Synthetics ETFs.

When hedging Synthetic Exchange-Traded Fund (ETF) positions using Total Return Swaps (TRS), banks face a demanding set of collateral management requirements from issuers including regulatory factors such as fund structure, concentration limits, investment guidelines, and ESG constraints. Today, most banks manage this complexity through time-consuming and risky manual processes; using spreadsheets and outdated systems to extract the required data before communicating with clients individually and sequentially. The approach is time-consuming and open to error, driving up costs and increasing risk for banks and their clients. Ensuring efficiency and effective collateral optimisation for TRS-hedged Synthetic ETFs is therefore a vital consideration.

Collateral Optimisation. Simplified.

Wematch is the one-stop shop for financial institutions looking to eliminate inefficiencies, reduce capital costs, improve the balance sheet, and optimise collateral in the TRS market. The Wematch Synthetic ETFs module consolidates collateral management and automates optimisation processes, seamlessly incorporating the complex rules that Synthetic ETFs must have in place when receiving collateral including UCITS concentration limits, ESG constraints, custom index requirements, custom concentration limits, and more. 

A unified pool of collateral.

The Wematch Synthetic ETF module automated collateral optimization drives efficiency and empowers dealers. Core functions include:

Benefits at-a-Glance

Getting connected to Wematch is simple, as it is delivered as a web-based Software-as-a-Service technology that connects to the TRS ecosystem through live APIs. To get started, or to request a demo, get in touch.

Automated collateral optimisation reduces the time taken for a dealer to complete the associated workflow from around 4 hours to just 15 minutes.

With certainty that collateral is optimised in line with client requirements and downstream compliance requirements.

For increased efficiency and agility and reduced operational risk.

Thanks to dynamic management based on real-time information.

Across collateral, balance sheet, and capital costs.

Thanks to feature upgrades based on close consultation with end users.