Our reporter Guo Jianhang reports from Beijing.
With the dilution of banks’ profits and the increase of labor costs year by year, how will IPC micro-credit technology (hereinafter referred to as "IPC credit technology", which is an integrated credit consulting service and solution provided by German IPC company for the financial field) continue to iterate in rural credit cooperatives?
As we all know, the core of IPC credit technology lies in the judgment of loans by bank account managers through offline investigation of the actual repayment ability of small and micro-loan customers. Since it was introduced into China in 2005, IPC credit technology has been widely used in rural credit system because the small and micro-loan customers did not meet the risk preference of large banks at that time, and the model required an independent offline account manager team.
"China Business News" reporter noted that with the rise of Internet loans in recent years and the maturity of big data risk control, the debate in the industry about which is better or worse between IPC credit technology and online big data risk control technology has been going on.
Jin Yunling, deputy general manager of the village finance department of Taizhou Bank, clearly stated that "rural areas have social characteristics of geographical popularity, and IPC credit technology, as a representative of geographical credit technology, still has great value in the field of agriculture-related credit with the rapid development of big data and financial technology."
Yang Yijian, Assistant General Manager of Microfinance Headquarters of Changshu Bank (601128.SH), recently held an internal seminar in China inclusive finance Research Institute. Regarding the question of whether IPC credit technology is outdated, he thought that "IPC credit technology itself is not outdated, and the core lies in whether the organization can guarantee the continuation and continuous iteration of this technology."
Technical iteration
Compared with the way that financial institutions can borrow assets such as customers’ inventory through satellite remote sensing technology in the data age, IPC credit technology has a completely different inventory method for customers’ assets in the early days of micro-credit.
Recalling the small micro-loan credit review work in the early years, Jin Yunling said, "When customers have loan needs, account managers will go to the site to inventory. Careful enough to make the number of chickens and ducks of farmers accurate to less than 100. In addition, most of the loan approvals will be reviewed several times, and the customer’s repayment ability will be cross-verified. "
The advantages of IPC credit technology at that time were self-evident. After systematic training and study, the bank account manager quantifies the customer’s actual repayment ability into standardized indicators such as pre-loan preparation table, questionnaire and logical inspection table through offline investigation. In this process, seeing is believing and cross-checking are the key parts.
However, an unavoidable problem of rural commercial banks is that the application of IPC technology will face the upper limit of the number of bank account managers. How can rural commercial banks improve the productivity of account managers and apply IPC credit technology to a wider range of credit scenarios?
Zhangjiagang Bank (002839.SZ) said in the investor activity in January this year that it is gradually transforming digital micro-credit based on the existing IPC credit technology, and improving its business efficiency by building a digital credit system "new micro-loan", while continuing to develop online and semi-online products and increasing the development, operation and promotion of credit insurance products.
As the first Taizhou Bank to introduce IPC technology, Jin Yunling said that at present, the innovative application of IPC credit technology is mainly promoted in two directions. The first is to grant credit to the whole village. After excluding unqualified customers in a village, all qualified customers are pre-granted. The second is to obtain customers in batches through the supply chain. For example, the person in charge of the supply chain recommends customers and makes credit loans for upstream and downstream customers in the supply chain.
Jin Yuanling believes that the village residence model can effectively improve the productivity of account managers under IPC credit technology. "Under the IPC credit technology, the average monthly production capacity of an account manager is three or four hundred households, and about 600 households in the agriculture-related business are also relatively saturated. However, if the region is familiar, the efficiency of household management will be improved. Therefore, it is possible to improve the efficiency of household management by setting a person to live in a village and understanding the information of the village. "
Jin Yuanling said, "In recent years, the supply chain +IPC exploration has achieved good results, and a new path of performance growth has been opened, with outstanding risk control capabilities."
Changshu Bank, which introduced IPC credit technology earlier, also has its mature operation on how to combine IPC credit technology with digital application.
Yang Yijian said that at present, the online loan products of Changshu Bank are scenario-based products. In the scenario, account managers take control, give fast access to materials, conduct rapid approval through models, and expand customers with the model of scenario plus model. In fact, this is also a digital application based on IPC technology.
IPC technology and data risk control are not "black and white"
Facing the situation that big data risk control is used more and more widely in the banking system and its efficiency is getting higher and higher, more IPC credit technology practitioners believe that the relationship between the two is not changing, and the credit review logic created by IPC credit technology is still the cornerstone of data risk control credit review.
Practitioners believe that IPC credit technology adopts field visits and face-to-face communication and quantifies it into questionnaires because small and micro customers lack standardized financial statements and negotiable collateral, so it is necessary for bank account managers to restore the operating conditions of small and micro customers through investigation technology. Now, although big data risk control can obtain the actual operating conditions of small and micro customers through other channels, the audit method can still follow the logic of IPC credit technology era.
Yang Yijian believes that IPC credit technology and data risk control technology are not directly "black and white". Yang Yijian pointed out, "On the whole, in the micro-loan business, the underlying logic of IPC credit technology is the cornerstone of credit business, and the cross-verification of repayment ability and willingness of small and micro customers is still the focus of our judgment on customers. The application of third-party data, such as credit data and industrial and commercial tax data, is still a part of assisting risk control. "
The reporter learned that data acquisition channels are more and more extensive, and the data docking of government affairs system has a vital impact on the data risk control of small and micro loans of banks.
For example, Anhui Bozhou Yaodu Rural Commercial Bank launched Jinnong Easy Loan on the whole line of pure credit in 2016, and launched a series of big data credit products on this basis. At present, the big data credit business of Yaodu Rural Commercial Bank accounts for more than 80%.
For the application of big data technology, Gao Hui, general manager of inclusive finance Department and Big Data Application Department of Bozhou Drug Rural Commercial Bank, believes that IPC credit technology focuses on the analysis and verification of customers’ repayment ability and willingness, while big data credit is to maximize customer acquisition ability, fully extract customer value and identify customer risk points under the premise of effective risk control.
In 2015, Bozhou City, Anhui Province integrated all the data of government departments, covering the basic information of customers and family information, etc. The bank paid attention to the analysis of individuals in the early stage of application, and gradually improved it in the later stage, further enriching the data application dimension.
Gao Hui said, "Banks continue to dig deep into data, and big data has played a key role in improving our quality and efficiency. At the same time, banks have obvious advantages in risk control by applying such government data. 80% of the customers of Yaodu Rural Commercial Bank conduct business without manual intervention in the whole process, and 17% of the customers will have manual weak investigation, which realizes the organic combination of strong analysis of big data and manual investigation by account managers. With the support of data, the average account manager manages more than 2000 households. After the early system push, when there is a risk point that needs manual intervention, the account manager will conduct on-site or off-site verification and handling. "
Gao Hui, for example, said that big data will be marked with disability data (note: the data is confidential, and the model will be set automatically, and only desensitization prompts will be given). After the system triggers the disability data, the system will further analyze the disability level and judge whether it will affect production, life and business, and the impact on loan safety. According to the situation, we will further conduct offline investigation on access through the account manager.
In short, IPC technology and big data credit complement each other, without the accumulation of offline experience, there will be no full application of data.
Many practitioners in inclusive finance agree that at this stage, part of the data is obtained after the offline team goes to the field to visit. In the era of digital economy, IPC credit technology can improve efficiency, but it is too early to directly replace IPC credit technology.
In fact, when serving small and micro groups, rural commercial banks frequently encounter problems such as incomplete online data and insufficient risk control data in villages and towns. Even in the case of sufficient data, complete online operation can not meet the diversified and personalized financial needs of customers. Therefore, IPC credit technology still has practical significance and value.