How Front, Middle, and Back Office apps can benefit from a Better Data Architecture
Brokerages have vast amounts of data in legacy systems and systems of record that need to be integrated with modern applications such as credit risk, fraud management, client-facing services, or transaction posting.
To help customers with recommendations to optimize their portfolios, for robo advising, or for sales and research staff, brokerages should look to leverage massive, accurate data sets and conduct large scale analysis with cutting edge artificial intelligence and machine learning (AI/ML) – all in real-time.
To drive profitable margin loads, drive decision support (authorizing trades), conduct compliance (both pre- and post-trade), and conduct performance measurement (attribution algorithms/modeling), firms will need to cost-effectively make customer portfolio data available from their system of record available in a consumable format, and also in real-time.
For back office, a better, real-time data architecture will help:
- Supply accurate, complete data to market makers
- Track commissions and charges
- Maintain custody of securities
- Automatically execute settlement and reconciliation
- Conduct funds administration
- Minimize fraud exposure
- Deliver risk reporting in real-time