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Choose mortgage hedging software by starting with your actual loan-sale strategy, then proving that the system can measure exposure, recommend or support hedges, reconcile positions and produce controlled daily reports from your own data. A useful platform connects expected closings and delivery decisions to pull-through assumptions, hedge workflows and intraday monitoring—not merely a price screen.
The right choice depends on execution mix, risk appetite, pipeline behavior, investor and agency requirements, integration architecture, internal expertise and governance. Treat every feature statement as a hypothesis to verify in a structured pilot.
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1. Map the lender’s execution strategy before looking at software
Mortgage pipeline hedging is not a standalone calculation. It links locked loans that may close, the probability that they will close, the way each loan will be sold and the hedge or delivery action needed to control market risk. Fannie Mae’s definition of pipeline hedging refers to risk and hedge reports based on best execution and expected closing percentages. See the agency’s definitions at Fannie Mae’s glossary; confirm the current wording and applicable guidance when you begin procurement because the glossary page does not expose a publication date in the available material.
Document every path a loan can take before asking vendors to demonstrate a product. Include best-efforts whole-loan sales, mandatory whole-loan commitments, agency delivery, TBA-based strategies, bulk or mini-bulk sales and any servicing exposure retained after sale. The software should represent the executions you actually use, expose the assumptions behind them and allow users to compare the all-in value of alternatives.
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Best-efforts execution
Fannie Mae defines best efforts as a direct sale in which the seller does not take the rate-lock interest-rate risk. The best-efforts asset price is lower than the price available for mandatory execution. In practice, the lender’s system still needs to model which locked loans are likely to close, but the hedge decision differs because the delivery commitment does not transfer the same market exposure to the lender.
Mandatory execution
Mandatory execution takes on the interest-rate risk associated with the commitment to deliver loans. A hedge platform must therefore connect expected closing percentages, trade commitments, pair-offs, fallout and delivery timing to the lender’s open position. The strategy can provide different economics from best efforts, but it also creates delivery, liquidity and operational obligations.
Best execution across delivery choices
Best execution means comparing all-in delivery pricing and selecting the path that gives a loan its highest value, rather than assuming one channel is always superior. Investor pricing, counterparty terms, pipeline characteristics, servicing value, capacity and the lender’s ability to meet delivery requirements all affect the result. Require vendors to show how assumptions and competing execution paths are presented to users.
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Outbyte PC Repair FREERepair Windows errors before they cause bigger problemsFix Now →Outbyte Driver Updater FREEScan for outdated or missing drivers - takes under a minuteDriver Scan →| Execution path | Risk characteristic | What the software must represent |
|---|---|---|
| Best-efforts whole-loan | The lender does not take the rate-lock interest-rate risk on the direct sale. | Expected closing percentages, loan eligibility, investor pricing and best-execution comparisons. |
| Mandatory whole-loan | The lender takes the interest-rate risk of the delivery commitment. | Open commitments, fallout, pair-offs, hedge positions, delivery dates and reconciliation. |
| Agency delivery | Value and obligations depend on the agency execution selected. | Eligibility rules, delivery status, pricing adjustments and settlement tracking. |
| TBA-based strategy | Pipeline exposure is managed against TBA pricing and market movement. | Note-rate or TBA measurement, shock scenarios, trade capture and position reporting. |
| Bulk or mini-bulk sale | Aggregated loan characteristics and delivery terms affect value and exposure. | Pool or cohort views, stratification, cash-flow inputs and delivery reconciliation. |
| Retained servicing exposure | Servicing economics can alter the value of a delivery decision. | Servicing valuation inputs, reporting and a clear connection between sale and servicing views. |
2. Define the risk model you need to trust
Ask a vendor to demonstrate the risk engine with your own loan attributes and historical outcomes. A polished dashboard is not evidence that the modeled exposure is accurate. The demonstration should show how the system handles pull-through or fallout, lock extensions and expirations, product and note-rate differences, eligibility changes, market moves and production forecasts.
