Source of Funds vs Source of Wealth
Source of funds explains how the money for a particular transaction was generated. Source of wealth explains how a customer accumulated their wider assets over time. Financial institutions use these different questions to assess whether a proposed transaction fits the customer relationship.
Digital account information and blockchain analytics can help teams reconstruct financial activity across different systems. Each data source has limits that affect what an analyst can conclude. An institution still needs evidence connecting the customer, the economic activity and the money under review.
Two questions for the customer review
HMRC distinguishes transaction funding from the accumulation of overall wealth in its UK anti-money laundering guidance. A transfer from another bank identifies a payment route without necessarily explaining the activity that generated the money. That distinction is useful terminology, while the applicable legal obligations depend on the institution and jurisdiction.
For an institutional customer, transaction funding might come from operating revenue or the sale of an investment. The wider wealth explanation examines how the relevant owner accumulated assets through business activity or other identifiable events. Teams should keep those explanations separate when they review the evidence.
Source of funds evidence and source of wealth checks
A source of funds review can connect the stated economic event with account activity and the amount being transferred. A source of wealth review considers the broader history behind the customer or beneficial owner. Evidence should answer the particular question raised by the relationship and the assessed risk.
A proposed review workflow records the evidence source, the covered period and any unresolved discrepancy. The analyst can then compare the customer explanation with information from independent sources. An account balance alone cannot reconstruct the commercial history behind accumulated wealth.
AMLR and risk-based evidence
Regulation (EU) 2024/1624 generally applies from 10 July 2027 to the financial institutions within its scope. Article 34 includes additional information on source of funds and source of wealth among enhanced due diligence measures. The applicable measures depend on the relevant provisions and the assessed risks.
The wider customer due diligence process establishes the context for examining a relationship and its transactions. Higher-risk circumstances may require enhanced due diligence with additional information and further review. A technology result must therefore reach the institution within the applicable customer decision process.
Open banking source of funds data
Account information services under PSD2 require explicit customer consent for the service. Where the relevant service and legal conditions permit access, open banking can supply account activity for an institutional review. Teams should establish the selected accounts and the available historical period before relying on that activity.
Stripe Financial Connections retrieves transaction data with permission from the account holder and specified data access. The Stripe integration concerns US bank accounts, and European deployments require separate availability checks. Procurement teams need to verify the actual geographic and account coverage of their chosen provider.
A connected account may show incoming business revenue without explaining earlier transactions outside the available history. Missing accounts, unavailable fields or an interrupted connection leave gaps in the evidence. The review should preserve those gaps alongside the retrieved data and any additional explanation.
Transaction matching and data provenance
Transaction matching can compare amounts and dates across account records and the stated business event. The institution can preserve the original evidence alongside the matched entries and the matching rule. That record allows a reviewer to inspect why the system connected two observations.
Currency conversions and partial payments require an explanation before a difference becomes an adverse finding. An automated match should expose the underlying entries and any assumptions used during reconciliation. Teams can then investigate a mismatch without treating an incomplete data feed as proof of suspicious activity.
Blockchain analytics and the limits of a transaction trail
Blockchain forensics can examine transfers recorded on a supported public network and their known associations. A transaction trail still needs evidence connecting an address to the relevant customer. Transfers through custodial platforms can also involve activity outside the visible public record.
Crypto source of funds checks examine evidence specific to transactions involving digital assets. Institutional reviews can combine that evidence with bank account activity and the stated economic explanation. A blockchain risk label alone does not establish how a customer originally accumulated wealth.
Explainable automation and the analyst decision
Automated systems can flag discrepancies between a customer explanation and the available transaction history. Each flag should identify the relevant evidence and the reason for further investigation. The analyst needs a way to challenge an incorrect match and record the eventual decision.
Testing should include missing history, duplicate entries and corrections arriving after an earlier review. A team can compare the resulting cases with its documented acceptance and escalation rules. Those checks help institutions assess whether a proposed technology supports their actual review process.
Financial evidence and Finance Loop
Finance Loop connects professionals working on emerging technologies in finance across European markets. Financial institutions and technology companies can discuss relevant contacts for open banking and financial crime analytics. Finance Loop maintains a partnership with the Digital Euro Association in the field of digital finance.
Companies can contact Finance Loop about relevant expertise and professional introductions for their institutional work. The discussion can focus on the evidence gaps and technology questions facing a particular team.