background
A pricing sheet is a real-time debt scenario used to evaluate potential new debt issuances. Prepared by junior bankers, these documents are sent to clients weekly as market updates or included as part of a larger deal deck. Their accuracy is critical as they directly inform client decisions on timing and structure of new bond issuances.
problem
Generating a pricing sheet required junior bankers to manually check and re-enter data across four separate systems — a process that took approximately 30 minutes per sheet. Beyond the time cost, manual data entry introduced the risk of human error in a context where accuracy is non-negotiable. There was no single source of truth, no way to catch anomalies at a glance, and no standardization across the team.
How might we automate the bond pricing process to reduce manual data entry, improve accuracy, and give junior bankers a single source of truth?
Current process
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New end-to-end process
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End-to-end lo-fidelity prototype
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Final deliverables
The Bond Pricing System consolidated the fragmented workflow into a single platform. The solution comprised three core components:
Automated comparables set creation
Data is pulled and populated automatically from verified sources, eliminating manual re-entry across systems.
Data visualization layer
Visual representations of pricing scenarios allow bankers to identify anomalies at a glance, rather than reading through raw numbers line by line.
Unified workflow
A single surface replacing the previous four-system process, reducing cognitive load and standardizing output across the team.
Outcome
The Bond Pricing System pilot launched for USD pricing. Time to complete dropped from 30 minutes to 10 minutes — a 66% reduction. Data accuracy improved through auto-population from verified sources, reducing the risk of manual entry errors. We are currently gathering feedback from the pilot to incorporate into the next phase, as we expand to additional currencies and lines of business.