China Merchants Bank
Many Chinese banks have made impressive progress in promoting technology innovation, but the bank that has pushed furthest in all aspects of its business is China Merchants Bank, led by Zhang Dong.
In the first half of 2019, the bank spent Rmb3.63 billion ($517 million) or 2.8% of its operating income on information technology, up by 64% year on year.
CMB has used fintech, especially big data and machine learning, to achieve plenty in recent years, including shortening the time of most personal loan decisions to under a minute and automating call centres while achieving a 98% customer satisfaction rate. The bank has also combed its dataset to create 1,800 distinct customer profile types and an all-important customer experience monitoring system.
CMB is innovative enough that its tech achievements are listed on not just one but multiple pages. But perhaps the most impressive during Asiamoney’s awards period was a series of landmark changes to the bank’s Flash Loan service.
By adding facial and fingerprint recognition and internally developed big data algorithms, the bank has managed to allow clients to apply online for retail loans at any time through a completely automated process.
By June 2019, the approval process for residential mortgages had a T+0 timeframe and for micro-finance loans a T+2 timeframe, representing a 7% improvement in efficiency compared with the end of 2018. The data algorithms can even help the bank set appropriate loan pricing depending on the real-time supply and demand of loans.
By the end of 2019, roughly 4.6 million customers had used the bank’s Flash Loan service. Perhaps most impressively, CMB’s asset quality improved. The balance of CMB’s non-performing loans amounted to Rmb53.2 billion by June 2019, a decrease of Rmb384 million from the end of 2018. The non-performing loan ratio of the bank also declined by 0.13 percentage point from the end of the previous year.
To help the bank’s own internal decision-making and marketing efforts, CMB has built a new big-data program that can analyse nearly 700 million credit records a day. That has not just made the bank better, it has also saved it money – roughly Rmb71 million a year – on data collection and analysis.