Pull-through and fallout
Expected closing percentages are central to pipeline risk. Require loan-level assumptions that can roll up to cohorts, channels, products, lock ages and originators. Ask whether users can update assumptions, retain an audit trail of changes and compare the forecast with actual closings and fallout. A model that only accepts one static percentage will not explain why exposure changes as the pipeline ages.
Loan-level and cohort-level views
Loan-level detail is needed to investigate an exception, an ineligible loan or a changed lock. Cohort-level views are needed to see concentration by product, investor, rate, channel, lock age or delivery path. Confirm that users can move from an aggregate position to the individual loans driving it without exporting data to a separate spreadsheet.
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Shock and scenario analysis
Request controlled scenarios for market moves, changes in pull-through, lock extensions, investor eligibility and production volume. Optimal Blue says its Hedge Analytics materials provide real-time data, shock analysis, note-rate or TBA measurement and data scrubbing. Those are provider descriptions, not independent validation; test the calculations with known positions and agreed expected results at the Hedge Analytics product information sheet.
Transparent assumptions and reconciliation
Every exposure number should have a traceable input: loan status, lock date, rate, product, expected close date, investor, delivery path, pull-through assumption and market data timestamp. The system should let the team reconcile modeled exposure with actual trades and commitments. Ask how corrected source data is versioned, who can approve a change and whether prior position snapshots remain available.
3. Follow one loan through the complete workflow
Do not evaluate modules in isolation. Walk a representative loan from pricing and lock through pipeline updates, hedge decision, trade capture, investor selection, delivery, settlement and daily profit-and-loss or position reconciliation.
- Price and lock: Confirm how the loan and its lock terms enter the platform, including product, note rate, lock period and channel.
- Update the pipeline: Show how status changes, extensions, expirations, withdrawn loans and changed attributes are reflected and time-stamped.
- Calculate exposure: Review the loan’s pull-through assumption, cohort assignment, hedge contribution and sensitivity to market movement.
- Choose execution: Compare best-efforts, mandatory, agency, TBA and other applicable delivery paths using all-in economics and eligibility.
- Approve and place the hedge: Identify required approvals, authority limits, trade instructions and the point at which a decision becomes a recorded commitment.
- Capture the trade: Verify counterparty, security or loan reference, price, quantity, trade date, settlement date and amendments.
- Deliver and settle: Follow the loan or pool through investor delivery, pair-off or exception handling and settlement status.
- Reconcile: Match the source pipeline, hedge trades, commitments, settlements and accounting or finance records. Inspect how breaks are queued and resolved.
CompassEdge is described by Optimal Blue as a unified platform combining hedging, loan trading, analytics, loan-sale execution and MSR valuation, with a connection to its pricing engine. The vendor also describes automated pooling and related workflows. Confirm which functions are native, which require an integration, how frequently data refreshes and what happens when a feed fails at the CompassEdge information page.
4. Evaluate integrations and data quality as risk controls
A hedge model cannot be better than the data feeding it. Build an inventory of your loan-origination system, product and pricing engine, investor and agency connections, TBA pricing feeds, accounting or general-ledger destination, servicing systems and identity or access provider.
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Questions for every interface
- Is the connection an API, scheduled file, message feed or manual upload?
- How often are records refreshed, and can users see the last successful update?
- What fields are mandatory for risk calculations and execution eligibility?
- How are duplicates, stale records, invalid values and rejected messages surfaced?
- Can an operator replay a failed transmission without creating a duplicate trade or loan?
- Are source values preserved so an auditor can determine what changed and when?
- What is the contingency process if the loan-origination system, market-data feed or vendor service is unavailable?
Optimal Blue says its Hedge Analytics solution integrates with pricing, loan trading, agencies, aggregators, TBA pricing and leading loan-origination systems. Its capital-markets materials describe a broader technology platform and integration coverage. Use those statements as a demonstration checklist, not as proof that your particular systems are supported; review the platform overview at Capital Markets Technology Platform and require a written interface and implementation scope.
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5. Require controlled daily operations and reproducible reporting
Hedging software becomes part of the lender’s control environment. Evaluate whether the daily process can be performed consistently, reviewed by another person and reproduced later for finance, risk, internal audit or a regulator.
