How can treasury teams reduce manual reconciliation and speed up fund settlement?

The cost of manual reconciliation shows up across three areas of the business:

1. Time: over 20% of treasury hours go to pay-ins and payouts

Treasury teams spend more than 20% of their time handling pay-ins and payouts, and another 10% visualising accounts across systems. Meanwhile, CFOs spend 23% of their time on pay-in and payout management.

This time cost traces back to how payments move through the business. When they arrive through multiple providers, settle at different times, and land in separate systems, reconciliation becomes a daily manual exercise rather than an automated one.

2. Capital: settlement delays tie up cash for up to two days

Businesses can wait up to two days for funds to clear. During that window, they either finance operations from their own capital or delay outgoing payments. Both options tie up cash that could otherwise be put to work elsewhere in the business.

3. Risk and compliance: fragmented data widens audit exposure

Reconciliation errors and exceptions leave you exposed to audit risk which can lead to compliance exposure. The more fragmented data sources you're working with, the bigger that exposure gets.

Before you can address your manual reconciliation burden, you need to know where it’s coming from. Start by mapping where manual intervention happens most often. Common friction points include:

• Mismatches between provider settlement reports

• Cross-currency netting discrepancies

• Intercompany transfers with no single source of truth

• Batch settlement files that don't align with accounting records

It's also worth separating two distinct problems, because they point to different fixes.

Diagnosing which one you're dealing with matters before choosing a solution. Consolidating providers won't fix inconsistent data, and standardising data capture won't fix fragmentation on its own.

Once you know whether you're dealing with fragmented data, inconsistent data, or both, you can start applying fixes that match the problem. Here are four changes that make the biggest difference:

1. Consolidating providers onto a single platform

2. Moving from batch to API-driven settlement

3. Automating exception handling rather than just transaction matching

4. Integrating payment data directly into finance systems

Addressing all four paves the way to same-day settlement, while cutting the daily manual reconciliation work.

1. Consolidate providers onto a single platform

Every provider in a payment stack produces its own settlement report, in its own format, on its own schedule. The more providers involved, the more reconciliation work is required to produce a single, consolidated view. Consolidating the number of providers makes the workflow much easier thanks to: 

• Fewer reconciliation touchpoints

• Fewer format inconsistencies

• Fewer opportunities for discrepancy between what one system shows and what another reports

You don’t have to move every flow onto one platform at once. A better place to start is looking at where you currently have the most providers relative to volume, and where differences in settlement timings are causing the most issues. In practice, that's often cross-border collections or multi-subsidiary payouts, since these tend to route through the highest number of intermediary banks and local payment providers.

With Adyen, our one platform acts as the single source of truth from pay-in to payout. This removes the need for mandatory daily manual reconciliation across fragmented legacy partners and limits the number of places where errors, and audit risk, can creep in. Payment data is also structured consistently across markets, currencies, and payment methods, so there's no need to reconcile across multiple statement formats.

2. Move from batch to API-driven settlement

Batch settlement is one of the main structural causes of both delayed funds and difficult reconciliation. Batches process at fixed intervals, so funds that cleared hours ago aren't yet reflected in accounts, and exceptions only show up once the batch runs.

Moving to API-driven payment connections gives you transaction-level data in real time, making exception handling faster and closing the lag between payment and visibility. Around half of corporate treasurers still rely on host-to-host bank connections for at least some flows, so identifying which connections can migrate to API is a concrete step toward both faster settlement and cleaner data.

With Adyen, direct connections to payment rails and card schemes, backed by our own banking licences in the US, UK, and EU, allow funds to settle up to three days faster than the industry average, and to move 24/7, including weekends.

3. Automate exception handling, not just transaction matching

Most reconciliation automation tools are built to match transactions that are already straightforward. The real cost sits in the exceptions: mismatches, missing references, timing differences, and cross-currency rounding. Good automation needs to categorise and route these, not just flag them for a human to sort out.

If the underlying data is inconsistent across providers, automating on top of it produces more errors. A useful test for any automation tool is whether it treats different exception types differently. For example, a timing gap from a weekend settlement needs a different fix than a data error.

Adyen's AI-driven treasury workflows handle reconciliation, transaction categorisation, and exception handling automatically, cutting the manual review time that would otherwise fall on your treasury team. These capabilities get more effective as more of the money lifecycle runs through a single, consistent data environment.

For flows that still rely on batch settlement, we use AI to work out the best timing and grouping in real time, rather than processing on a fixed schedule regardless of conditions. This cuts down on half-empty batches and avoids the manual work of prioritising urgent payments separately, so time-sensitive payments move when they're expected to without someone triaging them by hand.

4. Integrate payment data directly into finance systems

Even with faster settlement and better payment data, reconciliation remains manual if that data has to be exported, reformatted, or re-entered into the systems where accounting and treasury decisions are actually made. 

The solution is to integrate your payment data directly into your ERP and TMS systems through API connections, so transaction records flow through and accounting entries are generated automatically.

This also improves forecasting accuracy. When an ERP reflects real-time payment data rather than end-of-day settlement files, cash flow projections become more reliable, and the need for large precautionary liquidity buffers decreases.

Adyen's payment and liquidity data is structured to support deep integration into enterprise finance systems, removing the manual export and reconciliation step between payment events and accounting records.

Trying to implement all four solutions at once risks stalling the project. Here’s a suggested sequence for the best chance of success:

1. Audit where manual effort actually sits. Map reconciliation touchpoints by provider, flow, and root cause, fragmented or inconsistent, before choosing a fix.

2. Consolidate the highest-friction flows first. Start with the flows that involve the most providers relative to volume, not the flows with the highest transaction count.

3. Migrate host-to-host connections to API where possible. This closes the visibility gap before automation is layered on top.

4. Automate exception handling, not just matching. Only introduce AI-driven categorisation once the underlying data is clean and consistent.

5. Connect the result to ERP and TMS. This removes the last manual export and re-entry work, and depends on the previous four steps being in place.

Reducing manual reconciliation and speeding up settlement are connected problems. Both stem from fragmented infrastructure, too many intermediaries, and payment data that is inconsistent by design rather than by accident.

Businesses making the most progress are addressing both at the infrastructure level: consolidating providers, replacing legacy connections with real-time API integrations, and choosing platforms with native banking licences that can settle faster without relying on intermediary timing. This is the approach Adyen is built around, and it's why solving reconciliation and settlement together tends to produce better results than treating them as separate projects.

If you’d like to explore how we can help you minimise manual reconciliation and speed up settlement, get in touch.