Hang Seng Bank (ESG) has collaborated with Wizpresso to leverage its Valuelytics platform for ESG financing assessment. Valuelyticss, underpinned by cutting-edge generative AI technology, streamline the benchmarking and evaluation processes for green and sustainability-linked loans (SLL).
What motivates Financial Institutions to use AI?
Credit and lending products, on average, take up more than 70% of commercial banks’ revenues. Banks analyze various financial and non-financial data before approving corporate loans. These credit-related data may be sourced from traditional and alternative sources. They may vary in type depending on the sector classification of the borrower, leading to the majority of data being reported in multiple formats. Credit analysts and relationship managers then use the credit-related data to generate credit reports for subsequent credit review and documentation. The unstructured nature of credit-related data hinders a bank’s ability to efficiently evaluate a company’s creditworthiness or benchmark against previous credit records – leading to lengthy credit processing lead time and increased operational risks.
As a result, many banks have begun exploring transformative technologies to address the following pain points throughout the credit assessment process:
- Speed – Long lead times in the credit approval process can hinder customer experience and limit the amount of credit a bank can distribute. Increasingly, qualified and high-quality borrowers seek reliable and trustworthy banking partners to channel their funds more efficiently and rapidly, making speed-to-approval a top priority for financial institutions.
- Accessibility – Historical data may have substantial analytical value but is not easily accessible as they are stored in unstructured formats. Without AI, it is challenging for a bank to easily search and categorize data based on various criteria. The lack of digitized and structured precedents hinders the bank’s ability to reference previous credit decisions and benchmark companies.
- Data Risk – Data collected during the credit assessment may vary across sectors and can be analyzed in siloes by various teams, leading to potential blindspots throughout the lending cycle. As data is manually gathered, segmented, and stored, human errors can potentially occur.
How can AI accelerate Green Financing Assessment?
Similar to traditional credit assessment, a bank will analyze hundreds of ESG reports of a borrower and its peers when assessing a green financing opportunity. Through the assessment, the bank can set constructive ESG requirements and objectives as part of the green loan. These ESG reports can have up to several hundred pages, are unstructured, may contain multiple languages, and are stored in various formats, including PDF, Word, RTF, Excel, and more. For every review, the green financing team must manually extract relevant information, including key ESG policies, commitments, reported data, and more, to evaluate the borrower’s ESG performance and eligibility.
Applying new data sources, advanced analytics, and machine learning technologies can streamline processes, increase the accuracy of risk models, and enable banks to make holistic and data-driven decisions.
Wizpresso collects thousands of company disclosures, including ESG reports, daily. Our AI processes information in real time and transforms unstructured information into embeddings using transformer-based deep learning techniques. Using pre-trained models, our platform can evaluate these embeddings to generate grounded answers that can be traced back to the source document or passage for verification. Our model comprises over 250 ESG indicators and requirements to score and benchmark ESG disclosures, streamlining the entire research process by more than 80%.
Apart from green financing workflows, companies can utilize Valuelytics to compare their ESG performance against selected peers. Users can efficiently benchmark their ESG policies, commitments, and initiatives against industry best practices and plan for new projects in the future.
We are pleased to see Hang Seng Bank embracing technology to drive and enable their clients’ ESG journey. Using Valuelytics in ESG financing advisory effectively brings innovation to traditional banking. Hang Seng has always adopted a co-creation approach that creates value with customers collaboratively. This use case demonstrates how FinTech can enable a greener future.
Learn more about Valuelytics