Claims volume arrives faster than hiring does. That single fact is why claims processing outsourcing exists, and why it will keep existing regardless of what any software vendor says about it.
A partner can put thirty trained people on your work in six weeks. You cannot. When a catastrophe season lands, or a portfolio transfers, or a distribution deal works better than forecast, elastic capacity is worth real money and the alternative is a service level you cannot hold.
So this is not an argument that outsourcing is a mistake. It is an argument about what actually moves when the work moves, because that is where the disappointment usually comes from, and it is predictable enough to plan around.
What outsourcing genuinely buys
Worth stating properly before taking anything apart.
Speed to capacity. The recruit, train and manage cycle is somebody else's problem, and specialist firms are genuinely good at running it. This is the whole product and it is a good product.
Variable cost. Volume drops and the bill drops, roughly. That is a meaningfully different risk profile from carrying permanent headcount through a quiet year.
Coverage. Follow-the-sun processing, weekend surge, holiday cover. Hard and expensive to build for one operation, straightforward for a firm running it across many.
Process discipline. A good partner will document your process more rigorously than you have, because they have to in order to staff it. Plenty of insurers discover their actual process for the first time during transition, and that discovery has value on its own.
None of that is in dispute. The question is what the model cannot carry.
The document problem travels entirely
Here is the part that gets underestimated in every business case.
The reason a claims file takes 40 minutes is not that the keystrokes are slow. It is that someone has to look at a phone photograph of a damaged vehicle, a workshop quote on unfamiliar letterhead, a photocopied police report and a policy schedule with two endorsements attached, and work out what all of it says and whether any of it disagrees.
Moving that work to another building does not make the documents easier to read. It makes them harder, because the person reading them now has less context: less familiarity with your products, your regular suppliers, your regional formats, and the tells that an experienced assessor in your own team picked up over years.
So the difficulty is fully preserved and some of the compensating knowledge is lost. That gap gets filled with process: longer manuals, more mandatory fields, more QA sampling, more escalation paths. All of which is real cost that appears somewhere other than the per-claim rate.
The document layer is where the time actually goes, and it is the one layer outsourcing cannot compress. It can only re-price the hours. Our view on what makes those documents hard is set out in document automation for insurance.
Your policy does not travel cleanly
The second thing that does not move well is judgement.
Your claims policy exists in three forms: what the manual says, what your experienced people actually do, and the gap between them that nobody has written down. When work is outsourced, only the first form transfers. The partner encodes it into a service manual, trains against that, and manages to it.
From that point you have two policies. Yours drifts as your team learns things. Theirs drifts as their team learns different things. Both drift quietly, and the divergence shows up as inconsistent outcomes, disputed QA findings, and periodic recalibration exercises that everyone finds frustrating.
The governance answer is sampling. You review a percentage, find issues, feed them back, and the percentage never gets high enough to be a real control because a high enough percentage would cost more than doing the work yourself. Third-party risk guidance, including the 2023 interagency guidance on third-party relationships, is explicit that outsourcing an activity does not outsource responsibility for it. The obligation stays with you while the execution sits somewhere you can only sample.
Three ways to hold the work, compared
| Dimension | In-house, manual | Outsourced | Rules running on read documents |
|---|---|---|---|
| Capacity elasticity | Poor. Bounded by hiring and training. | Strong. This is the core product. | Strong, and roughly instant, within the volume you sized. |
| Consistency across cases | Varies by assessor, tenure and workload. | Varies, plus policy drift between two organisations. | The same conditions run on every case, in the same order. |
| Policy change latency | Days. Retraining and reinforcement. | Weeks. Manual update, retraining, contract scope. | A versioned change, back-tested before it goes live. |
| Audit reconstruction | Assembled from files and memory. | Assembled from a partner's records, on request. | The exact documents, values and policy version, retained per case. |
| Where document difficulty lands | On your people, who have context. | On their people, who have less. | On the reading layer, with the source shown for verification. |
| Cost curve with volume | Steps upward with headcount. | Broadly linear per claim. | Flattens; the marginal case costs a fraction of the first. |
| Institutional knowledge | Retained, and concentrated in individuals. | Sits with the partner, and leaves with the contract. | Encoded in policy, versioned, and inspectable. |
Read the middle column honestly and it is a good answer to the first column's worst problem. Read the third column and the point is that it is not really competing with the second one on capacity. It is competing on what consistency costs.
The costs that never reach the rate card
Per-claim pricing is the visible number, and it is not usually where the surprises live.
- Transition and ramp. Documentation, training, parallel running, and a productivity curve that takes months to flatten. Real, front-loaded, and frequently absorbed into an internal budget rather than the vendor comparison.
- Quality assurance. The sampling programme, the reviewers running it, the dispute process when findings are contested. This is permanent overhead, not project cost.
- Rework. Cases returned, corrected, resubmitted. Usually measured, rarely priced into the comparison.
