apps] (/help/tips/thirdparty). Where the official website focuses on providing overall functionality, third-party apps differ in that they provide platform-optimized environments for individual developer preferences or specific purposes.
whooing is a paid service. You may not understand that you have to pay more to use your household account book to save money. However, we who manage money should look at the utility of the investment rather than the unconditional cost control. If you can earn 30,000 won by spending 3,000 won, it is not a loss. You can also think of the opportunity cost of free and paid. If it's free, you can think of the opportunity cost of not knowing how your data will be used, advertisements that hinder usability, and anxiety about when the data that adds value will disappear over time.