How'd you fix TRSS's revenue issues in 2026?

The two paths out of the data-commodity trap

The revenue problem is not lead volume or pricing pressure in isolation. It is that sanctions and watchlist data has become a commodity input. OFAC's SDN list, the EU consolidated list, UK OFSI designations, and UN Security Council designations are all published free by the issuing authorities. Multiple commercial vendors — LexisNexis Risk Solutions, Dow Jones Risk & Compliance, Moody's (which acquired the Bureau van Dijk and kompany assets), and Refinitiv World-Check, now part of the London Stock Exchange Group — repackage substantially the same public designations with overlapping adverse-media coverage. When four vendors sell overlapping data at overlapping price points, the buyer treats the category as a procurement line item, and every renewal becomes a price negotiation TRSS cannot win against incumbents with deeper installed bases.

That framing produces exactly two viable strategic responses, and a RevOps team fixing TRSS's revenue issues has to pick one deliberately rather than drifting between both.

Path A — the outcome-locked compliance performance contract. TRSS stops selling access to data and starts selling a guaranteed operational result inside the buyer's existing screening stack: a committed refresh latency for new designations, a committed reduction in alert false-positive volume measured against the bank's own baseline, and a committed detection window for high-risk transactions. Contract value is tied to whether those thresholds are hit, with a portion of fees at risk. The buyer is the Chief Compliance Officer or the VP of AML Operations, not procurement. The sale is a risk-transfer sale.

Path B — the compliance-consulting channel land motion. TRSS accepts that it has no relationship equity in Tier-1 bank compliance departments and rents someone else's. The advisory firms that run sanctions-program assessments — the Big Four regulatory practices, Guidehouse, Capco, Oliver Wyman's financial crime practice — already sit in the CCO's office during remediation projects and consent-order responses. TRSS becomes the recommended technology inside their assessment deliverable, paying a referral fee for the introduction and the credibility.

The two paths differ on nearly every dimension that matters. Path A has a much longer first-deal cycle because it requires a legal and risk review of the guarantee structure, but it produces contracts two to three times larger than a data-only subscription and creates renewal defensibility, because the buyer is measuring value continuously rather than at renewal. Path B produces faster first meetings and a shorter time to a signed pilot, but it caps gross margin by 20 to 25 percent on first-year value and leaves TRSS structurally dependent on partners who can substitute a competing vendor the moment a better commercial term appears.

There is a third option TRSS should explicitly reject: continuing to position head-to-head against Palantir's investigative platform. Palantir sells a horizontal data-integration and analysis layer with a services-heavy deployment model. TRSS competing on "we also do investigations" invites a feature comparison against a company with far more deployment engineers, and feature comparisons are won by whoever has more surface area. The comparison TRSS can win is narrow and contractual: who will put money behind a number.

Where each path actually breaks

Before choosing, it is worth being specific about how each option fails, because both have real failure modes and pretending otherwise produces a plan that collapses at the first board review.

Path A fails when TRSS cannot establish a credible baseline. An outcome guarantee is meaningless without an agreed starting number, and most banks do not have clean, exportable metrics on their current false-positive rate. Alert dispositions are often recorded inconsistently across case-management systems, a "false positive" at one institution means "closed with no SAR" and at another means "closed at level one triage," and the transaction-monitoring vendor's dashboard rarely reconciles to the case system's own export. If TRSS signs a guarantee against a baseline the buyer's internal audit function later disputes, TRSS is exposed to a claim it cannot defend and — worse — to a compliance dispute with a regulated entity. The mitigation is a mandatory 60- to 90-day measurement phase before any guarantee attaches, priced separately, with the baseline methodology signed by the bank's own model risk management group.

Path A also fails on the regulatory-responsibility question. Under a risk-based AML program, the institution — not the vendor — owns its compliance obligations. Bank supervisors expect institutions to validate and govern vendor models rather than outsource judgment. A contract that reads as though TRSS is assuming the bank's regulatory duty will not survive legal review. The guarantee has to be scoped tightly to operational performance metrics — latency, throughput, alert volume, uptime — never to regulatory outcomes such as "you will pass your next examination" or "no missed filings."

