Banks and other financial institutions are constantly threatened by criminals attempting to launder illicit funds. Once illegal proceeds are deposited, the funds can be moved easily by wire transfer or disguised by mingling them with legitimate funds.
A high percentage of KPMG’s customers derive from the financial services sector. The organization’s main objective was to ensure that clients satisfied the requirements of relevant laws and regulations, by detecting, controlling and reporting fraudulent activity within transactions.
In its fight against terrorist financing and money laundering, the Office of Foreign Assets Control (OFAC) routinely publishes federal notices with regard to specially designated nationals, blocked persons and entities.
KPMG deployed a bespoke analytics program to identify fraudulent activity on behalf of its clients. The solution ‘scored’ and ‘audited’ client data against information provided by OFAC alongside internal and external information resources. This score was based on the identification of banned countries, unsanctioned persons and key terms.
However, with banks now facing a significant fine per incident if discovered to be conducting business with blacklisted countries or persons, this solution was ineffective as records were in a completely unstructured format incompatible with the analytics program. Furthermore the system ignored vast amounts of valuable data from country information to the nature of the transaction. For example, it did not consider delivery instructions (sent as free text within the wire transfer) which often reveal the true destination or end use of the final transaction.
Due to such poor information identification and quality, its analytics program could not effectively score the records and accurately report on any terrorist financing and money laundering. And, with over 14 million records, it was impossible to audit such a high volume of data manually or by traditional database management techniques. The organization required a powerful solution that would effectively analyze, re-engineer and match over 14 million records to reveal blacklisted countries, blocked persons and at risk transfers as well as highlight selected trigger terminology such as ‘diamonds’ and ‘guns’. Foremost it was essential that the organization collaborated with a reputable provider that would protect highly confidential client data, whilst not jeopardizing its integrity and at all times safeguarding the interests of its clients.