customer_support · finance · workflow
LSEG uses Amazon Q Business to enhance LCH post-trade client services query handling
LCH's client services team had to manually refer to detailed service and policy documentation to answer complex member queries across diverse asset classes. The team relied on product FAQs and an in-house knowledge center, but needed faster and more accurate information retrieval as their customer base grew.
How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · CS agent submits member query
A client services agent submits a member query via a web-based interface gateway.
Tools used
Amazon Q BusinessAmazon BedrockAnthropic's Claude v2Amazon ECSRAG
Outcome
Amazon Q Business provided LCH's client services team with quick and accurate answers to complex member queries, with responses delivered within a few seconds and high factual accuracy demonstrated in testing, saving time for live agents.
Results
Time savedwithin a few seconds
Volumehigh level of factual accuracy
Grounding & classification
Source type: technical build writeup
30 fields verified against source quotes, 6 dropped as unverifiable.
conversational aienterprise searchknowledge searchragsummarizationknowledge basepolicy documenthuman review describedmetric backednamed customerproduction runtime claimedtools describedvendor confirmedworkflow describedfinancial servicesaccuracy improvementemployee productivityresponse time reductiontime savedtechnical build writeupback office opscustomer supportrag answering