Jiang Jianqing is an Adjunct Professor of Finance at the China Europe International Business School (CEIBS) and also the Director of CEIBS Lujiazui Institute of International Finance (CLIIF). Prior to joining CEIBS, he was Chairman of the Industrial and Commercial Bank of China (ICBC). At present, he is the acting Vice Chairman of the China Finance Society. He received a doctorate degree in Management from Shanghai Jiaotong University in 1999.
Today, the global economy is struggling to recover and gain momentum amid highly complex political and economic situations, dramatic changes in economic structures, and uncompleted transitions from old to new dynamics. Particularly, the global finance industry faces new challenges:
• Financial fluctuations are intensified.
• Financial regulation is becoming more stringent.
• Expansionary monetary policies lead to loose liquidity.
• Narrow interest margins and negative interest rates frustrate the global banking industry due to the deterioration of asset quality and the decline of revenues and profits.
Against this backdrop, the business models and competitive landscapes of the global banking industry are being profoundly changed.
Today, the cycles of the business world and finance industry are overlapping. Many international financial institutions have responded to this overlap by selling assets, scaling down on investments, downsizing their workforces, closing low-performing offices, and taking other countermeasures. By doing so, they hope to survive the hardest development period without compromising capital needs or profitability. In the era of economic globalization, China’s banking sector is also facing the same challenges as its peers: A sharp decrease in the rate of profit growth and a quick increase in bad assets.
Established Relationships between Banks and Their Customers Are Being Disrupted
The banking industry is at the crossroads of a new cycle of digital transformation. Financial Technologies (FinTech), represented by cloud computing, the Internet, mobility, blockchain, and Artificial Intelligence (AI), are gaining momentum and quickly penetrating into the financial services sector. Financial disintermediation and rate liberalization are evolving at an accelerated pace, bank business structures are being adjusted, and competition from new, non-bank entrants is intensifying. New industry environments and landscapes, such as financing and payment disintermediation, are taking shape. The public’s understanding of banks has changed. Banks are losing their advantages of size, geographical coverage, and local branch networks. The banking market is undergoing further segmentation and quickly evolving. Traditional relationships between banks and their customers are being disrupted.
Consumers have unprecedented control over information. Some of them even have more information in their hands than bank sales personnel. As a result, they are no longer as dependent on their account-opening banks as was expected previously, and they do not necessarily follow the instructions or guidance of bank sales personnel. Instead, they have begun to proactively find their desired products and services on their own. The digital era is upon us, and there is no doubt that it is disrupting banks’ long-held ideas, business cultures, and operating modes. The entire market landscape is being shaken.
Rather than a heavy reliance on old, inflexible thinking patterns, bank development models must be continuously adjusted and optimized. The banks that fail to quickly adapt to the digital era will be phased out.
Banks Are Still Not Data-Savvy Enough, Although They Possess Massive Amounts of Information
We are living in an information society. Information Technology (IT) is an important driving force for social development and progress. The banking sector is tech-savvy and knowledge-intensive and has always stood at the forefront of the use of cutting-edge IT technologies.
Since the start of the 21st century, China’s major banks have successively completed large-scale data centralization and the setup of comprehensive business systems that take IT usage to new heights. Substantial progress has been achieved. These implementations help to dramatically accelerate innovation, improve competitiveness, centralize data, intensify operations, modernize management, and deliver services via electronic channels. It can be said that the impressive achievements made in China’s banking sector would have been impossible without the advances in IT.
The most recent round of IT initiatives in China’s banking industry are nearly complete and the next stage of ICT-enabled banking programs is accelerating throughout the country. By highly integrating digital technologies with operational management, ICT-enabled banking will create non-replicable core competitiveness and reshape the banking business model and development patterns.
While acknowledging the great IT achievements, we must also note that IT construction in China’s banking industry has been carried out in phases. As a result, many systems were designed and developed based on traditional manual operations, ideas, and approaches, leading to many inter-system coordination issues, such as system siloes, disparate standards, complex correlations, overlong processes, and high operating costs.
