Of the 31 licensed consumer finance companies currently in operation, several have recently disclosed their operating results for the first half of 2026. The sector is undergoing a deep adjustment overall, with the focus shifting from scale expansion to risk clearing and quality optimization.
Industry observers note that the first half of the year saw a distinct pattern emerge among licensed consumer finance firms, where leading institutions reduced their balance sheet size to manage risks while second-tier players filled the gap. The sector has moved away from a pure scale competition towards a focus on quality, with divergence evident across assets, revenue, and profitability. The previous growth model of relying on low-interest promotions to attract customers and hidden markups to generate profits is gradually losing its effectiveness. Market competition is shifting from price battles to a contest of compliance and risk control capabilities, and institutions that do not comply with regulations will see their space for survival narrow, accelerating the pace of industry consolidation.
During the period, Ant Consumer Finance reported total assets of RMB 318.55 billion and revenue of RMB 10.915 billion, with a net profit of RMB 1.942 billion. Zhaolian Financial had total assets of RMB 147.356 billion, revenue of RMB 6.688 billion and a net profit of RMB 1.381 billion, with its credit impairment losses down 18.48% year-on-year. Msxf Consumer Finance reported a 54.78% quarter-on-quarter increase in net profit for the second quarter, a result of simultaneous reductions in acquisition, client operation, risk control and operational costs. By the end of June, its key early delinquency rate hit a historical low, and net assets increased to RMB 15.7 billion.
The balance sheet reduction observed among leading firms confirms that the old logic of prioritizing scale above all else is being broken, and scale is shifting from being a source of profit to a potential source of risk. The three previously held assumptions that high interest margins, delayed risk exposure, and high rates covering high risks are all failing simultaneously. The industry now faces narrowing interest spreads, a concentration of historical non-performing loans maturing, and regulatory limits on using high rates to offset high risks.
By the end of June, Bank of China Consumer Finance had registered capital of RMB 1.514 billion, total assets of RMB 76.891 billion, net assets of RMB 9.614 billion, and a loan balance of RMB 75.296 billion. The company achieved a net profit of RMB 299 million in the first half of the year. China Post Consumer Finance reported total assets of RMB 76.794 billion and net assets of RMB 8.025 billion, achieving revenue of RMB 4.211 billion and a net profit of RMB 570 million during the reporting period.
Amid the overall pressure on the industry, two institutions managed to achieve growth in both revenue and net profit. Nanyin BNP Paribas Consumer Finance posted revenue of RMB 3.22 billion in the first half of 2026, a 17.5% increase year-on-year, while net profit rose approximately 22% to RMB 175 million. Ningyin Consumer Finance achieved revenue of RMB 1.792 billion, up 6.29% year-on-year, and net profit of RMB 264 million, up 5.60%. In contrast, some institutions are trapped in a scenario of rising revenue without a corresponding increase in profit. Jincheng Consumer Finance saw its revenue grow 16.5% to RMB 657 million, but net profit declined 49% to just RMB 56 million.
The banks backing the successful second-tier players, Bank of Nanjing for Nanyin BNP Paribas and Bank of Ningbo for Ningyin, have provided them with lower-cost funding and an existing customer base, serving as a strong moat in a tightening market. Their path choices and risk appetites also played a part, with Ningyin issuing over 60 public tenders in the first half of 2026 to systematically build out its proprietary business capabilities, while Nanyin BNP Paribas derives close to 90% of its business from its own channels.
In fact, actively reducing scale has become a common strategy among many institutions. In the past six months, several firms have mentioned proactive scale reductions. Msxf Consumer Finance deliberately tightened and controlled its scale based on the market risk environment, having adjusted and hardened its risk control strategy and moved to a higher-quality customer mix in the fourth quarter of 2025, which also led to asset management controls. Other institutions have disclosed plans to reduce total scale in 2026, aiming to build capabilities for low complaint rates and core risk control.
This is also a window of opportunity for the industry. The proactive contraction of leading players is ceding market share, and the growth of second-tier platforms is a mix of their own efforts and the strategic retreat of their larger competitors. However, the industry structure will not be completely reshaped, as head institutions still hold obvious advantages in funding costs, shareholder resources, and customer base, and their scale reduction is more of a proactive risk control measure. Mid-tier institutions can seize market gaps to increase their size, but their overall ceiling is limited by funding capacity, risk control systems, and acquisition channels. The industry is shifting from a scale-centric approach to one of divergence: head players focus on refined operations, mid-tier players compete for niche markets, and tail-end institutions face increasing survival pressure.
