Finance / Banking
DBS: Adverse news review
- Company
- DBS
- Country
- Singapore
- Adoption stage
- In operation
- Source published
- Date basis
- The date the source was published. It can differ from the date adoption started.
- How the source was checked
- Read the full source text
The work problem
DBS runs a screening operation that looks at adverse news relating to customers. The bank picked this work out as a target for raising productivity with generative AI. Before that, it needed a standard to tidy up development practices that differed from team to team.
Technology and data
The bank first built a generative AI framework. Reusable components, control mechanisms, workflow capabilities and prompt writing standards were set as the standard. On this basis it built an adverse news screening tool with generative AI. The data is handled by ADA, the bank-wide data analytics platform. The bank said this platform cut code deployment time by 25 percent and reduced the model deployment cycle to under 10 weeks.
Results
DBS said the tool raises productivity in adverse news screening. It is listed as a generative AI case in operation in the CIO letter covering 2025 results. The same letter said more than 2,000 AI models were applied to more than 430 use cases through ADA. Performance figures isolating the screening work were not given.
Limits and open questions
The source mentions this tool in a single sentence. Screening accuracy, handling time and the share reviewed again by people are absent.
Sources
- CIO statement | DBS Bankdbs.com, Accessed
Compiled from public sources. These are not results from ATF Works customers.