Path B fails on channel conflict and on margin math. Advisory firms are independent by design and often contractually required to remain vendor-neutral in an assessment engagement; a referral fee that looks like a kickback creates an ethics problem for the partner and a reputational problem for TRSS. The workable structure is not a per-deal referral fee at all but a co-developed methodology the firm licenses and delivers, with TRSS compensated for the technology component the client separately procures. It is slower to set up, produces fewer deals, and requires real product work — but it survives a partner's independence review, and the per-deal fee structure often does not.

Path B also fails on control of the narrative. When a partner presents TRSS inside a broader remediation program, TRSS has no seat in the room where scope is set. Deals get de-scoped, delayed to a later program phase, or bundled into a fixed-fee engagement where TRSS's line item is squeezed to protect the partner's margin.

How to decide between them

The decision is not a coin flip. It resolves on four measurable inputs about TRSS's own position, and a RevOps leader can score them in a week.

Input one: can you measure the buyer's baseline at all? Run a diagnostic with three friendly prospects. Ask for a 12-month export of alert volume, disposition codes, and time-to-disposition from their case-management system. If two of three can produce it within 30 days, Path A is executable. If none can, the guarantee has nothing to attach to, and TRSS must run Path B while building the measurement tooling that makes Path A possible later.

Input two: what is your balance-sheet tolerance for fees at risk? An outcome contract with 15 percent of value at risk means that on a $6 million book, roughly $900,000 of recognized revenue is contingent. That has real accounting consequences under ASC 606 — variable consideration is constrained until a significant reversal is improbable, which can defer recognition. If TRSS's investors are underwriting a revenue number this year, the CFO may veto Path A regardless of its strategic merit. Run this by finance before sales builds a playbook around it.

Input three: how long is your runway relative to the cycle? Path A first deals realistically take nine to fourteen months from first meeting to signature at a Tier-1 institution, because the guarantee triggers legal, vendor risk management, model risk, and sometimes internal audit review in addition to the normal procurement path. Path B pilots can land in four to seven months. Under twelve months of runway, the sequencing question answers itself.

Input four: do you have anything the incumbents genuinely lack? If the answer is "fresher data," that is not a moat, and neither path saves the business. If the answer is a specific detection capability — ownership-structure resolution, evasion-typology matching, network analysis across shell entities — that competitors do not offer at parity, Path A is defensible because the guarantee is backed by a real technical advantage rather than by optimism.

For most companies in TRSS's position the honest answer is a sequenced hybrid: run Path B to generate near-term pipeline and reference logos while using those engagements to build the baseline-measurement instrumentation that Path A requires, then convert to outcome contracts at the second renewal when you have a year of the customer's own data to anchor a guarantee. That sequencing is the recommendation, and it is the version of the plan a board will actually fund.

Concrete numbers behind each option

Vague strategy is why the 2025 plan failed. Here are the unit economics for each path, with the assumptions stated so they can be argued with rather than accepted.

Path A economics. A data-only sanctions and watchlist subscription for a large institution sits in a broad band — mid five figures to low six figures annually depending on seat count, data modules, and API call volume. An outcome-locked contract targets a two-to-three-times multiple on that, so a realistic first-tier price is $240,000 to $400,000 annually for a committed refresh window and a modest, verified reduction in false-positive alert volume against baseline. A second tier at $500,000 to $800,000 adds tighter latency commitments, a higher committed reduction, and a defined detection window for high-risk transactions. A top tier at $900,000 to $1.2 million adds a named compliance engineering team, real-time designation-change push into the bank's case management system, and quarterly independent verification. Note that the top tier targets the genuinely largest global institutions — the biggest banks in the world hold on the order of several trillion dollars in assets, with the largest around the $6 to $7 trillion range, so tier boundaries should be drawn well inside that ceiling rather than above it.

