Please use the sharing tools found via the share button at the top or side of articles. Copying articles to share with others is a breach of FT.com T&Cs and Copyright Policy. Email licensing@ft.com to buy additional rights. Subscribers may share up to 10 or 20 articles per month using the gift article service. More information can be found at https://www.ft.com/tour. https://www.ft.com/content/ba163b00-fd4d-11e8-ac00-57a2a826423e Does China’s bet on big data for credit scoring work? Ant Financial’s Sesame Credit system for rating individuals struggles to prove itself Share on Twitter (opens new window) Share on Facebook (opens new window) Share on LinkedIn (opens new window) Save Save to myFT Yuan Yang in Beijing DECEMBER 19, 2018 Print this page19 When Ant Financial launched its credit scoring system, Sesame Credit, in January 2015, it said the data-driven product would “make credit more available to millions of consumers across China”, giving individuals access to everything from mortgages to mobile phone contracts to car loans. But nearly four years later, Ant Financial, which is an affiliate of Chinese tech giant Alibaba, has never used Sesame Credit for lending decisions, and critics are increasingly questioning whether the tool can be used to accurately assess individual behaviour. Sesame, which is an opt-in feature of the Alipay mobile payments app, draws upon the biggest pool of non-traditional ratings data in the world. It synthesises details from hundreds of sources — ranging from purchases on Alibaba’s Taobao marketplace to subway fares — into a single trustworthiness number for each user, called a “Sesame score”. But one Ant Financial employee conceded there was a difference between “big data” and “strong data”, with big data not always providing the most relevant information for predicting behaviour, and analysts say the best predictor of whether someone will default on a loan in future is often their previous loan repayment history, rather than their likelihood of returning a rental car. “Banking and transaction data remain fundamental to predictive credit scoring,” said James Lloyd, Asia fintech analyst at Ernst & Young. Martin Chorzempa, a fellow at the Peterson Institute of Economics think-tank, agreed, saying trustworthiness is “very context specific”. “Someone evading taxes might always pay back loans, someone who breaks traffic rules might not break other rules,” he said. “So I don’t think there is a general concept of trustworthiness that is robust.” How it works 1: Sesame’s score and ‘seeds’ 1. Yuan’s Sesame score is 692, or “excellent”. Scores are graded on a scale of 350 to 950. 2. Yuan has one “Sesame seed” — obtained by using an Alipay credit service — and eight tasks to complete before earning a reward. 3. Yuan’s transaction history shows that she satisfied contracts with public transportation providers and Ofo, the ride-hailing app, this year. Critics have also questioned how Sesame crunches thousands of data points into a single score, saying there needs to be a strong correlation between hundreds of different behaviours — from trashing a hotel room to stealing a mobile charger — in order for the metric to be meaningful. “For one score to resolve everything, this is too big a burden,” said Liu Xinhai, a researcher at Peking University’s Centre of Financial Intelligence Research. ‘Adjusting our focus’ From 2015 to 2017, Sesame offered credit ratings services for other fintech companies, including Qudian, one of China’s biggest online lenders. But their ambitions were cut short last year when the Chinese government cracked down on high-interest lenders, clearing out many of their clients. Then, earlier this year, China’s central bank stopped allowing independent companies to provide credit ratings, and required all credit ratings to be given by a new public body called Baihang — effectively ending Sesame’s credit ratings business altogether. “We’re adjusting our focus,” said Zhao Xing, former chief data scientist of Sesame Credit who is now Alipay’s senior algorithm expert. Sesame’s business now relies on tie-ups with hundreds of other companies. When a company joins the Sesame platform, it gives Sesame some of its user data, which helps inform Sesame scores. In return, Sesame helps the companies decide how likely different users are to violate their contracts. The companies often give perks to users with a high Sesame score, such as deposit-free rentals for umbrellas, bicycles or even apartments. Ant Financial will regularly promote the discounts on the Alipay mobile payments app. But Shazeda Ahmed, a PhD candidate studying the company at the University of California Berkeley, said that in many cases, people were unaware that Sesame scores could not be used to take out loans — raising questions about whether Sesame Credit was “manipulating people into giving up data for a use that not related to scoring”. “When users talk about Sesame on social media it’s almost always about how to improve their scores, with loans being one big attraction,” she said. Perks for customers with high Sesame scores 1. Users with high Sesame scores can rent digital equipment without a deposit from retailers such as zFrontier, which provides e-sports equipment. 2. Users with high Sesame scores can also use travel services without a deposit, including car rentals from Avis and others. Analysts have compared the platform to a glorified loyalty card, rewarding users for buying Alibaba’s and its partners’ products, but not predicting behaviour. “Sesame Credit should not be seen as a credit score,” said Mark Natkin, managing director of Marbridge Consulting in Beijing. “It seems to be based on lots of variables that are more importantly indicators of your activity on Alibaba’s different platforms, and could be argued are not actually the most important factors in determining creditworthiness.” But Ant Financial has defended the system, with Mr Xing insisting that by monitoring users, Sesame Credit incentivises people to be more reliable. ‘Building a trustworthy society’ Sesame Credit has frequently been linked with the Chinese government’s ambitions for a “social credit” system, using big data to evaluate citizens’ trustworthiness. But while the two are often conflated — Sesame used to advertise itself as “building a trustworthy society”, and is regularly praised by state media for building the foundations of a social credit system — they are formally separate schemes. Nevertheless, Sesame is one of several tech companies sharing data with the National Development and Reform Commission, the “central planner” responsible for the social credit system, which is currently being tested as a pilot program in dozens of localities. The local government of Suzhou, a city near Shanghai, has also said that since last year, it has been preparing a points system called “Osmanthus points” with Ant Financial. A source close to Ant has denied any involvement in the scheme. As with other pilots, the scheme in Suzhou is likely to reward citizens for behaviour deemed “positive”. Like Sesame, the scheme will draw on many dimensions of data to create scores. However, unlike Sesame, it will produce four numbers: a basic score, plus one for “abilities”, one for “property”, and one for “moral character”. But Dai Xin, professor of law at Ocean University of China, warned that such schemes, like Sesame, were not likely to predict individuals’ future behaviour. “As with the Sesame Credit scores, it’s difficult to design possible social credit scores that have predictive ability across different contexts,” he said. “Will a plagiarising student also commit fraud? Will a company that fails to pay a debt also renege on a building contract? It all requires empirical testing, and we haven’t yet seen this.” Additional reporting by Yizhen Jia in Shanghai