Company Name:
GLOBAL PSYTECH SDN BHD (1255851-V)
Sector
Digital Agriculture, Digital Services, Digital Cities, Digital Health, Digital Finance, Digital Tourism, Islamic Digital Economy, Government, Telecommunication, Utility and Energy, Manufacturing
Tech Enabler
Artificial Intelligence (AI) and/or Big Data Analytics (BDA)
Support Sustainability or ESG
Yes
Overview:
Discover how our Creditworthiness Analytics solution transformed the conventional credit assessment process for a prominent financial institution. By harnessing the power of AI and machine learning, we provided a more accurate, inclusive, and alternative-based credit scoring model, enabling the client to expand financial access, reduce risk, and increase loan approval rates.
Our Creditworthiness Analytics solution was designed to enhance and complement the existing credit scoring models at the client. The use case demonstrates how our solution enabled the client to more accurately assess credit risk, resulting in improved financial inclusion and significant business growth.
Pain Points:
1. Significant challenges with their traditional credit scoring models, which relied heavily on historical credit data. This approach often excluded individuals with limited or no credit history, such as young adults, minorities, or those in emerging markets.
2. Additionally, the existing models struggled to accurately assess the risk for these segments, leading to higher default rates and missed opportunities to serve potential customers.
Significance: Accurate credit assessment is crucial for maintaining profitability and minimising risk. Traditional credit scoring models often exclude large segments of the population, such as individuals with limited credit histories, which results in lost opportunities for financial institutions to serve a broader customer base. Inaccurate credit assessments can lead to higher default rates as well. In an increasingly competitive financial landscape, financial institutions that fail to innovate in their credit assessment processes risk losing market share to more agile competitors who can better serve underserved markets.
Solution/Services:
General Financial Insights (GFI): Creditworthiness Analytics
Our solution addressed these challenges by integrating AI and machine learning into the alternative credit assessment. It evaluated a wide range of non-traditional data points—such as psychographics data and phone metadata—alongside traditional credit data. This comprehensive analysis allowed the client to generate more accurate credit scores, reducing the risk of default.
Key Features and Functionalities
• AI-powered alternative credit risk assessment to provide a holistic view of each applicant’s creditworthiness.
• Integration of alternative data to enhance credit scoring accuracy.
• Real-time analytics to enable faster decision-making.
• A customizable risk profile using GFI reports allows clients to adjust and decide risk thresholds based on their unique lending requirements.
Implementation:
• API Integration: The GFI system was integrated into the client's existing infrastructure through an API integration. This allowed the client to enhance their current credit scoring process with up-to-date credit scores
• Technology Used: RESTful API Integration
Benefit:
Quantifiable Benefits:
• 90% predictive accuracy in assessing credit risk, based on a customer base of over 45,000
• 50% improvement in non-performing financing (NPF)
• 25% reduction in delinquency rates
Qualitative Benefits:
• Improved financial inclusion
• Enhanced decision-making reduced uncertainty and allowed the institution to better align its credit offerings with customer risk profiles.