Banks are continuously expanding in size, going international, and operating holistic sets of financial services. As such, data issues, such as departmental silos, inefficient transmission, and slow responses, become more obvious. And though some banks possess large amounts of information, they are still not data-savvy enough because data silos limit the ability to achieve cross-department data mining and consolidation.
The banking sector inside and outside China has always attached importance to investing in the construction of ICT-based banks. The key to success is to hold the right mindset, develop the right strategies, and take the right actions. Building ICT-enabled banks is more than simply conducting digital technology upgrades or extending the range of applications. Instead, it means information integration and consolidation. The basis of banking informatization is a radical change to the quality and flow of old operations and management paradigms.
Four Keywords Best Define ICT-Enabled Banks
The prominent features of ICT-enabled banks are best described in four keywords: centralization, consolidation, sharing, and mining.
• Operations centralization: Operations become streamlined and standardized at very large scales. Businesses are centrally processed. Front-end, mid-range, and back-end systems are effectively separated. All types of risks are centrally monitored. All measures aim to improve quality and efficiency, reduce costs, and control risks.
• System consolidation: Central IT systems are set up. Information silos are eliminated. Unified architectures are adopted, and systems are engineered to interoperate with one another efficiently. The resulting benefits include flexible coordination for operations and management, and fast responses to market needs.
• Information sharing: Data-sharing platforms take shape. Data query and retrieval become easier. The setup of such platforms improves the availability and usability of information.
• Data mining: Data is collected, stored, processed, analyzed, and utilized. Cutting-edge data mining technologies help unleash the maximum value of mass data. Data mining results are used to gain insights into market trends, identify prices, evaluate risks, and allocate resources more efficiently. Data mining also facilitates operational decision-making, product innovation, and precision marketing.
Success in building ICT-based banks will result in generational differences between competing banks. Winners will maintain their strategic advantages for the long run.
Taking a Three-Step Approach to Building ICT-Enabled Banks
Building ICT-enabled banks starts with three aspects; platform, data, and finance:
• Information platform: Banks not only act as the financial services providers, but also become important data services providers in the entire economic system. They are expected to accumulate information (including transaction, financial, and logistics information) in every link of economic activity and then deal with such information using Big Data processing and mathematical modeling analysis methods. Doing so helps determine the potential financial requirements in the market and provides more targeted financial services to customers.
• Data foundation: Well-developed data warehouses are constructed to mine and analyze all types of structured and unstructured data, as well as implement data sharing. Data is used to gain insights into market trends, conduct precision marketing, identify prices, evaluate risks, and allocate resources more efficiently.
• Internet finance: Banks must actively engage in this transformative megatrend and give full play to the most innovative of ICT achievements to vigorously develop financial products and services. Banks are expected to unveil new products and extend the scope of services by leveraging powerful Big Data analysis technologies. Doing so improves the quality of service delivery to long-tail customers who are too easily ignored under traditional business modes, enhances customer experience, and increases the operating efficiency of financial systems.
Big Data and Intelligent Operations Drive the Construction of ICT-Enabled Banks
The key to building ICT-based banks is to enable the asset management and risk control capabilities of banks with modern information and communications technology. Asset conversion — meaning the conversion of capital from multiple dimensions, such as time, space, and scale — is the most critical function of a financial services organization.
Risks exist across the entire asset conversion process. Today, frequently occurring credit risks signify that traditional credit management approaches and existing information processing capabilities are inefficient for mitigating risk. For example, it is impossible to quickly and accurately understand funds, logistics, and information flows. Social credit information is fragmented and not easily shared. Disorderly competition, nonstandard credit grants, and data isolation result in severe information asymmetries. Some enterprises illicitly use information asymmetry to screen information and forge fake transactions. Due to credit losses, banks worry about being defrauded and can feel mired as if in a ‘pawn shop’ culture. As a result, a vicious cycle of social transaction costs is increasing where unsophisticated enterprises can succeed in blocking regulated enterprises.