Fees at risk should start at 10 percent, not 15. At 10 percent, a missed quarter on a $600,000 contract costs $15,000 in that quarter — painful enough to be credible, small enough that a single measurement dispute does not blow up the P&L. Raise it to 15 percent only after four consecutive quarters of hitting the number across the whole book.

Cost to serve is the number most plans omit. An outcome contract requires a named technical owner per account at roughly 0.3 to 0.5 FTE for the first year, plus quarterly verification work. At a fully loaded $200,000 per compliance engineer, that is $60,000 to $100,000 of delivery cost against a $600,000 contract — a gross margin around 83 to 90 percent before data costs, which is healthy, but well below the 95 percent a pure data subscription implies. Model it honestly or the second year surprises you.

Sales cost is the other omission. A Tier-1 banking deal at this size requires an enterprise AE, a sales engineer with genuine sanctions-screening depth, and executive sponsorship time. At a nine-to-fourteen-month cycle and a realistic 20 to 30 percent win rate against incumbents, TRSS should model customer acquisition cost at roughly 1.0 to 1.5 times first-year contract value, recovering in month 14 to 20 on a multi-year deal. That is acceptable for a contract with high renewal probability and unacceptable for a one-year deal, which is why every outcome contract should be written as a three-year term with annual performance reviews rather than an annual renewal.

Path B economics. A referral or influence fee in professional services typically lands in the 10 to 25 percent range on first-year value, and 20 percent is a reasonable planning number. On a $400,000 deal that is $80,000 out of first-year gross margin. The offsetting benefits are real: sales cycle compresses by roughly 30 to 40 percent because the trust problem is solved before the first meeting, win rate improves materially because the partner has already framed the requirement, and TRSS carries far less pre-sales cost per opportunity.

Volume expectations should be conservative. A productive advisory partnership generates two to four qualified opportunities per quarter after a six-month ramp, not immediately. Five active partnerships at three opportunities per quarter each is 60 opportunities annually; at a 25 percent win rate that is 15 deals, and at a $300,000 to $500,000 blended value that is $4.5 million to $7.5 million in first-year bookings — before the 20 percent fee, so $3.6 million to $6 million net. But that assumes five partnerships productive simultaneously, which realistically takes eighteen months to reach, so the year-one number is closer to two productive partners and $1.5 million to $2.5 million net.

The comparison. Path A produces fewer, larger, stickier contracts with higher acquisition cost and slower ramp. Path B produces more, smaller, less defensible deals with faster ramp and a permanent margin tax. On a two-year view, Path A generates higher lifetime value per logo; on a twelve-month view, Path B generates more cash. The hybrid sequencing captures the twelve-month cash while building toward the two-year value — which is why it is worth accepting the coordination cost of running both.

One number to watch above all others: net revenue retention. TRSS's core revenue issue is that a commodity data subscription retains at whatever price procurement negotiates, which in a commoditized category trends toward 90 to 100 percent NRR with real logo churn. An outcome contract where the buyer sees a quarterly report showing measured improvement should retain above 110 percent with expansion into adjacent business units and geographies. If the outcome motion does not move NRR above 105 percent by the end of year two, the thesis is wrong and TRSS should stop.

Implementation details and sequencing

The plan below assumes a start at the beginning of a fiscal year and a hybrid path. Each phase has an exit gate; do not advance on schedule, advance on the gate.

Phase one, months one through three — instrument before you sell. Build the measurement layer first, because everything downstream depends on it. That means a baseline diagnostic that ingests a bank's alert exports and produces a defensible false-positive rate, a time-to-disposition distribution, and a designation-to-screening latency measurement. Standardize disposition-code mapping across the three or four case-management systems that dominate the market, because without normalization every baseline is bespoke and unscalable. Simultaneously, have outside counsel draft the guarantee language — scoped to operational metrics only, never to regulatory outcomes — and pre-clear it with two friendly bank legal departments before it ever appears in a proposal. Exit gate: three completed baseline diagnostics with numbers the customer's own team signs off on.

