GenAI solution to automate credit memos

Developed by GFT Spain together with Oliver Wyman
20 September 2024
The Credit Risk Assistant utilises advanced techniques such as GenAI to enhance the credit memos in banks. It automates the processing of different data sources and provides the insights that analysts require to create these reports.
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Automated process

Benefits

Efficiency

Quality and consistency

Transparency

Features

Credit Risk Assistant interface with a document upload feature. The drag-and-drop functionality allows users to upload relevant files to enhance credit memo sections.

Data and metadata upload and storage

Embeddings are generated for the uploaded documents and loaded into a database. Metadata is used to categorise / associate data with companies, sectors, etc.
Uploaded files are stored in the cloud. The generated files are stored in the database by sections, and the PDF is generated based on these sections.
A preview of the Credit Risk Assistant tool's "Create a New Memo" screen. Users can review, update, and regenerate credit memo sections with relevant financial data.

Document generation

Able to generate tailored documents made of different sections. Data uploaded can be associated with the different sections.
Screenshot of a credit memo document management interface where users can view, download, and delete associated documents.

Traceability

Provides traceable sources for the content generated in each section, ensuring transparency and accountability. Also provides a confidence score for the sections produced.
Credit Risk Assistant's integrated chat support feature, assisting users in real-time with credit memo creation by answering financial and company-related queries.

Human in the loop

There is a chat where an operator can make adjustments via chat to improve tool responses. It can also be used to query the uploaded documents.

Multi-language PDF export

Credit memo documents are exported to PDF for their subsequent analysis. Able to generate the reports in multiple languages (all supported by LLMs).

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