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Choose mortgage hedging software by starting with your execution strategy, then proving that the system can turn expected closings into measured exposure, hedge decisions and controlled daily operations. A suitable platform should model your best-efforts, mandatory, agency, TBA, bulk or mini-bulk paths; apply transparent pull-through assumptions; connect to your loan, pricing, market and investor data; and produce positions, exceptions, reconciliations and audit-ready reports. Fannie Mae’s definition of pipeline hedging links risk and hedge reports to best execution and expected closing percentages, which is a useful test for every shortlist.
What mortgage hedging software must do
A lender’s pipeline changes continuously as loans lock, fall out, extend, change eligibility or move toward delivery. Hedging software should connect four activities that are often separated in spreadsheets: forecasting which loans will close, measuring the resulting market exposure, deciding or recording hedge actions, and monitoring positions through settlement. It should support both daily and intraday views when your strategy or market volatility requires them.
Best execution is not simply the price shown on a screen. It is the comparison of all-in delivery alternatives so that loans are delivered at their highest value. Fannie Mae’s definitions describe pipeline hedging in terms of risk and hedge reports based on best execution and expected closing percentages. Read the current Fannie Mae definitions alongside your own policies, because agency terminology and guidance can change.
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- Hedge workflow: turn approved assumptions and limits into recommendations, trade tickets or controlled approvals, with a record of who acted and when.
- Monitoring: refresh market, lock and pipeline data often enough to expose intraday changes, not only end-of-day snapshots.
- Reconciliation: tie modeled exposure and hedge trades to the lender’s general ledger, trade confirms, investor commitments and settlement records.
If a vendor cannot demonstrate all four using your data, treat the product as an analytics component rather than a complete pipeline-hedging solution.
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Start with your execution and servicing map
Document how your lender actually sells loans before evaluating features. A platform that is excellent for mandatory whole-loan delivery can be a poor fit for a mostly best-efforts operation, and a lender retaining servicing has different valuation and cash-flow needs from one selling servicing released.
Best-efforts execution
Under best efforts, the lender makes a direct sale without taking the rate-lock interest-rate risk described by Fannie Mae. The best-efforts asset price is lower than the price for mandatory execution, so the relevant question is whether the lower price is appropriate for the risk, capital, staffing and delivery certainty your operation can support. Confirm how the system represents lock commitments, expected pull-through and any extension or renegotiation events.
Mandatory whole-loan execution
Mandatory execution transfers interest-rate risk to the lender between commitment and delivery. The software therefore needs to show projected fallout, market sensitivity, hedge positions, pair-offs, delivery deadlines and the financial effect of misses. Ask for a loan-level drill-down from a hedge recommendation to the specific mandatory commitment and its settlement result.
Agency, TBA, bulk and mini-bulk paths
List every other path you use: agency delivery, TBA-based hedges, bulk sales, mini-bulk sales and any correspondent or aggregator commitments. Include product, geography, investor eligibility and counterparty constraints. Require the vendor to show how each path changes pricing, hedge instruments, pooling, allocation and exception handling rather than accepting a generic “multi-channel” claim.
Retained servicing and MSR exposure
If you retain servicing, pipeline risk is only part of the decision. Ask whether the platform models servicing cash flows and valuation, how servicing trades are linked to the originating loan population, and whether a servicing position can be reconciled independently from whole-loan or TBA exposure. Keep the servicing assumptions visible so a change in prepayment or runoff inputs does not silently alter a hedge recommendation.
| Execution characteristic | Risk implication | Demonstration requirement |
|---|---|---|
| Best efforts | Fannie Mae defines this as a direct sale without taking the rate-lock interest-rate risk; asset price is lower than mandatory. | Show lock, pull-through and exception handling without creating a mandatory position. |
| Mandatory whole loan | Lender assumes rate risk until delivery and must manage commitment and settlement obligations. | Show hedge sizing, delivery deadlines, pair-offs and realized versus modeled results. |
| TBA or agency delivery | Exposure depends on security, coupon, product eligibility and allocation timing. | Show security-level positions, eligibility changes and allocation reconciliation. |
| Bulk or mini-bulk | Pool composition and investor terms can alter price, fallout and delivery risk. | Demonstrate pooling, investor selection and a full audit trail from loan to pool. |
| Retained servicing | Servicing cash flows and valuation add a separate exposure to the origination pipeline. | Show linked MSR valuation, assumptions and reconciliation to the servicing portfolio. |
Test the risk engine, not just the dashboard
Request a documented explanation of every input that changes exposure. The most consequential assumption is expected fallout or pull-through: the percentage of locked loans expected to close. A single portfolio average can conceal differences by product, channel, loan age, branch, originator, credit profile or market environment.
