Upgrades in Value and Time: Five Problems to Be Solved with Fintech Tools
As fintech evolves, the usage becomes broader and the effects more profound. We sort out the five main problems in the financial field that have been or are likely to be solved by advanced technology.
In 2018, the fintech market was worth about USD 127.66 billion. The number is predicted to reach about USD 309.98 billion in 2020. As the fintech industry has gone through the initial development stage, traditional institutions are accelerating the pace of investment into the technology; clients are provided with more diversity in service choices, and regulators are stepping into this market with greater gusto. The market's competition tempo is also changing.
In 2019, the total mega-rounds hit a record high in each area, especially in the United States and Canada. The number was nearly doubled compared to the previous two years. Investors are pouring money into potential firms.
Fintech mainly has two advocates – the innovator and the creator. The former provides products with more attractive conditions such as lower fees. Often, the products or services are provided by traditional financial institutions, but some problems exist so that many clients cannot be reached, and service quality is questioned. The latter creates a new service that relies on cutting-edge technologies and alternative business models such as mobile payment. In this chapter, we mainly focus on the former to dig deeper into the five main problems that can be solved by technology to achieve success.
The credit system is a necessary infrastructure layer for the whole fintech industry as well as for society. Personal and enterprises' credit information records in some countries are blank or incomplete, and the information cannot be shared, which results in 'isolated data islands.' The technologies applied to help establish this system constitute a major flow into the reservoir of big data. Big data continues to broaden its sources, which can be collected from more dimensions, not limited to commercial areas such as social media and online shopping; through data mining, more personal features can be caught. Through data integrating and calculating to evaluate credit subjects, credit efficiency has improved, and a more open credit system can be established.
China is predicted to establish its national social credit system by the end of 2020. During the past few years, the government has been paying efforts to record more individuals in the country into the credit system. And once this is set up, the data can be used in the whole fintech ecosystem. When people get credit, they will go on to generate more data as they interact as consumers or with operating businesses. This process forms a data closed loop. And the United States' credit system has been run for over a century largely by market actors, while governments mainly lead European ones.
The information asymmetry is another problem in the financial market. The information gap among traditional financial institutions, enterprises, and individuals makes it hard for banks to predict risks. This group of clients mainly consists of SMEs Small and Medium Enterprises) and individuals with lower credit scores. This group of clients needs little loans and has difficulties in evaluation, which of course, is not the kind of business welcomed by banks. But this group of clients often occupies a large percentage of the market, especially for SMEs, and the information asymmetry makes it hard for the finance market hard to provide financing services for the real economy.
Big data and AI can be applied to solve this problem. mainly using areas including P2P lending, micro-lending, consumer finance and supply chain finance. These technologies can get trustable information from diverse dimensions and allow evaluation of the risks for clients that could not be covered previously. One prominent example is supply chain finance, since for SMEs upstream and downstream on the supply chain, they have little financial records and limited abilities of financial management skills. And these SMEs' business operation conditions can be evaluated through data collected from business cooperation with core companies, data such as transaction records. For personal lending P2P platforms, it is popular in the US while in China, they were killed after five years of rising and decline, from 2014 to 2019.
The traditional business process for financial institutions often includes several steps, and each step needs human labor to finish and deliver information. So the operating cost is high, and humans can only handle limited cases and provide limited clients each day. For risk costs, when financial institutions cannot identify risks for clients through traditional methods such as central bank credit reports and warranties, they cannot access financial service. But if banks decide to do research, higher operating cost problems happen again; if lower-risk control standards may lead to risk exposure. In a word, the traction cost of each business case and risk is high.
While fintech finds a way to solve it, the most widely used is cloud computing, and the application scenarios example is digital banking. Digital banking is regarded as the future of banks, in which the whole business pipeline is built on the distributed structure, and big data is shared online among all departments. Financial institutions can get data information if clients give them authorizations. As a result, banks can evaluate clients' financial conditions. The number of days served clients are improved and labor cost is decreased since most of the business process is calculated online.
Large banks in China and the US are all focused on this area; this seems to be common sense. The usage of technology can significantly reduce costs. One good example is Webank in china, which uses fintech to reduce (in Chinese) the cost of banks to CNY 3.6 (USD 0.51) per household, while the domestic average cost of traditional financial institutions is between CNY 20 – 100 (USD 2.83 – 14.14) per household.
Homogenization of products
The financial products provided for clients are often pretty similar to limited choices and are sometimes unable to meet clients' demands. Most of the time, the design-related products and then bring products to clients through distribution channels. And sometimes, it may cause vicious competition, since their products and targeted customers overlap. So the situation is, the market has demand notches while existing products struggle to catch clients' eyes. The supply-side and demand-side are not matched. Artificial intelligence and big data provide solutions for this trouble. The tailored design and pricing of products will replace homogenized ones, and the demand side and supply side will shift towards equilibrium. The application cases include insurtech, wealth management and lending.
Safety and regulation
Some safety problems have already existed for a long time, such as online fraud and identity forgery. Besides, the appearance of fintech itself will generate safety concerns such as data privacy, and some firms make use of a loose regulation environment to profiteering. Some of them are not truly fintech firms, and only want to take advantage of this hot concept to attract investors and users. The technologies applied are biological identification, encryption technology and the regulatory sandbox. Application cases can combine with all areas of fintech since safety and regulation are needed everywhere. These technologies can identify online fraud and raise warnings when something unusual happens; the solving of private data issues is in the early stage. The sandbox can test fintech firms' risks and operation conditions, so the risks in the real world can be checked earlier and losses reduced. Different from other problems, this is a problem that is attracting each county's serious attention and maybe can be solved by countries together.
Fintech provides solutions that combine technologies and business demands to solve problems; this wave of promotion will just be accelerated. Players in this market are using fintech to improve their competitiveness to earn more clients and market share. The regulators are taking part in this market more deeply to standardize market behavior. Participants who have real technical skills to solve problems and comply with market regulations can take place in the fintech industry. A new fintech ecosystem with more energy, higher efficiency and greater safety is brewing.