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Founding Minds
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Case study · Capital markets

One trading platform. Multiple electronic markets.

Founding Minds built a multi-tenant SaaS platform for municipal and corporate bond trading, bringing inventory, electronic market connectivity, bidding automation, and profit-and-loss tracking into one system. Its rule-based autobidder helps trading desks automate decisions while retaining control over the rules that govern them.

The situation

DRL Group trades municipal and corporate bonds across several Electronic Communication Networks (ECNs), the venues where inventory is listed and bids are placed. Each ECN presents different market information and has its own workflow.

A trading desk needs one view across them. The platform provides it for several trading operations on the same system.

Where the judgement shows

What made it hard

Bringing multiple trading networks together.

Each ECN has its own message semantics and timing behavior. Presenting one coherent view of bonds, bids, and market activity means deciding how the system reconciles differences between networks. Those decisions are a large part of the product.

Keeping trading operations isolated and in sync.

Each tenant’s inventory, live bids, and profit and loss are its own book, so isolation is a trading requirement as well as a compliance one, and it shapes architecture choices. Within each tenant, inventory and P&L stay aligned with trading activity. The P&L module keeps trade details and matches them against later buys and sells, so the record has to stay correct across days.

Automating bids without losing control.

The autobidder executes bids automatically according to predefined trading rules, with configurable capital restrictions and total-bid limits for each desk. It is deterministic by design, with no person in the loop at the moment a bid is placed.

Price, yield, latency, and the daily offer lifecycle.

Traders bid in price or in yield, so the system holds both and converts between them. Performance matters, and every optimization has to be weighed against correctness. Offers that did not trade are taken down from the ECNs at the close and re-uploaded the next day after verification, a daily lifecycle with a gate in it.

What was built

A multi-tenant SaaS platform for bidding and offering municipal and corporate bonds, in three parts.

Unified trading platform

Connects to the ECNs and lists inventory for the offering side. Traders select a bond from inventory and send it out for bids; returned bids are listed against each bid-wanted with the details that matter, such as the highest bid and which venue it came from.

Rule-based autobidder

Executes bids automatically according to predefined trading rules, with configurable capital restrictions and total-bid limits for each desk. Bids can be expressed in price or yield. The behavior is deterministic: a bid is placed because a rule applied.

Trading operations and reporting

An inventory management module, a profit and loss module that matches trades against subsequent buys and sells, offer lifecycle handling at the close of each day, and graphical and printable reporting.

What changed

A unified platform for electronic bond trading

The platform brings inventory, bidding, automated rule execution, profit-and-loss tracking, and reporting into a common environment for municipal and corporate bond trading.

“Founding Minds has transformed the dynamics of our business operations, improving both performance and reliability. The FM team is a reliable resource of knowledgeable experience that provides quality work, communicates challenges, identifies improvements, and maintains efficiency to meet schedule expectations. Founding Minds has gone beyond expectations to learn our business needs that have been essential to our success. I look forward to continuing to strengthen this relationship with the FM team.”
Sara Manning Director of Information Technology, DRL

The engineering decision that mattered

Automating trading is not only about placing bids faster. It requires faithfully representing the rules, limits, and operational practices of a trading desk. The platform’s rule-based approach brought automation into the workflow without making trading decisions opaque.

The sector: Financial Services → Next case study: Recordkeeping and billing →

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