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Pull-through and cohort modeling
Require both loan-level and cohort-level views. A cohort might group loans by lock week, product, note rate, channel or investor. Ask whether the system stores the assumption used for each forecast, who can change it, when it changed and how the change affected the hedge recommendation. Test a historical period with unusually high fallout and another with unusually high pull-through.
Market shocks and sensitivity
Use controlled shocks to rates, spreads, volatility and key TBA prices. The system should show the change in exposure, hedge coverage and projected P&L, with results traceable to the affected loans. Vendor materials for Optimal Blue’s Hedge Analytics describe real-time data, shock analysis, note-rate or TBA measurement and data scrubbing; these are provider claims that require validation with your own scenarios at Hedge Analytics.
Loan attributes and eligibility changes
Change attributes that frequently create exceptions: product type, note rate, lock age, occupancy, documentation, loan amount, agency eligibility, investor overlays and delivery date. Verify that an ineligible or materially changed loan is removed from the appropriate hedge bucket, flagged for review and retained in the audit history.
Position and trade reconciliation
Ask the vendor to reconcile the modeled pipeline with actual trades, confirms, open commitments, pair-offs and settlements. The output should identify unexplained differences rather than forcing an operator to adjust a balance manually. A useful demonstration starts with a known position, introduces a late lock, a fallout and a trade amendment, and then proves that every balance and P&L movement is explainable.
Trace one loan through the complete workflow
Do not evaluate screens in isolation. Follow a representative loan from pricing and lock through delivery and settlement. Require the vendor to identify what is native, what arrives through an integration, how frequently it refreshes and what happens when a feed fails.
- Price and lock: confirm that the loan, product, note rate, lock date, expiration and channel enter the pipeline with a unique identifier.
- Pipeline update: change status, lock age, expected close date and eligibility; verify the update time and the user or system that made it.
- Risk calculation: apply the approved pull-through and delivery assumptions; inspect loan-level, cohort-level and aggregate exposure.
- Hedge decision: create a recommendation or approval workflow that records instrument, size, price, counterparty, authority and timestamp.
- Trade capture: enter or import the trade and verify that the position, coverage and remaining exposure update without duplicate records.
- Investor selection and pooling: test best-execution comparisons, pool construction, investor eligibility and allocation changes.
- Delivery and settlement: reconcile commitments, pair-offs, fees, proceeds and settlement status to the source records.
- Daily and intraday oversight: reproduce the position snapshot, P&L, exceptions and approvals that management or finance would review.
Optimal Blue describes its capital-markets platform as integrating pricing, loan trading, agencies, aggregators, TBA pricing and leading loan-origination systems. Treat that description as a list of integration topics for a demonstration, not proof that your specific LOS, PPE, investors or data formats are supported. Ask for a current interface map and a failure-recovery procedure at Capital Markets Technology Platform.
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Evaluate data quality and operational controls
Hedging output is only as reliable as the data entering it. Make data ownership explicit for every field used in pricing, pull-through, eligibility, hedge sizing and settlement.
- Validation: reject missing or contradictory lock dates, rates, products, loan identifiers and investor commitments before they affect a position.
- Scrubbing: identify duplicates, stale records, impossible dates and status combinations, and route them to an exception queue.
- Refresh monitoring: show the last successful market, lock, trade and investor-feed update, with alerts when a service-level threshold is missed.
- Role controls: separate users who edit assumptions, approve trades, release deliveries and reconcile results; support least-privilege access and approval limits.
- Position snapshots: preserve an immutable view of exposure and assumptions at each reporting time so a later correction does not rewrite history.
- Audit trail: record before-and-after values, user, timestamp, reason and related trade or loan for material changes.
- Reconciliation: compare system positions and P&L with trade confirms, investor statements, settlement data and finance records.
- Reporting: reproduce daily risk, hedge, best-execution, exception, originator and management reports for the same cut-off time.
Optimal Blue materials mention data scrubbing, position reporting, daily P&L tracking and reconciliation. Use those claims as demonstration checkpoints; they do not establish that your control framework is satisfied.