The use of Big Data and intelligent operations in asset management and risk control is crucial to banks and other financial institutions now and in the future. As the breadth and depth of social and economic activities are radically changing, the risk control capabilities of banks must rise to meet new challenges. Big Data is not data sampling; instead, Big Data uses models to import complete, holistic sets of data to analyze transaction habits and identify risks from abnormal transaction habits. Therefore, it is a must to strengthen research and analysis of source data to ensure that information is accurate by industry, region, individual, competitor, product, transaction, time, and content. A feasible method for effective risk management is to make full use of detailed transaction records from governments, intermediary organizations, and enterprises combined with data from social credit losses, breaches of contract, and other legal or regulatory violations. This approach ensures the availability, reliability, accuracy, and timeliness of data sources. The longer the history, the higher the accuracy of the data. In addition, credit risks are monitored by using data integration, consolidation, and logical analysis models such as data association and data matching. All of these help make the following possible:
• Precise credit approvals and accurate credit management: Develop standardized and professional credit classifications through the use of Big Data analysis and mathematical models to resolve issues found in traditional approaches, including standards non-compliance, oversight, and lack of synchronization to streamline management processes and improve approval efficiency.
• Credit innovation: Achieve precise admission, automatic approval, and model-based risk control to develop more online, self-service financing products.
• Deep understanding of customer behavior and needs: Establish unified customer tags and customer profiles to form a panoramic view that enables precise, targeted, and effective marketing.
• Judgment on risks of enterprises and their data: Collect data from multi-dimensional sources, combine and associate data through mutual proof to discover and highlight abnormal transactions, accounts, and habits.
• Strictly monitor enterprise fund, logistics, and information flow: Focus on settlements and, in particular, risks. The absence of settlements probably indicates risks. Post-loan management must rely on daily traffic monitoring. Poor credit cultures do not have effective approaches for monitoring loans after approval, and follow their customers only through their payment of interest.
• Risk measurement systems: Determine risk appetite, risk concentration, and risk limits to determine the reasonable distribution of capital.
High-Tech Innovations Unleash Infinite Possibilities for Traditional Banking Industry
Modern finance is evolving by combining finance with ICT technologies. The FinTech revolution is driving a shift from physical currency to virtual currency, and banks are changing their role from being a payment and financing intermediary to being an information intermediary. Over-the-counter services are evolving from human-human dialogs to remote mobile self-service operations. Banks and Fintech have close interactions. Looking back at the past several decades, we find that all financial innovations would have been impossible without financial technologies.
Banks actively embrace technologies to improve their core competitiveness. The banking industry is often the earliest adopter of the latest high-tech innovations and achievements. In the future, Big Data and AI technologies will make a difference in the finance field, especially in the area of risk control during asset conversion processes. Credit decision-making is a game process, and it must be dealt with beyond traditional approaches that heavily rely on experience gained from constant practice and lessons learned.
The win and loss experiences are accumulated by constantly learning. Deep neural networks can be used to simulate the human’s brain mechanism for credit judgment and decision-making. Internet finance and blockchain technologies will play a bigger role in the payment field and improve payment security. Virtual Reality (VR) technology will be a great help for on-site credit investigation. Unstructured image data will provide a true-to-life, engaging experience for remote decision-makers. Remote mobile Internet technology will disrupt the operating and service delivery models of traditional banks. Banking services free from organizations and manual intervention will be a slow-paced but inevitable megatrend.
In the future, banks will not necessarily be fixed places, but they will definitely be providers of indispensable services. Although the world may experience disastrous global financial crises, the pace of innovation in the finance sector will accelerate as a result. The global banking industry is undergoing an unprecedented digital revolution. Traditional banks are being disrupted and overshadowed by the rise of digital, ICT-enabled banks that are reputable due to their vitality and efficiency. The digital journey of banks worldwide is undoubtedly a challenging transition. Standing at the moment of history-making change, China’s banking industry is a pioneer and will endeavor to boldly explore a new path through consistent practices.
(Source: China Europe International Business School)