AutoRek Alternative: How to Evaluate a Replacement Properly

Why firms open this evaluation

AutoRek is an established financial controls and reconciliation platform with a long presence in UK regulated finance, and firms running it are generally not looking to replace a system that has failed. The evaluation is usually triggered by one of three pressures.

The first is implementation and change velocity. Enterprise reconciliation platforms are configured to a firm's data model, and each new source, corridor, or product line is a configuration exercise. Firms scaling quickly, or firms whose counterparties change file formats regularly, feel this as a queue.

The second is the analyst workload behind the matching rate. Automated matching clears the bulk of the population everywhere. The residual breaks still require a person to investigate each one, and headcount grows with volume.

The third is the strengthened evidential standard under PS25/12 and the annual safeguarding audit. Firms are being asked not only to show that a reconciliation was performed but to show that the record produced for the auditor is the record relied upon at the time.

What to actually test in a comparison

Do not run a matching bake-off. Every serious platform matches well and a bake-off will tell you very little. Test the residual instead.

Take one month of real breaks that your team investigated manually, with the conclusions removed. Give the same population to each platform and measure three things: how many are resolved without human involvement, how many of those resolutions are correct against your team's original conclusions, and whether the reasoning behind each resolution is legible enough that a reviewer could sign it off.

Then test evidence. Pick a historic date, request the full control cycle for it, and ask each vendor how you would demonstrate to an auditor that the record has not been altered since.

Finally, test onboarding. Hand each platform a source file it has not seen, in the format your counterparty actually sends, and time the path to a working reconciliation.

Where Safeheld is differentiated

Autonomous investigation. Safeheld does not queue the residual breaks for a human. The engine forms a hypothesis for each break, retrieves the supporting records itself, tests the hypothesis, and either resolves the break with its reasoning attached or escalates it with the analysis already complete. Confidence gating and value thresholds determine which path a break takes, and both are set by the firm.

Persistent memory. Counterparty settlement behaviour, once characterised, is retained and applied to subsequent breaks involving that counterparty. The engine improves against your data rather than requiring a new rule for each pattern.

Automated schema mapping. New sources are read and mapped by the engine rather than configured by a specialist, which removes the implementation queue that accompanies each new corridor, acquirer, or product line.

Cryptographic sealing. Every run is hashed into a SHA-256 Merkle root at execution. The seal fixes the inputs, the logic, the outcome, and the reviewer, and it can be verified by an auditor or regulator independently, without access to your tenant. This is the point on which the evaluation most often turns, because it changes what the firm is able to prove rather than what it is able to assert.

Migrating without a controls gap

No regulated firm should cut over a client money control on a date. The pattern that works is parallel operation: connect the sources, run Safeheld alongside the incumbent for a full reporting cycle, and compare outcomes daily.

Parallel running produces two useful outputs. It evidences equivalence for the audit committee, and it surfaces variances that the incumbent process had been absorbing. The second is uncomfortable and it is the point of the exercise.

Historic sealed runs can be generated for a back period where source data is available, so the firm does not begin its verifiable evidence trail on the cutover date.

The cost model that actually matters

Licence cost is the smallest line in a reconciliation programme. The material costs are the implementation project, the internal engineering effort to maintain source feeds and rules, the analyst headcount consumed by exception handling, and the audit preparation effort each year.

Model those four over three years rather than comparing annual licence fees. Two platforms with similar list prices can differ by an order of magnitude once implementation days, configuration change requests, and exception headcount are included.

The variable that dominates the model is exception headcount, because it scales with volume. If your reconciliation team grows in line with transaction growth, the platform is not automating the expensive part of the process. The test is simple: model your break population at three times current volume and ask each vendor what happens to your headcount.

Audit effort is the second largest and the most frequently omitted. Where evidence is assembled for the auditor each year, that assembly is a project with a cost and a risk. Where evidence is sealed at the point each run executes, the auditor is given a fixed record and the annual project disappears.

Risks to manage in any replacement

Data access. The most common cause of a slipped timeline is not software but the availability of complete, timely statement data from every safeguarding institution, acquirer, and third party. Start those conversations before the vendor selection concludes.

Historic continuity. Decide early how far back you will seal historic runs, and confirm that the source data for that period is retrievable in a usable form.

Governance sign-off. The audit committee will want documented evidence that the new control is at least equivalent to the one it replaces. Parallel running produces that evidence as a by-product, provided the comparison is recorded daily rather than summarised at the end.

Knowledge transfer. Break resolution logic often lives in the heads of two or three analysts. Capture it during parallel running, because it is the benchmark against which autonomous resolution accuracy is measured.

Frequently asked questions

What should be tested when comparing reconciliation platforms?

The residual break population, not the match rate. Supply one month of real breaks with conclusions removed and measure autonomous resolution rate, accuracy against your team's original conclusions, and whether the reasoning is legible enough for a reviewer to sign off.

Can a firm migrate without a gap in its client money controls?

Yes, by running both platforms in parallel for a full reporting cycle and comparing outcomes daily before retiring the incumbent. Historic runs can also be sealed for a back period where source data is available.

How should the cost of a reconciliation platform be modelled?

Over three years, including implementation, internal engineering to maintain feeds and rules, exception-handling headcount, and annual audit preparation. Exception headcount dominates, because it scales with transaction volume unless the platform resolves breaks without a person.