Choose the operating model deliberately
Decide how much expertise and authority remains inside the lender. The choices are self-service software, a hybrid model with advisory support, or outsourced hedge execution. Fannie Mae defines outsourced hedging as a service in which a vendor monitors risk and executes trades on the seller’s behalf, usually under a power of attorney. Outsourcing activities does not remove the lender’s responsibility for governance, limits, oversight, records or business continuity.
| Model | Best fit | Questions to resolve |
|---|---|---|
| Self-service | Experienced capital-markets staff who set assumptions, approve trades and monitor positions internally. | Are staffing depth, training, segregation of duties, market coverage and backup authority adequate? |
| Hybrid | A lender that wants internal control with outside analytics, advisory coverage or surge capacity. | Which decisions remain internal, how are recommendations challenged, and what happens when the adviser is unavailable? |
| Outsourced execution | A lender that delegates monitoring and trade execution under a defined mandate. | What power of attorney, limits, alerts, reports, service levels, disaster recovery and termination rights apply? |
For every model, document who owns assumptions, approves exceptions, confirms trades, signs off on reconciliations and communicates with finance, risk and regulators. Require contingency coverage for staff absence, vendor outage and market disruption.
Build a comparable scorecard
Use the same scenarios and evidence requests for every candidate. Score capability only after the vendor shows the workflow in your terminology and data.
| Category | Evidence to request | Failure signal |
|---|---|---|
| Execution fit | Configuration for each actual delivery path, investor and servicing arrangement. | One generic hedge workflow with no path-specific assumptions. |
| Risk model | Pull-through cohorts, loan-level drill-down, shocks, eligibility changes and explainable hedge sizing. | Only an aggregate dashboard or undocumented formulas. |
| Data and integrations | LOS, PPE, market, trade, agency, aggregator, investor and settlement interfaces; refresh and outage behavior. | Manual rekeying or unclear ownership of stale data. |
| Controls | Roles, approvals, exception queues, snapshots, audit logs and reconciliation reports. | No immutable history or no way to resolve breaks. |
| Workflow usability | Time and steps for a lock change, fallout, trade amendment, pool change and settlement correction. | Operators must maintain parallel spreadsheets for normal cases. |
| Operating model | Self-service, hybrid or outsourced responsibilities, coverage and escalation. | Delegated authority is vague or oversight reports are delayed. |
| Implementation | Data mapping, testing, migration, training, support, release management and business continuity. | No named implementation owner or recovery target. |
Have capital markets, secondary marketing, finance, operations, IT and risk score the same evidence independently, then resolve disagreements in a recorded decision meeting. A feature that is impressive to one team but unworkable for another is an implementation risk.
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Run a structured pilot before signing
A pilot should test accuracy and operating behavior, not merely confirm that users can log in. Use a representative historical sample and a controlled live workflow under agreed access and data-protection rules.
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- Freeze the inputs: preserve the lender’s reconciled pipeline, trades, commitments, settlements and assumptions for each test date.
- Load and map: document every field transformation from the LOS, PPE, market and trade sources; record rejected or defaulted values.
- Recreate decisions: compare the system’s exposure and hedge recommendation with the lender’s approved historical position, without treating either as automatically correct.
- Stress the workflow: introduce a late lock, fallout, extension, rate shock, eligibility change, stale feed and amended trade.
- Measure operations: record calculation latency, refresh timing, manual touches, exception resolution time, duplicate prevention and recovery after a feed failure.
- Inspect traceability: verify that every report can be traced to loans, trades, assumptions, users and timestamps, and that corrected data does not erase prior snapshots.
- Obtain cross-functional sign-off: have capital markets, finance, operations, IT and risk approve the findings or document specific remediation and an owner.
Set acceptance thresholds before the pilot begins. If a vendor cannot meet a threshold, price the remediation, interim control and operational burden rather than treating the issue as a minor configuration item.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What the available vendor evidence shows
One documented example is Optimal Blue. Its Hedge Analytics materials say the solution is designed to measure and manage the net hedge position, mitigate mortgage-pipeline interest-rate risk, use shock analysis and connect with pricing, loan trading, agencies, aggregators, TBA pricing and leading loan-origination systems. The same material describes data scrubbing and real-time market and lock feeds. These are the provider’s descriptions, not independent product testing.