As the regulatory framework for consumer credit continues to improve, a series of policies that standardize practices are accelerating the restructuring of the sector. The new rules on loan assistance, which took effect in October 2025, regulate the business conduct of banking institutions in this area and are driving the clearing of high-risk customer groups from the market. Regulations effective from August 1st mandate the transparent disclosure of comprehensive financing costs, requiring a detailed breakdown of all fees charged by the lender and its partners to calculate the annualized comprehensive cost for borrowers under normal repayment conditions, with no other fees to be collected beyond those disclosed. Further rules effective September 30th govern online marketing of financial products, stipulating that organizations or individuals other than financial institutions and third-party internet platforms are prohibited from conducting or indirectly conducting such marketing.
Meanwhile, several local regulators have issued quantitative guidance on core metrics such as the scale of loan assistance channels, the proportion of assisted loan business, and the weight of financing guarantee business. They are also providing clear guidance on the average loan pricing for consumer finance companies, strengthening risk prevention and compliance from the source. One practitioner in the southeastern region noted that due to local regulatory requirements, his company had already lowered its interest rates to below 20% several years ago, and the current industry changes have little impact. Another frontline worker at a consumer finance company in North China said that their firm is actively shrinking its assisted loan business, with the publicly advertised rate of 24% being the actual rate applied. However, some assisted loan platforms in the industry target a further sub-prime customer base and can charge additional fees under the guise of credit information services, bringing the comprehensive financing cost to 36%. While this is a common industry practice, his company, as a licensed institution, strictly adheres to the 24% cap.
The weighted average rate at his company has been reduced to 21% to 22%, and they are seeking to move closer to 20%. Although there is no official document forcing a reduction below 20%, the window guidance is clear. Publicly disclosed product rates remain predominantly at 24%, and only a few institutions have lowered them to 20% or 18% to benchmark against credit cards. He further explained the two main cooperation models with loan assistance platforms: a pure traffic referral model where the platform directs users to the consumer finance company's own platform, and an API model where users complete loans directly on the platform's interface, with funding from the consumer finance company, initial risk assessment by the platform, and a second credit check by the finance company. Leading institutions are now successively disclosing their partner lists, driven mainly by stricter regulation and risk incidents in the assisted loan space.
The market is also shifting. The formal takeover of Zhongbang Bank and risk incidents involving certain platforms, combined with the stricter regulation and scale compression of assisted loan cooperation by banking institutions, have led to a general contraction in the business of small and medium-sized assisted loan providers. The industry model of using high pricing to cover high risks will become further constrained. Pricing ranges are being compressed, and the compliance costs of channel marketing are rising. From the second half of the year into next year, institutions will continue to adjust their customer mix towards lower-risk groups, re-examine channel cooperation models, and see a continuous clearing of non-compliant assisted loan partnerships. The standardization of product disclosure will compress industry profit margins, and the gaps in risk control and capital strength between institutions will widen, potentially increasing transformation pressure on smaller players.
Looking ahead, for institutions to achieve sustainable and healthy development, they must strengthen compliance, proprietary customer acquisition capabilities, independent risk control systems, and consumer protection. Those with a first-mover advantage in these areas are better positioned to be proactive and are likely to effectively seize the market opportunities that emerge from the industry's adjustment, ushering in a new development window.
As the industry pivots towards high-quality development, AI large models have become a key tool for consumer finance companies to rebuild risk control capabilities and reduce costs. Zhaolian Financial has released the industry's first open-source large model, which transitions applications from simple model fine-tuning to agent-based uses that combine model and engineering capabilities. In risk control, Msxf Consumer Finance's real-time decision system uses multi-dimensional data like voiceprints and behavioral patterns for multimodal analysis, cross-referencing against a database of tens of millions of fraud voiceprints. Its anti-fraud interception rate has improved to over 99.9%, and the iteration cycle for its anti-fraud model has been shortened from 90 days to one day, moving risk control from post-event tracing to pre-event warning.
To address the insufficient use of traditional risk control data, Haier Consumer Finance has built a multimodal feature processing platform that handles text, time series, images, and voice data. Using several fine-tuned professional large models, it automatically extracts high-value risk features from unstructured data. For example, it has developed a dedicated large model for interpreting credit reports, trained on credit report data, which can identify deep characteristics such as liability health, credit behavior patterns, and potential stress signals. CITIC Consumer Finance has established a full-process intelligent risk control system and is simultaneously accelerating intelligent upgrades on its operations side, with multiple AI application projects being rolled out in business, customer service, and operational scenarios, using automation to replace repetitive manual work and continuously improving overall operational efficiency.