Phase two, months two through six — open the channel in parallel. Do not wait for phase one to finish. Approach three advisory firms with a co-developed sanctions-program assessment methodology rather than a referral-fee offer. The methodology is the product: a structured diagnostic the firm delivers under its own brand, with TRSS's measurement tooling underneath. Get through each firm's independence and conflicts review before discussing commercials, because discovering the conflict problem after building a pipeline forecast around it is a predictable and expensive failure. Exit gate: one signed methodology partnership and two joint client conversations scheduled.

Phase three, months four through nine — paid pilots, not free trials. Every pilot is paid, at $75,000 to $150,000 for a 90-day parallel run. Free pilots signal that the technology is unproven and, more practically, they never get staffed by the customer, so they fail for lack of attention rather than lack of merit. The pilot runs TRSS screening in parallel with the incumbent, publishing biweekly comparison reports on alert volume, latency, and any detections the incumbent missed. Critically, the pilot's success criteria are written before it starts and signed by the buyer — a pilot without a pre-agreed pass condition ends in an argument. Exit gate: 60 percent of pilots produce a signed success memo.

Phase four, months eight through fourteen — convert to outcome contracts. Only pilots that produced a signed baseline and a signed success memo convert to a guarantee. Everything else converts to a standard subscription or does not convert at all; do not guarantee a number you have not measured because you want the logo. Contracts are three-year terms, 10 percent of fees at risk, quarterly verification against the customer's own system logs rather than TRSS reporting, and a defined dispute path that goes to a joint review before it goes to money.

Phase five, months twelve through twenty-four — expand and prove NRR. The expansion path inside a large institution is geographic and by business unit: a program that starts in correspondent banking extends into trade finance, then into wealth and private banking onboarding. Each extension is a new baseline and a new guarantee, priced incrementally. This is where the outcome model earns its acquisition cost, and it is the only phase that validates the whole thesis.

RevOps ownership of the mechanics. None of this holds without instrumentation on TRSS's own side. RevOps owns four things here. First, a deal-desk gate that blocks any guarantee from being quoted without an attached signed baseline — this is a hard system control in CPQ, not a policy document. Second, a distinct opportunity type and stage model for outcome contracts, because a nine-to-fourteen-month guarantee deal forecast on the same stages as a data subscription will produce wildly wrong forecasts for three quarters. Third, revenue recognition coordination with finance so that fees at risk are modeled as variable consideration from day one rather than discovered at audit. Fourth, a post-sale SLA-performance dashboard that surfaces at-risk accounts to the account team 30 days before a quarterly measurement, so a miss becomes an intervention rather than a refund.

Team structure. Split into a land pod and an expand pod rather than a single generalist team. The land pod runs diagnostics and pilots and is compensated on signed success memos and first contracts. The expand pod owns quarterly verification, SLA performance, and business-unit expansion, and is compensated on net revenue retention. Each pod needs a sales engineer with genuine sanctions-screening depth — this is the hardest hire and the one most often deferred, and deferring it is the single most common reason outcome-based motions fail in the first year, because the technical credibility gap shows up in the second meeting and never recovers.

Positioning the government-services adjacency. TRSS's public-sector work is an asset if framed as detection-methodology provenance and a liability if framed as an identity. The line that works is about the analytical patterns and the rigor, not about the customer list. Never imply access to non-public government information, because that raises a data-provenance question in vendor risk review that costs three months to answer.

Related questions

What single metric should TRSS guarantee first?

Designation-to-screening latency. It is objectively measurable from timestamps, independently verifiable, requires no disposition-code normalization, and is the easiest guarantee to defend in a dispute. Add false-positive reduction only after a signed baseline exists.

Why not just cut price to compete with incumbents?

Because the category is already commoditized. Price cuts in a commodity category get matched within a renewal cycle by vendors with larger installed bases and better cost absorption, and they permanently reset TRSS's price ceiling with existing customers.

Should TRSS abandon its government-services revenue?

No. It funds the transition and provides methodology credibility. Keep it as a separate business unit with its own P&L so its longer cycles and different margin profile do not distort the commercial-banking motion's metrics or forecasts.

