NCF Wealth Strives to Use Intelligent Risk Control Technology to Improve Efficiency and Reduce Risks
In recent years, due to the rapid growth of consumer finance and stringent financial supervision, the traditional risk control model has suffered bottlenecks due to cost, efficiency, information dimension, etc. Thus, intelligent risk control underpinned by big data, cloud computing and other scientific and technological means has started becoming a competitive arena for financial technology companies.
According to the information of Fintech Discovery, at present, state-owned, corporate and some city commercial banks have already taken action. “In 2020, the value of the financial technology market will reach 24.5 billion yuan, of which intelligent risk control takes 7.59 billion yuan, accounting for 31% with a huge market,” predicted by IYIOU.COM in the 2018 Research Report on China Intelligent Risk Control.
Obviously, in the next three years, intelligent risk control will witness fierce competition in financial technology, and become the most critical core competence of financial technology companies.
Against such backdrop, how to perform well in intelligent risk control will inevitably become the focus of all major platforms. NCF Wealth CEO SHENG Jia said in an interview, “As a technical means applied in such key links as risk control audit, asset pricing, post-loan tracking, financial technology will help improve the efficiency of risk control and better protect the rights and interests of investors.”
Continuous Innovations in Intelligent Risk Control Improve the Efficiency of Financial Services
The traditional risk control model based on risk scoring using “strong features” such as the traditional scorecard model and the rules engine inevitably has multiple weaknesses. “For example, the traditional risk control business process requires approval at all levels, which cannot meet the user’s capital requirements in time, leading to low efficiency, and bad user experience. Plus the high cost caused by the complicated auditing process, it is difficult to meet users’ needs,” said industry insiders.
Against such backdrop, the intelligent risk control that integrates big data, artificial intelligence, cloud computing and other financial technologies has become a trump card of the platform. “Intelligent risk control has revolutionized and complemented traditional risk control in three aspects. Firstly, its ultra-fast review speed provides users with better service experience. Secondly, it makes a more accurate analysis of the user behavior data. Last but not least, it utilizes data models to accurately quantify the time and scenario in which future risks are most likely to occur.”
The above-mentioned industry insiders said, “intelligent risk control is to capture non-traditional financial data, and enhance the relevant features of weak finance in the consumer finance market featuring large-scale growth in the internet economy. The analysis method based on machine model is a timely and effective supplement to traditional risk control.”
Meanwhile, as China attaches more importance to problems of inaccessible and unaffordable financing troubling micro, small and medium-sized enterprises, intelligent risk control has become more important for financial and pseudo-financial institutions to serve these enterprises and the real economy, and realize inclusive finance.
In the past few years, the government has made various explorations in developing financing for small and micro enterprises, but failed to get satisfactory results. At the “10th Lujiazui Forum” last year, Yi Gang, Governor of the Central Bank said, “the average life span of micro and small enterprises in China is about three years. Three years after their inception, only a third of them can keep normal business operation. However, it takes an average of 4 years and 4 months for them to have loans for the first time after establishment. That is to say, they have to survive the “death period” before they can obtain loans.”
Obviously, intelligent risk control based on big data, cloud computing and other scientific and technological means can not only improve the efficiency of financial services, but also serve small and micro enterprises and the real economy better. “When using big data, cloud computing, and the internet to solve the problem of information asymmetry, low cost and high efficiency become apparent. It does not only provide loans for small and micro enterprises, but also bring profits to financial institutions,” said Liu Shangxi, Member of the National Committee of CPPCC and President of Chinese Academy of Fiscal Sciences during the NPC and CPPCC.
At the 2019 Boao Forum for Asia, Li Dongrong, President of the National Internet Finance Association of China, pointed out that financial institutions should seize the opportunities of information technology development, enhance the level of digitization and datamation, improve the efficiency and capability of finance serving the real economy, and promoting the development of digital inclusive finance.
Helping the Platform Reduce Credit Risks and Achieving Precise Customer Positioning
However, when “intelligent risk control” becomes a buzz word in the market, what and how we can do to achieve better results undoubtedly become the core problem for all the major platforms to solve.
In particular, recent years have witnessed the implementation of stringent industry regulatory policies. On the one hand, scenarios and customer groups are becoming more diversified, placing complicated requirements on risk control. On the other hand, as customer group sinks, the customer information that can be effectively obtained is limited, making it urgent to improve the core risk control capabilities of the platform through the application of intelligent technologies such as AI + big data.
