Fintech companies are tracking customer behavior as a data element, and much can be learned from social media in developing a KYC profile.
For many years, human resource departments have been using data from social media sources to profile potential employees. These same sources can be used by bankers to make lending decisions.
Bank product development teams are now working with fintechs to aggregate data from Twitter feeds and other social media outlets to know the customer better and determine if the bank wants them as a client. If the customer profile does not match the lender’s requirements and standards for what constitutes a good client, the client may be dropped completely.
Financial institutions need to develop the model for their core values and evaluate customers based on those values. Customer attributes need to be identified and mapped to the FI's criteria for what constitutes a good candidate. Geocoding, for example, can enable FIs to track customer travels to foreign countries. If the customer is visiting places that do not align with the FI’s core value, this data can be factored into the FI's risk assessment on that customer.
Building these customer profiles entails drawing information from new or previously untapped sources such as payment transaction history, social media, and financial documents. FIs may need to buy data to fill in the gaps about other aspects of the customer’s creditworthiness.
Fintech applications for data aggregation enable FIs to dig even deeper into the data by taking raw data and applying machine learning and AI to calculate new customer profiles. Visa made a big foray into the data aggregation business with the acquisition of Plaid, whose technology accesses customer banking account data and aggregates it for use by financial service providers.
New credit models using third-party applications and APIs will be needed. FIs will also make fintech investments in the form of new risk-scoring models for this purpose.
The economic downturn could potentially have significant repercussions on the loan portfolios. Evaluating a customer’s creditworthiness based on credit score alone just will not cut it. Understanding the customer from a risk management perspective will help to circumvent the challenges of assessing creditworthiness at a time when historical risk parameters may not be indicative of customer’s ability to repay. The end goal is to strike the appropriate balance between risk and data to increase FIs’ confidence in lending. Factoring in customer behavior as an element in the risk profile can provide FIs with better assurances in their lending practices.
This is the second of two parts. Maria Arminio is president and CEO of Avenue B Consulting; and Bo Berg is founder of Hygge Consulting Corp.
