This study examines the impact of ownership structure on Chinese banks' risk-taking behaviours. We classify the Chinese commercial banks into three categories based on the types of controlling shareholder, and find that banks controlled by the government (GCBs) tend to take more risk than those controlled by state-owned enterprises (SOECBs) or private investors (PCBs). This is attributed to the severe political intervention and weak incentives to follow prudent bank management practices for GCBs. We also find that the results are more pronounced among banks with concentrated ownership presumably because the large controlling power helps to enhance the monitoring of the management and promotes prudent operating procedures. Our findings have important implications for the ongoing reform in the Chinese banking sector.

We employ a hand-collected unique dataset on banks operating in China between 2003 and 2011 to investigate the impact of board governance features (size, composition and functioning) on bank efficiency and risk taking. Our evidence suggests that board characteristics tend to have a greater influence on banks' profit and cost efficiency than on loan quality. We find that the proportion of female directors on the board appears not only to be linked to higher profit and cost efficiency but also to lower traditional banking risk. Similarly, board independence is associated with higher profit efficiency of banks; while the opposite is found for executive directors and in the presence of dual leadership of the CEO/chairperson. Among the control variables, we found that liquidity negatively affects profit and cost efficiency, while positively affecting risk. Interestingly, we find some evidence of an incremental effect of specific board characteristics on efficiency for banks with more concentrated ownership structures and state-owned institutions; while for banks with CEO performance-related pay schemes the effect on efficiency when significant is usually negative. Our results offer useful insights to policy makers in China charged with the task of improving the governance mechanisms in banking institutions.

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This paper explores how borrowers' financial and personal information, loan characteristics and lending models affect peer-to-peer (P2P) loan funding outcomes. Using a large sample of listings from one of the largest Chinese online P2P lending platforms, we find that those borrowers earning a higher income or who own a car are more likely to receive a loan, pay lower interest rates, and are less likely to default. The credit grade assigned by the lending platform may not represent the creditworthiness of potential borrowers. We also find that the unique offline process in the Chinese P2P online lending platform exerts significant influence on the lending decision. We discuss the implications of our results for the design of big databased lending markets.