Qudian, PPDai, and fintech

I spoke at a UBS luncheon today, entitled "Online lenders’ great future".

Joe Zhang, Nov. 2017

Summary: The regulatory noise in recent weeks is due to populist backlash (envy). But make no mistake: The sector has vast potential, and the underlying economics is compelling. The noise will subside over time. Expect the friendly regulatory framework to continue. As part of my book tour, I will speak again on this very topic at the Graduate School of the central bank in Beijing (Tsinghua Uni.) on 28 Nov.

 Slide 1. Three types of lenders

* Unlicensed and semi-licensed: thousands of P2P operators, with 200+ voluntary closures each year,

* Licensed: 11,000 traditional microcredit firms licensed by Provinces (210 of which have an online lending licenses),

* Thousands of non-P2P online or offline lenders operate mostly without lending licenses but make loans anyway, or lend via a trust structure or make bank entrusted loans.

* Online lenders equivalent to < 1% of bank assets (< 2 trn yuan vs < 200 trn)

Slide 2. Famine and feast in the industry

 * Ability to access better borrowers,

* Ability to access cheaper funds,

* Ability to ramp up volumes,

* Ability to minimise delinquency

 Slide 3. Regulation today and next year

 * No single rule is in force,

* All rules are for consultation,

* Good guys behave but bad guys are not penalized: selective enforcement

* Potential rules to come: Online lenders must not take deposits, must get a lending license or use a qualified structure, Caps on rates, custodian banks, Caps on loan sizes of RMB 200k on personal borrowers and RMB 1m on corporate loans

* Regulation to evolve slowly

 * China has the most sensible subprime credit regulation in the world, striking a balance between prudential supervision and space for innovation

 Slide 4. Data data everywhere. Which bit is useful?

 * All data shed light on a specific aspect of a borrower,

 * PBOC Credit Bureau data most accurate but do not cover much of the subprime sector

 * Zhima Credit, JD, WeChat and CTrip data are all narrowly-based. WeChat data may be of better quality but cannot be relied upon for big loans.

 * PBOC tried in 2015 to gradually encompass microcredit sector data but gave up soon.

 * Private-sector data services are growing to fill the gap but their quality varies.

 * Hard to find credit data on borrowers’ activities in other omline lending platforms

 Slide 5.   The lure and traps of purchase-based loans

 * Online purchases in credit analysis as a risk control mechanism are overrated,

 * Qudian’s low delinquency owes more to its feedback loop with Zhima Credit (and its small loan sizes) than to its merchandise platforms,

 * Lenders who targeted medical care, beauty parlors, vocational training, travel and weddings have lost big,

 * Loans related to car-purchases have not seen waves of frauds, just yet, but it is early days: depreciating assets + difficulties in collections,

 * Home equity loans will fare better only because housing prices are still rising. Small-sized loans are key,

* Banks are eyeing home equity loans but are handicapped by CBRC

 * Most SME lenders and guarantors have died a death by a thousand cuts

 Slide 6.   Issues for discussions

 * The hangover of online binge: borrowing from multiple sources and social ills,

 * Many operators pretend to have a sophisticated risk control models but are simply shooting in the dark,

 * How many operators will the capital markets absorb?

 * Subprime credit surge has made the banks safer and more profitable,

 * Populist backlash against the sector has limited influence on regulation,

 * The public suffers far more in the stock market, or due to alcohol, electronic games, bad medicine, and cigarettes,

 * Many operators in the credit data, investment platforms, bad debt collections credit software and risk control models sub-sectors cannot resist the fast money the bare-knuckle lenders are making