Transaction Categorization API: New Strategy for NPL Prevention

Transaction Categorization API: New Strategy for NPL Prevention

In addition to its impacts on communities health, the COVID-19 pandemic has also led to a significant decrease in borrowers repayment capability in Indonesia.

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According to the survey by Pefindo Credit Bureau, the average total percentage of high-risk and most high-risk borrowers was above 40% from March to May 2020, in stark contrast to the total percentage of low-risk borrowers which kept decreasing to 3,9% in May.

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The same thing also can be seen in the NPL rate which increased from 1,8% to 3% just in the same period. It is predicted that the increase happened by the troubled cash flow of borrowers before the pandemic strucks.

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While the ratio is stable now, it does not mean that fintech lending companies will stay safe and sound. The same problem may occur eventually if lenders start to loosen borrower's cash flow screening processes.

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Aside from additional data such as income or employment information, lenders can include categorized data such as payment and purchasing. Lenders thereby will not only understand the borrower's capacity to repay the loans when it's due, but also to better see the borrower's financial situation and their consumption patterns.

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Brick Transaction Data API

That is why Brick provides liabilities data through our Transaction Categorization API to enable clients retrieve any categorized purchases, payments, and transfers accordingly from a transaction description stated on financial services statements.

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Our categorization can label transactions made to P2P lenders, multifinance and other financial services as liabilities. Clients can use this data to understand how much liabilities that end-users have. Clients can match this data with Income Data to calculate end-users debt-to-income ratio.

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How does it work?

1. Client asks the end-users to authenticate and connect their Financial account to the apps.
2. End users authorize client's access to retrieve their transaction data and related aggregated spend attributes.
3. Client submit a request of end-users categorized transaction data and aggregated spend attributes to Brick's API.
4. Bricks API response to lenders with requested data.
5. Categorized data is served to clients.
6. Client can assess end-users credit worthiness based on recurring repayment transfer made to P2P Lending, Multifinance and other Financial Services