As artificial intelligence (AI) advances, investment teams are rethinking their technology strategies to stay competitive and future-proof their processes. Traditional operating models are being replaced by new approaches that harness data, automation and AI. This shift requires a fundamental redesign of the investment target operating model, focusing on flexibility, scalability, and clearer process delineation.
Looking beyond the traditional approach to target operating model design
Traditional operating models often centre on legacy processes and systems, such as PMS (Portfolio Management System), OMS (Order Management System), and IBOR (Investment Book of Record). While useful today, these platforms and ways of working are rigid. In fact, they are likely to limit a firm’s ability to capitalize on emerging opportunities from AI.
Future operating models of investment technology should be less constrained and rely on three foundations:
- Data and knowledge resources,
- Clear task definition, and
- Leveraging automation through AI.
Crucially, the investment philosophy of the team should guide system design. Whether that focuses on a total portfolio approach, objective-based investing, factor-driven strategies, active return-seeking, or ESG considerations, the technology framework must enable and promote the philosophy – not restrict it.
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