How long before this shows up in reported revenue?

Bookings move in months eight to fourteen; recognized revenue lags further because fees at risk are constrained variable consideration. Expect the first clean quarter of outcome-contract revenue around month sixteen to eighteen.

What kills this plan fastest?

Quoting a guarantee without a signed baseline. One disputed measurement with a regulated institution costs more in legal time, reference damage, and internal confidence than several deals are worth. The CPQ gate exists specifically to make this impossible.

FAQ

What actually caused TRSS's revenue issues rather than just slowing growth? The underlying cause was selling a commoditized input into a category where four established vendors repackage largely the same public designation lists. Without workflow embedding or a contractual outcome, there was no mechanism to command premium pricing or defend renewals, so every deal became a price negotiation against incumbents with deeper installed bases and longer relationships. Fixing pipeline volume would not have addressed that.

Is an outcome guarantee legally safe when selling into regulated financial institutions? Only if scoped correctly. The guarantee must cover operational performance — latency, alert volume, uptime, throughput — and never regulatory outcomes. The institution retains full responsibility for its compliance program under a risk-based approach, and any contract implying otherwise will fail bank legal review. Have outside counsel draft the language and pre-clear it with two friendly bank legal departments before it appears in a proposal.

How do you establish a baseline when the buyer's own metrics are inconsistent? Run a paid 60- to 90-day measurement phase before any guarantee attaches. Normalize disposition codes across case-management systems, define "false positive" in writing with the bank's own model risk management group, and get the resulting baseline signed. If the buyer cannot or will not produce exportable data, sell a standard subscription instead — never guarantee against an estimate.

Why pay advisory firms rather than hiring more enterprise sellers? Because the gap is relationship equity and credibility in the CCO's office, not headcount. A new enterprise seller takes nine to twelve months to build the access an advisory partner already has. That said, the structure matters more than the fee: co-develop a methodology the firm delivers under its own brand rather than offering a per-deal referral fee, which many firms cannot accept under their independence policies.

What percentage of fees should actually be at risk? Start at 10 percent. It is credible enough to differentiate from incumbents who guarantee nothing, and small enough that one measurement dispute does not damage the quarter. Move to 15 percent only after four consecutive quarters of hitting committed numbers across the entire book, and never before the measurement tooling has produced consistent results at scale.

What does RevOps specifically own in this transition? Four hard controls: a CPQ gate blocking any guarantee quote without an attached signed baseline; a separate opportunity type and stage model for outcome deals so forecasts stay accurate through a much longer cycle; revenue-recognition coordination with finance on variable consideration; and a post-sale SLA dashboard that flags at-risk accounts 30 days before quarterly measurement so misses become interventions.

Sources

• https://ofac.treasury.gov/ — U.S. Treasury Office of Foreign Assets Control, source for SDN and consolidated sanctions list publication and update cadence
• https://www.fincen.gov/ — Financial Crimes Enforcement Network, guidance on BSA/AML program expectations and beneficial ownership reporting
• https://www.ffiec.gov/bsa_aml_infobase/pages_manual/olm_011.htm — FFIEC BSA/AML Examination Manual, supervisory expectations for risk-based compliance programs
• https://www.fatf-gafi.org/ — Financial Action Task Force, international standards on combating money laundering and terrorist financing
• https://www.federalreserve.gov/supervisionreg/srletters/sr1107.htm — Federal Reserve SR 11-7, supervisory guidance on model risk management including vendor models
• https://www.fasb.org/ — Financial Accounting Standards Board, ASC 606 revenue recognition standards including variable consideration constraints
• https://www.lseg.com/en/risk-intelligence — London Stock Exchange Group risk intelligence, current owner of the World-Check screening data business
• https://www.gov.uk/government/organisations/office-of-financial-sanctions-implementation — UK Office of Financial Sanctions Implementation, consolidated list of financial sanctions targets
• https://www.consilium.europa.eu/en/policies/sanctions-against-russia/ — European Council, EU sanctions regimes and consolidated designation lists

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