Take NCF Wealth as an example to get a glimpse of it. According to the information of Fintech Discovery, the platform is based on the concept of four-dimensional risk control system. It uses big data to build the cross-over algorithm of multi-domain database, introduces quantitative risk management technology, constructs a risk control model for different business forms, exercises overall management of credit, operational, compliance, and information security risks.
In addition, based on actual business demands, NCF Wealth has independently developed an intelligent risk control system “Tianyuan”. It is understood that Tianyuan System uses the current mainstream big data and AI technology, effectively covering all the links of the platform’s main business, including data collection, storage, anti-fraud, comprehensive credit score, credit approval, loan tracking, post-loan monitoring, overdue management, etc.
NCF Wealth’s Tianyuan Intelligent Risk Control System Strategy
In terms of R&D period, it took only more than half a year for “Tianyuan” Intelligent Risk Control System Project to move from R&D testing to launching. After its launching, online retail businesses were all audited by the system, covering the full life cycle of pre-lending, lending, and post-lending. This effectively prevents and controls customer frauds, reduces the credit risk of the platform, and significantly lowers the overall overdue index. Meanwhile, the system also realized the automatic approval of the risk control within seconds, shortening the approval time and effectively improving user experience. In addition, by using the latest anti-fraud technology and evaluation model, the system achieved precise customer positioning. As a result, the differentiation of customers and effective recognition rate were greatly improved.
It is worth noting that while enhancing the data application and automated AI approval capabilities, the platform can effectively integrate resources, build a risk control sharing platform, enhance the capability and efficiency of the platform’s risk control, and realize effective control of its own risks. At present, NCF Wealth is actively submitting patent applications in anti-fraud algorithms, credit approval processes, and rapid search and matching of risk information, and making preemptive patent layouts for more advanced technical solutions and industry standards in the future.
Sci-tech Risk Control Talents Are Scarce Mature Team Can Seize the Opportunity
The continuous development of technologies such as big data, artificial intelligence and blockchain has enabled internet financial platforms to have more space in risk control, which puts forward higher requirements for the talents.
At present, nearly 600 enterprises on the market have begun to provide technical services in different aspects of intelligent risk control with “gradient” strength. “Mainly constrained by technical reserves, financial strength, talents, etc., the shift to intelligent risk control faces bottlenecks such as weak products, difficulty in obtaining customers, and backward risk control technology. It is difficult to independently develop intelligent risk control systems,” said an executive of a financial technology company in an interview conducted by Fintech Discovery.
In fact, in the era of intelligent risk control, the competition of technology boils down to talents, and the risk team is crucial. At present, the lack of a strong team is a major problem faced by many financial technology companies. A good team can give the company a great advantage.
Moreover, from the current overall situation, commercial banks that have established wholly-owned financial technology subsidiaries are competing fiercely for scientific and technological talents. However, NCF Wealth is well prepared with a mature risk control team.
According to Fintech Discovery, NCF Wealth’s risk control talents come from the core risk control departments of large commercial banks and internet financial industry. They are equipped with excellent educational background and rich experience in the financial, banking and internet industries. At present, the big data and data modeling team has more than 20 members with rich R&D and management experience in the establishment, operation and maintenance of big data platforms in the fields of data mining, data modeling, artificial intelligence and business intelligence.
NCF Wealth’s artificial intelligence model
Nowadays, with the continuous development of credit business and the continuous iteration of the credit market, innovative financial credit scenarios will keep emerging. So it’s imperative for the risk control business to keep evolving and innovating to adapt to new scenarios and businesses, and deal with new risks and challenges. For example, the dark industries are constantly upgrading their crime tools. Face transplanting technology and face-image making video technology that have mushroomed in the artificial intelligence recently have provided new means for fraud groups or black mediators to commit crimes. In this regard, NCF Wealth’s risk control team is exploring new biometrics such as voiceprint to prevent identity theft and other fraud.
In terms of the traditional face recognition and living body detection methods, the team is studying how to prevent various types of forged images or video attacks by constructing a special deep neural network architecture. In addition, internal business data accumulation is employed to build the model sharing ecology.
“NCF Wealth’s risk control team hopes to trace and verify the identity and information through the relationship between higher-dimensional users, and increase the cost of fraud; it hopes to continuously optimize the bottom frame of the knowledge graph and relation network technology, so as to update the T+1 risk warning response to an almost real-time one,” said NCF Wealth to Fintech Discovery.
However, more explorations still need to be made in risk control. Finance has all the basic conditions for integration with artificial intelligence. The new risk control model is essentially the organic combination of artificial intelligence and big data. However, data is the problem for now. How to get it, which data can be used, and how to use it have always been problems in the industry. Those who can solve these problems better will be invincible.