From Legacy Rails to Intelligent Infrastructure: The Evolution of Financial Systems

The biggest innovation in the development of modern financial systems has been the rise of dedicated financial institutions operating on behalf of their customers—collectively known as banks, insurance companies, and securities firms. During the second half of the twentieth century, the rapid adoption of automated systems enabled banks to operate their core functions over electronic channels and to transfer data and funds quickly across disparate systems. This digitization enhanced the efficiency of financial services, but transactions and risk exposures remained largely paper-based. With a few exceptions, financial infrastructure was not digital, nor did it provide a means of connecting the disparate and non-interoperable automated banking systems worldwide.

The data in these systems was static, residing in disparate databases that financial institutions could process with various analytical models. Although these models addressed important considerations such as financial return profiling and risk analytics, they did not provide a self-learning and self-healing capability. Such a static model allowed machines to perform rules-based automation but could not adapt to changes in the data distribution. Financial institutions and capital markets were in many ways still using the equivalent of early computing systems—programmed to perform a set of functions based on established business rules.