The feedback from Chief Risk Officers (CROs), who are using our Knowru product dedicated to financial risk management, has given our team valuable input and understanding of their unique risk management methodologies, the underlying factors involved in the impact of each, as well as differences among different countries.
One key discovery made in my time spent with various CROs, is that there is no such thing as universally applicable management methodology for all scenarios. On the contrary, solutions must be tailored for the specific regulations, data-management and communication flow in a particular country. While this presents itself as the not the most user-friendly option, it is of course a required necessity in order to meet the goals and measurement standards set forth by the CROs and governing authorities.
As more companies join our team in using Knowru for their financial risk management with respect to lending products, differences across countries caught our attention, which has come about during the collaborative work with global CROs in understanding their unique risk management methodologies and the underlying factors behind each of their implications, as well as the differences between them.
The main lesson here, which will be imparted in the concluding section, is that ‘when it comes to management methodology, there is no such thing as one-size-fits-all’. Solutions remain bespoke as CROs focus on the understanding of their own situations and evaluate the actions and results. This ensures, at the very least, that their measures are understandable and appropriate, though this may not present itself as the most user-friendly option.
Let’s explore three key differences below that highlight country-specific requirements.
Credit Data Management
ID verification.
• Not all countries are using ID numbers in their systems. For example, in the United Kingdom (UK), a lending company has to use a combination of information, such as name, date of birth, address etc., to identify an applicant and pull credit data from 3rd party sources.
Credit data management entities.
• Other than 3rd party sources, there are other credit vendors available. For instance, the People’s Bank of China, the only valid source of personal credit reports in China. It is a government agency that collects all the financial information. However, getting access to these data protected by regulations and procedures can be very difficult. In the United States (US), major credit agencies (Equifax, Experian and TransUnion for example) all operate as private, for-profit entities.In 2012, the Consumer Financial Protection Bureau (CFPB) began supervising these agencies at federal level. As a financial institution can only provide report to individual agencies, the amount of data and evaluation on an applicant may be different across these agencies over time.
Credit data storage.
• In South Korea, in order to protect the applicants’ personal information, financial institutions are not allowed to keep credit data of applicants who have been rejected for approval.
Consumer Behavior
Payment methods.
• In the US and South Korea, people mostly use credit or debit cards to make payments for purchases. But in China, a significant number of people use smartphone apps, such as AliPay or WeChat Pay, that are connected to the users’ bank accounts. By contrast, in South East Asian countries, most people continue to use cash as their primary means of exchange, which influences a credit agencies’ cover rates. For example, an Indonesian credit agency’s cover rates, as defined in acquiring any form of data on an applicant, might not reach 40% and even with that, the provided data might not fully describe the applicant’s credit history.
Communication methods.
• In China, people rarely use emails to communicate personal matters. As a result, risk management measures based on email addresses, such as using email addresses for registration/verification purposes or checking email histories won’t be as effective in China.
Laws, Regulations and Government Policies
• In the US, discrimination is of great concern when it comes to the subject of credit approval. Lending companies is obligated to prove that any given lending decision is not discriminatory in nature and is based (solely) on its prediction regarding an applicant’s credit performance.
• Because of this requirement, companies tend to employ more explainable methods to address approval ratings such as regressions and score cards.
• In China, cash loans are not allowed. With that, a lending product should be designed to serve particular purposes, such as buying electronics or furniture, paying for travel expenses, etc. Plus, markets providing these different types of goods vary (e.g. consumers applying for lending products with the purpose of receiving plastic surgeries are different from those purchasing smartphones). This scenario requires CROs to study each market’s participants, trends and consumer behaviors comprehensively so as to successfully establish risk management strategies targeted for the specific situation.
• In South Korea, the government has significant influences on financial institutions’ lending policies in its effort to achieve policy goals. For example, in the late 90s, it lowered the criteria for obtaining credit cards and promoted the adoption of credit cards among the public in order to boost consumption.
• In the past few years, it issued restrictive policies such as mandating banks to refuse applicants whose financial metrics (e.g. debt-to-income) goes above certain thresholds in order to curb the country’s ever-increasing real estate price.
These examples demonstrate how the landscape for consumer lending products can be different notably at the lending decision stage across countries, which is important for management measures. CROs need to take in account the following factors:
• What data on applicant profiles are important?
• What data is available for analysis?
• How to validate the integrity of collected data?
• How to obtain data that are important and available?
• How to make a decision based on the collected data?
• How to manage decisions and the collected data?
Indeed, even in one single country, a CRO might have to face a situation where he/she is required to manage risks associated with a new product for different consumer groups, within different regulatory settings. These above examples may be able to assist CROs in similar situations to brainstorm key factors in designing their risk management strategies.
Author’s Bio-Ken Park
Creator of Knowru, a cloud-based software platform that hosts Application Programming Interfaces (APIs) for automatic machine learning models, a typical application case of which is data scientists turning their machine learning (ML) and statistical models to APIs.
Ken received his Master of Science (MSc) in Computer Science from the University of Chicago, and Bachelor of Science (BSc) in Applied Mathematics (Honors), and Mathematical Methods in the Social Sciences (Honors), graduating Summa Cum Laude. He is also a graduate of the Kellogg School of Management program for undergraduates in Managerial Analytics.
Before creating his Knowru platform, Ken spent six years as an Analyst with Boston Consulting Group, Houston Police Department and as the Head of Fraud Analytics & Operations with Enova International. Currently，he works in Chongqing, China in a local fin-tech company SimpleCredit as CRO（Chief Risk Officer）leading the department of Risk Control.
Ken holds certifications including Certified Financial Analyst and Financial Risk Manager.
Media Contact
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