Psychometric-Based Credit Scoring

Scoring the credit risk of a business involves a review of the balance sheet, cash flow, and current assets added to data related to prior credit history. In developing countries, small businesses, including micromerchants, typically can’t qualify for loans, including credit cards, because lenders lack a comprehensive, financial data-only underwriting model because they have no prior credit history.

LenddoEFL offers a quantitative risk scoring tool lenders can deploy to find good customers among the more than 200 million micromerchants worldwide with little or no prior credit history. The possible revenue to lenders able to safely do business with these prospects is estimated to exceed $300 billion.

LenddoEFL’s risk scoring model utilizes psychometric factors, data science, behavioral economics, social network analysis, and risk analytics. It has been used since 2010, mainly in Asia-Pacific and Latin America, to help underwrite $2.50 billion in loans, including credit cards. Currently more than 50 banks in the Philippines, Indonesia, Malaysia, Thailand, Vietnam, Peru, Mexico, and Colombia are customers.

The company operates its software-as-a-service platform from the cloud. The platform also handles know your customer verification and onboarding. It only operates on a white-label basis, using a client’s brand, logo, fonts, and colors. Clients include banks, insurance companies, and business-processing outsourcing firms.

Several companies offer psychometric-based credit scoring. LenddoEFL was the first to market in 2010. It presents applicants with a questionnaire that takes 20 minutes to complete. Algorithms measure an applicant’s answer patterns for trustworthiness, stability, connections to communications, and more. That gives lenders another risk management analytic to consider and contributes to an increase in loan approvals.

LenddoEFL has collected more than 12 billion data points on an opt-in basis, as well as information on millions of repayments. LenddoEFL algorithms, machine learning, and artificial intelligence use these factors to create a predictive score.

Psychometric-based credit scoring is being deployed in developing markets by retailers, wallet providers, and payment gateway providers. Those companies challenge banks to address the credit gap in emerging markets.

LenddoEFL acquired competitor Entrepreneurial Finance Lab (EFL Global) in 2017.

Paolo Montessori is Chief Executive Officer at LenddoEFL in Singapore, paolo.montessori@lenddo.com, www.lenddo.com.