Access and approval controls
- Role-based access for originators, secondary-marketing staff, traders, operations, finance and administrators.
- Separate preparation, approval, trade-entry and reconciliation responsibilities where your policy requires it.
- Configurable limits for trade size, authority, counterparty and exception escalation.
- Time-stamped audit trails for source-data changes, assumption changes, approvals, trade amendments and overrides.
Exceptions and reconciliation
Look for queues that identify missing locks, stale market data, ineligible loans, unmatched trades, delivery breaks, unexpected fallout and settlement discrepancies. The user should see the owner, age, severity and next action for each exception. Ask whether a resolved exception retains its original evidence and resolution note.
Reports and position snapshots
Reports should support the daily hedge meeting, finance close, management oversight and counterparty reconciliation. At minimum, ask to see pipeline exposure, hedge positions, expected closing percentages, trade detail, daily P&L, delivery status, data-quality exceptions and an as-of timestamp. Optimal Blue describes data scrubbing, position reporting, daily P&L tracking and reconciliation capabilities across its materials. Validate those workflows against your own chart of accounts, position definitions and retention policy.
CompassPoint reporting claims
Optimal Blue describes CompassPoint as providing daily loan- and cohort-level valuation, cash-flow and stratification reporting for origination pipelines, whole-loan portfolios and mortgage-servicing portfolios. It also presents best execution, P&L tracking, daily risk management, originator scorecards and pull-through modeling as features. Treat these as vendor claims and ask for a live demonstration using anonymized records shaped like your pipeline at the CompassPoint page.
6. Choose the operating model: self-service, hybrid or outsourced
The same software can be a poor fit if the lender does not have the people, authority and coverage to operate it. Decide explicitly how much work remains internal.
Self-service
Internal staff perform data validation, scenario analysis, hedge decisions, trade execution, reconciliation and reporting. This offers direct control and keeps expertise in-house, but requires trained personnel, documented procedures, backup coverage and sufficient separation of duties.
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Hybrid advisory support
Internal staff retain decision authority while an adviser assists with analytics, scenarios, process design or execution support. Define exactly which activities are advisory, which require lender approval and how disagreements or urgent market events are handled.
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Fannie Mae defines outsourced hedging as a service in which a vendor monitors risk and executes trades on the seller’s behalf, usually through a power of attorney. The lender remains responsible for governance, oversight, data quality, policy compliance and business continuity. Review delegated authority, trade limits, counterparty controls, reporting frequency, incident notification, contingency coverage, termination rights and access to complete records.
Optimal Blue’s Hedge Analytics page describes full-service, hybrid and self-service models. Compare accountability, staff training, operating hours, escalation paths and the ability to take control during a vendor outage before selecting one. A lower internal workload is not the same as lower institutional risk.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.7. Score vendors against the same evidence
Create a weighted scorecard before demonstrations so a persuasive interface does not outweigh a missing control. Have capital markets, secondary marketing, finance, operations, IT and risk score the same scenarios.
| Evaluation area | Evidence to request | Pass condition |
|---|---|---|
| Execution coverage | Demonstration of each execution path the lender uses, including best execution logic. | Users can compare applicable delivery choices with visible assumptions and eligibility constraints. |
| Risk model | Loan-level and cohort-level exposure, pull-through, fallout, lock changes and shock scenarios. | Outputs reconcile to agreed test cases and changes are traceable. |
| Market and trade data | Feed timestamps, TBA or other market inputs, trade capture and amendments. | Stale, missing or rejected data is visible and cannot silently alter positions. |
| Workflow | End-to-end loan, hedge, delivery and settlement walkthrough. | Manual handoffs, approvals and exception ownership are explicit. |
| Integration | Interface map, field list, refresh schedule, error handling and recovery procedure. | Your LOS, pricing, investor and finance connections have a documented implementation path. |
| Controls | Roles, limits, audit trail, snapshots, reconciliation and report retention. | Daily operations can be reviewed and reproduced without spreadsheet reconstruction. |
| Operating model | Self-service, hybrid or outsourced responsibilities and service levels. | Authority, accountability, coverage and contingency obligations are contractually clear. |
| Implementation | Migration, configuration, training, testing, cutover and support plan. | Named owners, acceptance criteria and rollback procedures exist for each stage. |
8. Run a structured pilot with your own data
Vendor presentations describe capabilities; they do not establish independent performance or prove that a lender’s controls will work. Use a representative historical sample and a controlled live workflow.
