[DigitalToday reporter Lee Ji-young (이지영)] KakaoPay applied its proprietary alternative credit scoring model, "KakaoPay Score", to the Korea Housing Finance Corp’s screening for jeonse loan guarantees. It plans to use AI-based credit assessment leveraging mydata and payment data to improve financial access for thin-file customers and sole proprietors with limited financial histories.

KakaoPay said on Tuesday it introduced KakaoPay Score, jointly developed with Korea Credit Bureau (KCB), into the Korea Housing Finance Corp’s jeonse loan guarantee process.

KakaoPay Score is an alternative credit scoring model that combines remittance and payment data with mydata such as asset information. It is designed to analyse users’ actual repayment capacity using AI machine-learning techniques.

The company said it uses its base of more than 22 million mydata subscribers as well as payment and remittance data to analyse users’ financial behaviour patterns from multiple angles and predict risks with greater precision.

It expects financial access to improve in particular for thin-file customers who have been disadvantaged under existing credit scoring systems due to limited financial histories. It said reflecting mydata-based asset information has increased the likelihood that they can be reassessed as creditworthy customers.

The Korea Housing Finance Corp expects the adoption to enable a more multi-dimensional assessment of the repayment capacity of potential customers that has been difficult to capture under existing evaluation criteria.

A KakaoPay official said, "Based on the data competitiveness held by the platform, we are expanding new financial opportunities for customers who have been left in existing blind spots in finance," adding, "Through various collaborations, we will lead the alternative credit assessment market."