During the loan process: Difficult to abandon manual review

Business Management

The loan process is viewed as the risk taker and operator after credit approval, serving as the link between pre-loan and post-loan risk transmission.

◎ Risk Control Model Development

Based on feedback, all 16 surveyed consumer finance institutions mentioned building real-time credit approval systems using technologies such as artificial intelligence, cloud computing, and big data. Additionally, three institutions use a combination of traditional manual processes and risk control systems.

Dynamic Risk Management

Building Digital Infrastructure

◎ Debt Repayment as a Key Focus of Risk Control

According to the information provided by the 16 consumer finance institutions, they comprehensively assess users’ repayment ability during the loan process based on multiple dimensions such as credit history, asset status, and consumption stability.

Comprehensive Assessment of Repayment Ability

Multi-dimensional Data

Constructing balanced risk models and strategies related to access and pricing during the loan process relies on advanced machine learning algorithms and rich data sources.

◎ Data Usage and Collection

Regarding data sources, the 16 surveyed financial institutions mainly utilize internally accumulated vast amounts of user data combined with deep integration of foreign exchange market data. Leveraging the advantages of borrower data accumulation, they perform in-depth data mining on complex business scenarios and large datasets (603138) to gather various risk-related data.

Precise User Profiling

Multi-source Data Collection

◎ R&D Progress and Achievements

Based on feedback from the 16 institutions, due to differences in scale and revenue, there are also significant disparities in R&D investment and technological achievements.

Notable Anti-fraud Results

Polarized Patent Achievements

Business Development Challenges

In addition to differences in technological investment, each consumer finance institution has varying insights into the difficulties faced in loan operation and their solutions.

◎ Incomplete Evaluation Data

Currently, domestic income, debt, and credit data are not fully developed, which hampers consumer finance institutions’ ability to effectively assess users’ repayment capacity.

Solution: Continuously introduce accurate third-party income and debt data, develop income and debt verification models, and enable rapid and effective verification of borrowers’ repayment ability.

◎ Contradiction Between “Universal” and “Preferential”

Against the backdrop of overall interest rate reductions in the consumer finance industry, the contradiction between “universal” and “preferential” offerings has become more apparent. Increasing market competition also demands more refined management of existing customers, including more precise pre-emptive risk control and enhancing user stickiness.

Solution: Continue digitalization efforts to improve customer acquisition efficiency and reduce manual costs through technological means, addressing challenges in business expansion.