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- Freeze the baseline: Reconcile the sample’s pipeline, trades, commitments, deliveries, settlements and realized outcomes before loading it into the candidate system.
- Define expected results: Agree in advance on exposure, hedge, P&L, best-execution and exception outcomes for selected scenarios.
- Test adverse cases: Introduce fallout, extensions, expirations, changed loan attributes, stale feeds, duplicate records and failed interfaces.
- Observe live operations: Run the daily process with real user roles, approvals, queue ownership, reports and reconciliation rather than a scripted demo.
- Measure the work: Record accuracy, exception handling, data latency, manual steps, traceability, correction time and report reproducibility.
- Score cross-functional results: Have capital markets, secondary marketing, finance, operations, IT and risk evaluate the same evidence.
- Document conditions: List configuration changes, custom integrations, services, training, staffing and controls required for production.
Use a pilot to validate the product you will operate, not to create an impressive one-day result. A vendor’s favorable demonstration is not a neutral benchmark, and no cited material establishes that any provider passed this type of test.
9. Clarify implementation, support and continuity before contracting
Ask for a production plan that identifies data mapping, historical-load limits, configuration ownership, user acceptance testing, parallel runs, cutover timing and post-launch support. Require written service levels for availability, incident response, market-data interruptions, interface failures and recovery objectives.
Questions for the contract and implementation plan
- Which modules, feeds, reports and user roles are included in the quoted scope?
- Which functions depend on third-party data, a pricing engine or a separate loan-trading service?
- Who owns configuration of pull-through, eligibility, delivery and accounting rules?
- How are releases tested, communicated and rolled back if a calculation changes?
- Can the lender export complete loan, trade, position, assumption and audit data at termination?
- What training is provided for traders, operations, finance, administrators and backup staff?
- What is the procedure for a market-data outage, cyber incident, vendor outage or loss of key personnel?
10. Use vendor evidence carefully
Optimal Blue is a useful example of the type of platform a lender may evaluate, not a conclusion that it is the only or best choice. Its Hedge Analytics materials say the solution is designed to measure and manage net hedge position, mitigate mortgage-pipeline interest-rate risk, use shock analysis and integrate with pricing, loan trading, agencies, aggregators, TBA pricing and leading loan-origination systems. Its CompassEdge materials describe combined hedging, trading, analytics, loan-sale execution and MSR valuation functions. Verify current product names, modules, availability, implementation scope and integrations directly with the provider.
Optimal Blue attributes this statement to Jim Glennon, Vice President, Hedging and Trading Client Services: “In today’s highly competitive market, mitigating execution risk is imperative to success. Optimal Blue’s hedge advisory suite provides robust tools to accurately measure and confidently manage risk with real-time feeds of market and lock data.” This is a provider representative’s promotional statement, not an independent finding or performance benchmark.
The available material does not establish a complete, current multi-vendor landscape, neutral pricing comparison or verified referral program. Ask your current loan-origination, pricing, investor and advisory partners which systems are actually under consideration, then test every candidate with the same data, scenarios and controls.
11. Make the final decision
Select the system that produces trustworthy decisions inside a controlled operating process, not the one with the longest feature list. Before approval, the executive sponsor should be able to answer five questions:
- Does the platform model every execution strategy and servicing exposure that matters to our business?
- Can we explain every major risk number from source loan data through pull-through, market input and trade position?
- Can our teams complete the daily process, reconcile it and reproduce the evidence without hidden spreadsheet work?
- Are integrations, permissions, delegated authority and outage procedures appropriate for our control environment?
- Did the candidate prove its behavior on our representative data and live operating scenarios?
If any answer is no, defer the decision until the gap has an owner, acceptance test and documented control. Mortgage hedging software is consequential infrastructure: its value comes from connecting execution strategy, risk measurement, data integrity, trade workflow and governance every day.
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