Using transaction monitoring to better detect and disrupt financial crime
The surveillance of client transactions by financial institutions, known as transaction monitoring, is one of the main tools used by banks to ensure transactions are not fraudulent. To better understand how effective the current transaction monitoring model is, the SWIFT Institute commissioned a report assessing its strengths and weaknesses.
Authored by Matthew R. Readhead, Associate Fellow at the Royal United Services Institute (RUSI), the report analyses the shortfalls of the current transaction-monitoring model. It assesses the scale of investment, the balance between costs and benefits and the overall effectiveness of the suspicious transaction-reporting regime. It also explores industry initiatives for innovation and reform, and provides a set of recommendations to address existing pain points, potential alternatives and how effective the prospect of systemic monitoring may be in the future.
The report unpacks the difficult position that FCC teams often find themselves in - caught between internal pressures to manage costs, and regulators’ requirements that they maintain broad coverage of relevant risks. These problems have spurred a widespread desire across the AML/CFT ecosystem to reduce waste and improve the delivery of actionable and relevant financial intelligence.
Fraudsters and money launderers are constantly developing their tactics, and if the financial community wants to stay one step ahead then it is vital that it reflects and evaluates on its security models too. This report outlines 10 recommendations for improving the existing transaction monitoring system. From changing what financial institutions look for when monitoring suspicious behaviour, to embracing better machine learning technology and harnessing the power of national regulators to affect a change far greater than individual organisations can achieve alone.
OneSource Virtual uses J.P. Morgan virtual card solution on supplier management tool
OneSource Virtual (OSV) has announced the general availability of its new Finance & Accounting solution, powered by J.P. Morgan’s virtual card payments solution, Single-Use Accounts (SUA). The Invoice Pay + Supplier Management offering from OSV complements its existing line of services and extends its capabilities, allowing customers to have one partner for their financial management deployment and their invoice processing and payment services.
Invoice Pay is a new payment optimisation solution that streamlines the accounts payable process to reduce the number of steps for customers. Now, instead of customers following a series of detailed steps for each payment type - cheque, ACH, and credit card - OSV and J.P. Morgan complete those steps on their behalf so that all customers have to do is select and approve which invoices to pay and reconcile the payment batches. With SUA virtual cards, customers are eligible for six figures in annual cash savings and rebates, in combination with fraud protection across all payment types.
In addition to offering Invoice Pay to its customers, OSV is using it internally to improve its own operating efficiency and gain insights to provide a superior customer experience.
Paired with the invoice solution is Supplier Management, which adds another component to what a finance and accounting partner can offer: the ability to improve a customer’s relationship with their suppliers. Supplier Management provides supplier setup and maintenance, plus a range of payment options with detailed remittances. Suppliers also receive a supplier-facing support team and 24/7 access to a supplier portal for increased visibility.
TNO, Rabobank and ABN Amro work on privacy-friendly data analysis
New technologies have huge potential in the fight against financial crime. But it requires cooperation between several parties, as many past initiatives have shown. Also, these technologies are still in the fledgling stages of development. To find out more and to assess whether they could prove useful as tools for detecting financial crime, ABN Amro and Rabobank are collaborating with Dutch scientific research organisation TNO on a project called Multi Party Computation for Anti Money Laundering (MPC4AML).
The project has produced good initial results based on a synthetic data set - data that has the same characteristics as regular data but doesn’t relate to real clients. The synthetic data set contains fictional clients who make payments between various banks. The clients in this data set have a risk score, like real clients. Clients whose accounts are linked to salary payments and mortgages usually have a lower risk score than, for example, those who receive large cash deposits.
The partners say they don’t want to share these risk scores with other banks. However, if one of their low-risk clients receives money from high-risk clients at other banks, they say they want to be able to monitor that client more closely. The challenge is to do this when you’re not allowed to see the risk scores used by other banks. The technology being tested in this collaborative project could hold the answer. By encrypting and splitting the data, the partners hope to ensure that nobody can find out the original risk score.
Nevertheless, using an algorithm, this system can calculate which of low-risk clients are involved in transactions with high-risk clients at other banks, and vice versa. This is important information that can help the banks deploy their analysts more effectively in future. That way, less time could be spent on clients that analysts check under the current system, and more could be spent on others.
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