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Big-Tech Credit for Inclusive Finance

Oct 23-2020   



When it comes to loans to medium, small and micro enterprises (MSMEs), risk management empowered by big tech might be more reliable than the traditional risk management of banks. This is one of the major findings of a series of papers by the Institute of Digital Finance (IDF) at Peking University in collaboration with the Bank of International Settlements (BIS) and the International Monetary Fund (IMF). The papers have ignited widespread discussions and media coverage.

 

In one recent media interview, Prof. Huang Yiping, Director of IDF and Deputy Dean of the National School of Development (NSD), explained that as part of financial data risk management, big-tech credit refers to the way large tech firms use extensive technological ecosystem and data risk management models to provide credit service to MSMEs and build innovative management framework for credit risk.

 

Compared to the traditional risk management of banks, big-tech credit has achieved a breakthrough as it works without the credit data of the Central Bank (at present most people don’t have such credit data) and relies on the data footprints on big-tech platforms for analysis to arrive at equally – perhaps better – credit assessment.

 

The papers show that big-tech credit has a better fit with small-scale MSMEs with a short credit history. As such it might offer a feasible path for inclusive finance, said Prof. Huang.

 

In the interview with Cai Jing magazine, Prof. Huang talked about the innovations that big-tech credit brings to the underlying logic of risk management, the traditional financial mechanisms that it collides with, and its adaptivity to economic cycles.

 

Prof. Huang said that big-tech credit can break down the bond between certain credit policy and housing price, thereby cancelling to some extent what Ben Bernanke termed Financial Accelerator Effect. As a result, the stability of the financial system will improve; on the other hand, credit policy will react more strongly to cash flow.

Big-Tech Credit for Inclusive Finance

Oct 23-2020   



When it comes to loans to medium, small and micro enterprises (MSMEs), risk management empowered by big tech might be more reliable than the traditional risk management of banks. This is one of the major findings of a series of papers by the Institute of Digital Finance (IDF) at Peking University in collaboration with the Bank of International Settlements (BIS) and the International Monetary Fund (IMF). The papers have ignited widespread discussions and media coverage.

 

In one recent media interview, Prof. Huang Yiping, Director of IDF and Deputy Dean of the National School of Development (NSD), explained that as part of financial data risk management, big-tech credit refers to the way large tech firms use extensive technological ecosystem and data risk management models to provide credit service to MSMEs and build innovative management framework for credit risk.

 

Compared to the traditional risk management of banks, big-tech credit has achieved a breakthrough as it works without the credit data of the Central Bank (at present most people don’t have such credit data) and relies on the data footprints on big-tech platforms for analysis to arrive at equally – perhaps better – credit assessment.

 

The papers show that big-tech credit has a better fit with small-scale MSMEs with a short credit history. As such it might offer a feasible path for inclusive finance, said Prof. Huang.

 

In the interview with Cai Jing magazine, Prof. Huang talked about the innovations that big-tech credit brings to the underlying logic of risk management, the traditional financial mechanisms that it collides with, and its adaptivity to economic cycles.

 

Prof. Huang said that big-tech credit can break down the bond between certain credit policy and housing price, thereby cancelling to some extent what Ben Bernanke termed Financial Accelerator Effect. As a result, the stability of the financial system will improve; on the other hand, credit policy will react more strongly to cash flow.