The provider describes CompassPoint as delivering daily loan- and cohort-level valuation, cash-flow and stratification reporting for origination pipelines, whole-loan portfolios and mortgage-servicing portfolios. It presents best execution, P&L tracking, daily risk management, originator scorecards and pull-through modeling as features. Confirm which modules, data feeds and reports are included in the edition and implementation you would buy.
CompassEdge is described by the provider as a unified hedging and trading platform combining pipeline-risk analytics with loan-sale and MSR-valuation functions, automated pooling and integration with its pricing engine. Verify current product names, availability, integration scope, implementation effort and support terms directly with the vendor.
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1Fix the driver behind crashes, sound loss and screen glitches2Repair Windows errors before they cause bigger problems3Scan for outdated or missing drivers - takes under a minuteJim Glennon, Optimal Blue’s vice president of Hedging and Trading Client Services, describes the company’s position this way: “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 vendor representative’s promotional statement, not an independent finding. The available material does not establish a complete, current multi-vendor landscape, objective ranking or pricing comparison, so ask your LOS, PPE, investors and advisors which other systems are genuinely under consideration and apply the same pilot.
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Resolve implementation and commercial questions
Enterprise hedging software rarely fails because a screen is missing; it fails when data ownership, authority or operational effort was underestimated. Put these items in the request for proposal and contract exhibits.
- Implementation phases, named responsibilities, data mapping and migration approach.
- Supported LOS, PPE, market, trade, agency, aggregator, investor and accounting interfaces, including file and API specifications.
- Market-data licensing, refresh frequency, historical depth and treatment of unavailable feeds.
- Configuration limits for products, investors, hedge instruments, branches, entities and servicing portfolios.
- User, transaction, module, advisory, support and integration fees; the available materials state no comparable pricing, so require a complete five-year cost schedule.
- Service-level objectives for availability, data latency, incident response, recovery point and recovery time.
- Security controls, encryption, identity integration, tenant separation, retention, export and termination assistance.
- Release management, regression testing, change notices and the process for approving model or assumption changes.
- Training for traders, analysts, operations, finance, IT and internal audit, plus documentation for new staff.
Require a written statement of what is standard, configurable, custom, dependent on a third party or performed manually. That classification is more useful than a long feature list when estimating risk and total operating cost.
Common selection failures and fixes
Choosing by feature count
A long menu of analytics does not prove that the system handles your delivery paths. Fix this by requiring a loan-to-settlement demonstration for each material execution strategy.
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Using one pull-through percentage
An undifferentiated assumption can misstate exposure when lock age, channel or product behavior differs. Fix it with documented cohorts, approval rights, back-testing and exception review.
Accepting stale or unverified feeds
Old market or lock data can produce a precisely calculated but wrong position. Fix it with freshness indicators, alerts, feed-recovery procedures and a defined manual fallback.
Leaving reconciliation to spreadsheets
Parallel spreadsheets create duplicate identifiers and untracked adjustments. Fix it by making trade, position, settlement and finance reconciliation a required workflow with ownership and audit history.
Assuming outsourcing transfers accountability
A delegated trader can execute within a mandate, but the lender still needs limits, oversight, records, continuity and review. Fix it with a power-of-attorney scope, independent monitoring and termination and contingency procedures.
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Skipping cross-functional testing
Capital markets may approve a model that operations cannot maintain or finance cannot reproduce. Fix it by scoring the same pilot with every affected function and documenting unresolved exceptions.
Decision checklist
- Every execution path and servicing exposure is mapped and supported.
- Pull-through, eligibility, market shocks and hedge sizing are transparent at loan and cohort levels.
- LOS, PPE, market, trade, agency, investor and settlement data flows have owners and freshness controls.
- Daily and intraday positions, P&L, best-execution and exception reports can be reproduced.
- Roles, approvals, audit trails, snapshots and reconciliations meet finance and risk requirements.
- The chosen self-service, hybrid or outsourced model has clear authority, coverage and contingency plans.
- A representative pilot has measured accuracy, latency, manual effort, traceability and recovery behavior.
- Commercial, security, implementation and exit terms are documented rather than assumed.
Select the platform that makes your lender’s actual exposure understandable and controllable from lock through settlement. A polished dashboard is useful only when its assumptions, data lineage, decisions and reconciliations withstand the same scenarios your capital-markets team faces every day.
Quick Recap
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