Elucidate is a BaFin-authorised, ESMA-registered financial crime risk infrastructure provider. This is not an introductory engagement: a Master Services Agreement is already in place with Mastercard, two Statements of Work have been executed, and our platform is integrated with the MMCP engineering team in their staging environment. The sections that follow detail the FI-assessment architecture deployed in MMCP staging and a sample EFI-scored report from that engagement — context for the subsequent product proposal.
Master Services Agreement executed with Mastercard procurement. No further commercial onboarding is required.
Two scoped engagements have been completed with Mastercard, including the sample EFI-scored report shown in the following section.
The Elucidate platform is integrated with the MMCP engineering team's staging environment. Connectivity and integration work is complete.
The reference architecture currently deployed in MMCP staging. Open-source, proprietary, and Wolfsberg DDQ data feed a unified entity graph; third-party data sources enrich each entity; live transactional behaviour produces a risk score; the result is delivered to the receiving bank's workflow tool for green-list classification or manual review.
Output produced in the previous engagement: a single financial institution scored end-to-end against the Elucidate FinCrime Index methodology. The same scoring engine and data spine underpin the new product proposal that follows.
The bank appears to have a robust framework for managing financial crime risks, focusing on maintaining compliance with both national and international legislation across different sectors. It has implemented a variety of policies and initiatives to manage risks associated with sanctions, transactional activities, reputation, culture, bribery, and corruption, as well as its geographic footprint and customer portfolio.
Transactions are subject to rigorous assessments, with an emphasis on using environmental and social risk management systems. Additionally, the bank deploys systematic controls, particularly in dealings with high-risk countries, thus reflecting compliance with international standards to mitigate money laundering and the financing of terrorism.
No reported regulatory or legal scandals involving the bank were found within the last 36 months in the provided documents or context. The bank maintains a clean record concerning significant compliance issues or fines across its operations.
Mastercard operates a network of approximately 200–250 RSPs, each maintaining its own risk appetite. Payments are currently bound to specific RSPs at the corridor level rather than routed dynamically, because no system component reads each RSP's policy at run-time. The Payment Validation Agent addresses precisely that gap: it ingests RSP policies, pre-validates each payment against them, and delivers the transaction with a routing recommendation already attached.
Onboarding a new originating bank requires bilateral negotiation with every RSP. Origination from higher-risk markets, nested flows extending to the fourth party, crypto provenance, direct scheme connections into SEPA, and the recently introduced collections business with SME nesting all compound the operational complexity and manual workload.
Payments are bound to specific RSPs at the corridor level rather than routed dynamically, because no component reads each RSP's policy at run-time.
Every new originating bank requires bilateral negotiation with each RSP. Risk appetites are agreed pair-by-pair and do not propagate automatically.
Markets including Congo and Rwanda, together with nested flows extending to the fourth party, demand case-by-case triage that does not scale operationally.
Crypto provenance flows, direct scheme connections into SEPA, and the new collections business with SME nesting continue to accumulate within the same manual review queue.
A Common Data Layer feeds two scoring engines and a set of policy modules. A layer of autonomous agents operates on those signals under bounded autonomy. The Payment Validation Agent is the agent proposed for this engagement.
Real-time pre-validation of every payment against the schema. The transaction arrives with a routing recommendation already attached, the evidence assembled across the underlying modules, and a drafted justification — in every case. When an RSP changes its appetite, routing recommendations update everywhere immediately, without each pair being renegotiated bilaterally.
A composite, explainable risk score per transaction and counterparty — combining static profile attributes (geography, sector, ownership, network) and dynamic behavioural data, in real time. The Elucidate FinCrime Index sits underneath as the institutional benchmark, with independent standing on both sides of any transaction.
A single schema that feeds every upstream component — transaction data, counterparty data, RSP policy statements, and dynamic behavioural signals — normalised so the scoring engines and the agent layer operate on a consistent view.
Step through the current hard-tied path one hop at a time, then switch slides to see how the Payment Validation Agent intervenes — pre-validating against RSP appetite within the network and enabling a routing path that the current corridor mapping would not select.
The corridor's mapped RSP is the only available option. If its risk appetite does not match the payment, the flow is held or rejected — even where another RSP in the network would have accepted it.
The Payment Validation Agent evaluates each RSP's risk-appetite statement against the transaction's composite score and pre-validates the payment prior to settlement. The routing recommendation is delivered with the transaction, not as a downstream triage task.
The same payment routes through the same Mastercard rail to an RSP whose policy aligns with the transaction profile. When an RSP modifies its risk appetite, every routing recommendation across the network is updated in real time, eliminating the need for bilateral renegotiation.
Provide a 12-month transaction file from one of the affected higher-risk corridors. Elucidate will ingest the relevant RSP risk-appetite statements as written, process the file through the Payment Validation Agent against an indicative appetite profile, and deliver a comparison against your current decisioning.
Cases where the agent produces the same decision and routes to the same RSP, with a drafted justification attached — establishing baseline alignment between the schema and your current decisioning.
Flows that an RSP with a compatible risk appetite could have accepted — payments not currently reachable through the existing corridor mapping.
Payments rejected or escalated by the existing manual review queue that the agent would have cleared, accompanied by the supporting evidence trail.
This document accompanies the walkthrough requested in our recent discussion. The session will cover the material above against your actual RSP appetite logic, followed by scoping of the corridor to be used for the proof of concept.
Schedule the walkthrough