- Management time. Governance meetings, service reviews, escalation handling. It is somebody's job, and often several people's part-time job.
- The complexity ceiling. Most agreements route anything genuinely difficult back to you. So the partner clears the volume and your senior people keep the hard cases, which are the ones that consume time. The headcount saving is smaller than the volume shift implies.
- Exit. Knowledge that lives with a partner has to be rebuilt if the relationship ends. That cost is real and appears at the worst possible moment.
The comparison gets much easier with a real file on screen. Start free trial and run a claim pack your partner would normally handle, or book a demo and we will run it with you.
What changes the arithmetic
The reason this comparison looks different in 2026 than it did five years ago is not that outsourcing got worse. It is that the reading layer got good enough to change which work needs a person.
If a machine can read a handwritten loss notice, a photographed quote and a badly scanned third-party report, and turn them into values a person can verify at a glance, then the volume that justified the outsourcing contract is no longer the volume that needs hands on it. What remains is the genuinely difficult residue, which is the work you probably wanted your own experienced people doing anyway.
And if your rules then run on that data identically, on every case, the consistency problem that sampling was trying to manage stops being a governance exercise. A case that stops tells you which condition it hit. A case that routes to review tells you why. Both are inspectable years later, under the policy version that actually ran them.
Two limits, because this argument is easy to overstate.
Determinism belongs to the rules layer. The same inputs and the same policy version produce the same outcome, replayably. The reading layer is a different kind of system and we do not claim bit-identical extraction from it; we claim that the source document is shown alongside what we read, that arithmetic gets recalculated rather than transcribed, and that a discrepancy is surfaced rather than smoothed over. We would rather flag an unreconciled statement than quietly adjust it to balance, which is a real behaviour in this category.
And a person still handles the hard cases. The change is that they handle the hard cases with the file already read and the discrepancies already flagged, instead of starting from a folder.
The version of this that is usually right
For most operations the answer is not a switch. It is a re-scope.
Keep the partner for surge, out-of-hours and overflow, where elastic capacity is genuinely the product. Move the reading and the rules in-house, where consistency and audit actually matter and where the marginal cost of another case is close to nothing. The partner's people then work on read files against your policy rather than against a service manual that is a copy of your policy, which removes the drift problem at its source.
That is a smaller, faster change than a transformation programme, and it does not require ending a relationship that is working.
What we can and cannot claim here
Floowed is the decision platform. Document Intelligence reads the file; the Decision Engine runs your rules on what it read. We return a decision and a record. We do not administer claims, hold policy records or move money.
Every customer we have came off manual process rather than off a competing platform, and our deepest proof is in lending because that is where we have been longest: 180 or more officer hours returned weekly at one lender, memo preparation from roughly 15 hours to about three minutes, six times the volume through the same team, three times as much statement fraud caught as manual review was finding, and a 54% cut in review time on clean cases.
Those are lending numbers, labelled as such. Our non-lending decision streams open shortly, and we are not going to present them as a shipped insurance track record or invent a carrier reference. What transfers is the general part: we read documents of any quality, and we run the rules a team writes on what we read, the same way every time. On data handling we are PDPA-compliant, with the specifics on the security page.
Frequently asked questions
Should we end our outsourcing contract?
Usually not, and certainly not as step one. The higher-value move is changing what the contracted hours are spent on. If your partner's people work on files that have already been read and checked, you get more from the same contract and the drift problem shrinks.
How do we compare a per-claim rate to a platform cost?
Convert both to total cost per closed case over 24 months, and include transition, QA, rework and management time on the outsourcing side. The per-claim rate is the visible number, not the whole number. Approach the platform side the same way and count the internal effort to write and maintain the rules.
What happens to our team?
The composition of their day changes rather than the headcount, in every deployment we have seen. Time moves out of reading and keying and into the cases that actually need judgement. That is the honest version; a vendor promising headcount reduction is promising something they cannot control.
Can this handle our worst documents?
That is the specific thing we are built for: handwritten, photographed, badly scanned, stamped over, multi-language. It is best-in-class globally on non-standard documents. The way to establish that is not to read a claim about it but to upload the file your team complained about last week.
What about cases that need investigation?
They route to a person, with the reason shown and the source documents attached. Tampering signals, arithmetic that does not reconcile and cross-document inconsistencies are surfaced in the same pass that read the file. We detect signs of manipulation; we do not certify a document as genuine and we do not verify identity documents natively, which are separate controls.
How long does it take to get live?
Weeks of proper configuration, then live. Most of the time goes into writing the rules precisely and testing them against decided cases, which is work that pays for itself in what it surfaces about the current process. Compared with a tier-one implementation running six to eighteen months with a consulting engagement attached, it is a different order of magnitude.
See it on your own documents
The way to settle a build-versus-outsource argument is to put one real claim pack on screen. Book a demo and we will run yours, show what we read next to the source, and walk through how your rules would decide it. To try it yourself first, start free trial.
Last updated 2026-08-04 by Kira.