The previous two posts have covered the business & strategic need for Wealth Management IT applications to reimagine themselves to support their clients. How is this to be accomplished and what does a candidate architectural design pattern look like? What are the key enterprise wide IT concerns? This third & final post (3/3) tackles these questions. An additional following post will return our focus to the business end when we focus on strategic recommendations to industry CXO’s.
Ten Key Overall System Architecture Tenets –
The design and architecture of a solution as large and complex as a WM enterprise is a multidimensional challenge. The below illustration catalogs the four foundational capabilities of such a system – Omnichannel, Mobile Native Experiences, Massive Data processing capabilities, Cloud Computing & Predictive Analytics – all operating at scale.
Illustration – Top Level Architectural Components
Here are some of the key global design characteristics for a common architecture framework :
Given the above list of requirements – the application architecture that is a “best fit” is shown below.
Illustration – Target State Architecture for Digital Wealth Management
Infrastructure Tier –
Cloud Computing across it’s three main delivery models (IaaS, PaaS & SaaS) is largely a mainstream endeavor in financial services and no longer an esoteric adventure only for brave innovators. A range of institutions are either deploying or testing cloud-based solutions that span the full range of cloud delivery models. Business innovation and transformation are best enabled by a cloud based infrastructure.
Data Tier –
While banking data tiers are usually composed of different technologies like RDBMS, EDW (Enterprise Data Warehouses), CMS (Content Management Systems) & Big Data etc.Given the focus of a Digital Wealth Manager has in leveraging algorithmic asset management & predictive analytics to create tailored & managed portfolios for their clients – Hadoop is a natural fit as it is fast emerging as the platform of choice for analytic applications.
Services Tier –
The overall goals of the services tier are to help design, develop, modify and deploy business components in such a way that overall WM application delivery follows a continuous delivery/deployment (CI/CD) paradigm.
A highly scalable, open source & industry leading platform as a service (PaaS) is recommended as the way of building out and hosting this tier. Microservices have moved from the webscale world to fast becoming the standard for building mission critical applications in many industries.
Predictive Analytics & Business Process Tier –
Techniques like Machine Learning, Data Science & AI feed into core business processes thus improving them. For instance, Machine Learning techniques support the creation of self improving algorithms which get better with data thus making accurate business predictions. Thus, the overarching goal of the analytics tier should be to support a higher degree of automation by working with the business process and the services tier.
User Experience Tier –
The UX (User Experience) tier fronts humans – client. advisor, regulator, management and other business users across all touchpoints. An API tier is provided for partner applications and other non-human actors to interact with business service tier.
The UX tier has the following global responsibilities –
Putting it all together-