Six ways we keepchange from breaking.
Each one starts with a problem we've seen more than once and ends with things you can hold: a requirements pack, a control design, test evidence, a signed-off release.
Trade lifecycle change, front to back
From pre-trade data to settlement, specified without ambiguity.
The problem. A lifecycle change can break before an order is placed or long after it is captured. Unclear pricing and reference data, fragmented identifiers and undocumented hand-offs create execution, settlement and reporting risk.
Where you might be. A new product or platform change connects pre-trade data, order and trade capture, post-trade processing, and downstream risk, finance or regulatory reporting across multiple teams.
What we do
- Map current and target workflows from market data, pricing and instrument/security master through order and trade capture to downstream reporting.
- Specify trade data-quality controls and execution interfaces, drawing on working knowledge of FIX messaging.
- Define allocations, confirmations, matching, netting, settlement and fails rules for cash products and OTC derivatives.
- Specify DTCC / Deriv-SERV, MarkitWire and SWIFT MT5xx hand-offs, with testable requirements and exception ownership.
What you'll have at the end
- Front-to-back current / target-state lifecycle maps
- Interface and exception specifications
- Traceable requirements and control matrix
- Business scenarios and readiness checkpoints
Market data platforms & vendors
Know what you license, who uses it, and what it costs.
The problem. Pricing, market and reference data feeds accumulate faster than the understanding of who consumes them. Coverage gaps, overlapping licenses and unclear entitlements create avoidable cost and delivery risk.
Where you might be. You are onboarding Bloomberg, LSEG, Fenics or Tradeweb, reviewing a platform estate, or rationalizing vendors without disrupting critical consumers.
What we do
- Inventory vendors, pricing and reference data feeds, consumers and contractual usage boundaries.
- Assess instrument/security master coverage, cross-vendor symbology and source-precedence rules.
- Specify onboarding, distribution and entitlement requirements.
- Identify licensing overlap and rationalization options for commercial review.
What you'll have at the end
- Vendor, feed and consumer inventory
- Coverage and entitlement gap analysis
- Onboarding and mapping specifications
- Prioritized rationalization roadmap
Data governance & quality
Controls your auditors and your analysts can both trust.
The problem. A data lake is not governed simply because the data has landed. Missing ownership, inconsistent definitions and silent quality failures undermine trust.
Where you might be. Pre-trade, execution, post-trade, risk or finance domains are being onboarded to a data lake, governance checkpoints are unclear, or incident reporting relies on manual discovery.
What we do
- Define ownership, critical data elements and domain-onboarding checkpoints across the front-to-back lifecycle.
- Specify source-to-consumer lineage and measurable quality thresholds.
- Build SQL / Python validation with automated alerts and exception ownership.
- Establish evidence and reporting for governance decisions.
What you'll have at the end
- Domain-onboarding and governance checklist
- Data dictionary and lineage maps
- DQ rule library and alert specifications
- Ownership, controls and incident framework
Regulatory & reporting data
Reporting data that reconciles before regulators ask.
The problem. When a reported field cannot be traced back to a controlled source, every reconciliation becomes a debate rather than a repeatable check.
Where you might be. Risk, finance or regulatory reporting change under BCBS 239, EMIR, Dodd-Frank or MiFID II requires clearer definitions, reconciliation or ETL-stage controls.
What we do
- Translate reporting obligations into field-level business requirements with your compliance experts.
- Map lineage and transformations from market and trade data through ETL to risk, finance and regulatory reports.
- Specify completeness, accuracy and reconciliation controls at each stage.
- Define evidence, exception handling and accountable sign-off.
What you'll have at the end
- Report and field-definition catalogue
- Source-to-report lineage and mapping
- ETL-stage control and reconciliation rules
- Business validation and sign-off pack
Requirements, UAT & delivery assurance
From workshop to signed-off release, fully traceable.
The problem. A document is not a shared understanding. Requirements that lack acceptance criteria, owners or traceability leave the hard decisions until UAT.
Where you might be. A pre-trade, execution, post-trade or reporting delivery phase needs a senior BA to connect stakeholders, developers and testers, or a release needs a credible path to business sign-off.
What we do
- Facilitate workshops and write BRD / FSD specifications or focused user stories.
- Define BDD acceptance criteria, dependencies and decision ownership.
- Plan UAT scenarios, test data, entry / exit criteria and defect triage.
- Maintain traceability through Scrum delivery, release readiness and sign-off.
What you'll have at the end
- BRD / FSD or prioritized user stories
- BDD acceptance criteria and traceability matrix
- UAT plan, scenarios and defect process
- Business readiness and release sign-off pack
AI-ready data & automation
Clean, governed data before the model, not after.
The problem. AI does not repair unclear definitions or uncontrolled inputs. Without approved training-data criteria, a promising prototype cannot become a trusted workflow.
Where you might be. A team needs approved AI-ready market, trade or reporting data, or wants to automate recurring reconciliation and analysis without losing control.
What we do
- Define training-data eligibility, ownership, usage boundaries and approval criteria across market, trade, risk and reporting data.
- Set quality thresholds and validate datasets before model consumption.
- Prototype repeatable analysis and reconciliation workflows in Python / SQL.
- Document control points, human review and a maintainable handover.
What you'll have at the end
- Training-data criteria and approval checklist
- Dataset quality validation and evidence
- Working automation prototype
- Controls, handover and runbook
How an engagement usually runs.
Discover
Stakeholder interviews. Current-state mapping. The right problem, before the solution.
You get: Problem statement & scopeDefine
Requirements, ownership and acceptance criteria. A shared definition of done.
You get: Traceable requirementsDesign
Data flows, control points and test scenarios. Make the hand-offs explicit.
You get: Target-state & control designDeliver
Work alongside the build team. Validate, triage and prepare for sign-off.
You get: Test evidence & release readinessOptimize
Review what changed. Tighten controls and remove repeat manual work.
You get: Improvement plan & handover
Three shapes the work can take.
Fixed-scope assessment
You have a bounded question. We give you an independent answer and a short, ranked list of what to do next.
Embedded senior BA
We join your team for a delivery phase and do the analysis hands-on, in your stand-ups and your JIRA.
Advisory retainer
A senior person to call when a requirement, a data decision or a go-live doesn't feel right.
Things people ask before we start.
Do you work remotely?
Hybrid engagements in the Greater Toronto Area; remote delivery elsewhere. The working arrangement is agreed around your team and the work.
How quickly can you start?
Start dates depend on the scope and current commitments. Share your timeline and we will confirm availability before you make a decision.
Do you sign NDAs?
Yes. we can sign an NDA before discussing sensitive requirements or reviewing your data.
Can you work alongside our vendors or systems integrator?
Yes. we work alongside internal teams, vendors and systems integrators, making responsibilities, interfaces and acceptance criteria explicit.
Do you provide contract staff?
Yes. ScopeX connects experienced contract professionals with capital-markets engagements through a vetted talent network. Matching depends on the requirements and availability.
Got a change thatcan't afford to go wrong?
Thirty minutes, one conversation about the problem. No pitch deck, no junior sent along to take notes.