The challenge
Unlike domestic payments, cross-border payments, have always been labour-intensive and cost inefficient in China. Local regulations require corporates to provide one of three supporting documents – either the custom declaration form (CDF), commercial invoices or purchase order – for matching and reconciliation against payment reference numbers, which is typically a manual process. Corporates may have multiple internal data sources, and the required information must be retrieved from various internal systems. CDFs are typically downloaded from the local custom’s portal into multiple excel spreadsheets for subsequent matching or printed for manual checks. This exposes parties in the payment chain to operational risk through multiple manual touch points across teams and ultimately prevents end-to-end straight through processing (STP). The regulator will also perform a yearly assessment of companies import/export deviation ratio, and any large deviation identified will put a corporate at risk of a trade regulatory classification downgrade, which can lead to further challenges in handling of cross-border transactions going forward.
Merck engaged Deutsche Bank to implement a fully automated reconciliation workflow as part of the bank’s digital treasury service (DTS) initiative, driven by robotic process automation (RPA) tools.
The key objectives of this workflow were to:
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Increase automation and accuracy in reconciliation.
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Consolidate data across different sources for the purpose of standardisation.
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Reduce manual effort on teams, number of touchpoints and repetitive tasks.
The solution
Merck used a unique reference number (tag) on each shipment and the tag is reported by the logistics team at the time of the import declaration.
Based on pre-agreed rules defined per Merck’s matching logic, RPA will structure the extracted data and match the supporting documents with the corresponding purchase information, leveraging the unique tag.
For the matched data, RPA will automatically prepare payment files, regulated reporting data and the required CDF list for bank payment processing. For unmatched data, RPA will sort out deviation types and send to related teams to follow up on the exceptional handling process. With additional information input, RPA will repeat the process and clear all unmatched data on rolling basis.
Best practice and innovation
Merck engaged all key stakeholders internally to review the current fragmented process and partnered closely with Deutsche Bank to formulate a standardised workflow. The business process transformation paves the way for this RPA solution.
This is a unique solution benchmarked across other corporates’ practices to deliver a fully digitalised, highly compliant and automated cross-border payment process. The matched commercial data, logistic data and payment data are seamlessly integrated with full visibility to all stakeholders. The enriched data and exceptional handling trails serve as the basis for management to further improve the business flow and working capital efficiency in the future. This digital treasury solution is a unique offering in the market combining cutting-edge technology across RPA, AI and API.
Key benefits
“Merck has set a new standard among corporates in China to achieve auto-reconciliation amidst regulatory requirements, which may reshape the way the industry approaches cross-border payment control methodology, it attributes to Merck’s innovation culture and good collaboration with the bank.”
Sharline Wang, Head of Treasury & Insurance China
