Gen(AI) on the prize – How GenAI is revolutionizing lending, and what APAC banks should do next

In this edition of Banking Perspectives, we dive further into how generative artificial intelligence (GenAI) is transforming lending, enhancing operational efficiency and improving decision-making.

We speak with Yi Chen, Managing Director, APAC-Middle East region for Moody's Banking to discuss the capabilities of GenAI from loan origination to portfolio monitoring, specifically in the APAC region – and what banks can do now to start reaping the benefits.

Q: Thank you for your time, Yi. Let’s start by discussing the banking industry as a whole. How do you see GenAI transforming traditional banking practices?

Yi: AI is not completely new to the banking industry – some banks have been leveraging this technology for years, especially in the data analysis, risk measurement, and predictive analysis space.

However, today, the banking sector is at another transformative crossroads – driven by the rapid advancement of AI and its sub-technologies like GenAI, AI agents, agentic workflows and machine learning. Traditional banking processes, especially in commercial lending, are often manual, labor-intensive, and prone to errors. AI-led solutions offer a powerful alternative by helping to automate these tasks and minimize manual work - fostering improved consistency, efficiency and timely decision-making.

Q: Can you tell us more about the benefits that GenAI can bring to lending operations?

Yi: Take credit assessments, for example. AI can analyze and summarize unprecedented volumes of data, including both well-structured data, such as financial statements, and alternative data sources like social media sentiments, news streams, and utility payment histories. This not only helps to speed up the credit assessment process but also provides a more nuanced, real-time understanding of credit risk, which is crucial for making well-informed lending decisions. 

Additionally, AI can enhance loan portfolio monitoring by continuously analyzing portfolio data to identify potential risks early, ensuring timely interventions and better risk management.

In today's digital age, banking customers expect seamless and personalized experiences. GenAI can also accelerate the application process all the way to loan approval, enabling banks to make quicker, more informed decisions and tailor the banking experience to meet individual customer needs.

Q: Loan origination involves multiple steps, from gathering customer information to assessing risk and granting approvals for loans. What operational gains might GenAI bring to the loan origination cycle?

Yi: GenAI can streamline the loan origination process by automating repetitive tasks and reducing approval times. For example, automated spreading solutions can swiftly analyze financial statements, providing insights and reducing the time required for manual data entry. In underwriting, GenAI can offer a comprehensive view of a borrower's creditworthiness, allowing for faster and better-informed credit decisions.

The role of entity verification and know-your-customer (KYC) is crucial in supporting compliance and reducing fraud risk. GenAI can automate these processes, ensuring that necessary checks are completed efficiently and effectively. This not only helps to speed up the loan origination process, but also enhances the overall security and reliability of lending operations.

Q: Banks are gradually transitioning from experimentation to the development and implementation of GenAI use cases. What unique challenges do banks in the APAC region face when integrating GenAI into their operations?

Yi: The APAC region faces a unique set of challenges and opportunities when it comes to integrating GenAI. One of the primary challenges is the diverse regulatory environment across different countries, which can complicate the implementation of standardized AI solutions – such as in the case of data and model security-related regulations.

The varying levels of digital maturity among banks in the region can also impact the pace of AI adoption. For example, SaaS technology is not widely adopted, and this is a key foundation for GenAI deployment.

Q: What recommendations would you offer to banks in the region, as they seek to address these challenges and harness the potential of GenAI in their organizations?

There are several recommendations that can help banks reap the benefits of GenAI while ensuring a measured approach to integration. It's crucial for banks to take a step-by-step strategy rather than rushing into a large deployment. They might consider:

1. Collaborating with technology partners and industry peers to stay ahead of the latest developments and implement best practices in AI adoption.
2. Investing in enterprise-wide GenAI education, so that all stakeholders understand the potential and limitations of these technologies.
3. Designing new operating models that allow for a controlled mix of human and technological interaction, ensuring that AI complements rather than replaces human expertise. “Human in the loop” is the key to success.
4. Focus on building robust data governance frameworks to support the integrity and reliability of the data feeding into AI systems. This includes addressing issues like algorithmic bias and data protection. Technology vendors, many of whom have already developed strong governance protocols, can help banks to grow.

Adopting GenAI-powered solutions will be one of the essential drivers for banks to remain competitive in this dynamic landscape and will help them meet the evolving needs of current and future customers. By leveraging vendor expertise, investing in governance and reviewing operational models, APAC banks will be well-positioned to successfully integrate GenAI into their operations. This approach not only enhances competitiveness, but also improves customer experience and drives sustainable growth.