Digital Business Technology Platform and AI, investment management beyond the legacy


The new generation of services and new businesses is digital and primarily focused on the platform known as the Digital Business Technology Platform (DBTP). The roadmaps through which most of the business of the future will develop converge on a precise trend: setting up architectures that can seize the business opportunities offered by the latest generation enabling technologies that have undergone significant changes in recent years: Web 2.0, AI, Cloud & Net Computing, Internet of Things (IOT).

The new architectures are required to use technologies to promote the integration between the Front-End (the one that “sees” the user) and Back-End procedures (the procedures that “make the service work”), and in a much more evolved way than in the recent past. This is not an affirmation of ERP (Enterprise Resource Planning), but rather the intersection and integration of the digital business components that are now considered as being essential:

  1. Open information systems
  2. Customer and User Experience
  3. Internet of Things – IOT
  4. Business Intelligence, Data & Analytics
  5. Ecosystems and Partnerships.

The aim is to create a “cognitive company” that is able to understand and constantly adapt to the volatility of external and market conditions, insofar as its production areas are clearly related to the outside.The company becomes ‘Agile’ in product innovation and can act as an enabler for new industries. Thus, experimentation and innovation are fast, the absorption of changes does not come up against operational and IT obstacles, an it is necessary to have a governance that can extract value from high digital information exchanges, i.e. from data, and the ability to interpret this data for operational and strategic purposes, and which is different from the past in moving from the governance of operational efficiency to transformation capabilities.

Components of the Digital Business Technology Platform

In order to understand the founding insights of such an optimal digital integration framework, to assess whether to push for its adoption and to define the financial industry’s digital agenda, it is useful to analyse the design of a Digital Business Technology Platform and its individual components.

DBTP architecture’s competitive advantages help:

  • overcome the limitations of legacy technologies and company silos also in core business functions, to transform them into businesses-as-a-service.
  • bring Business Intelligence out of obscurity through the use of Data & Analytics and place it at the centre of governance.

The greatest actions and transformative effects on the industry are expected to come from AI, with the industry going from “doing the same things well” to “doing something radically different”.

A recent report by the World Economic Forum*offers a broad analysis and a very valid guide to understanding the impacts that AI will have on the current financial services structure and the greatest challenges. This transformation is taking place on several different levels:

  1. faster and more streamlined operations,
  2. customised products and advice,
  3. ubiquitous presence,
  4. rapid decision making,
  5. new value proposition.

The development of AI in the new financial services will require management to be able to:

  • be first and best in the deployment of AI: those institutions that will be first in using AI  as a differentiating factor will be rewarded by a virtuous cycle of feedback that will determine their advantages, leaving those coming later scrambling to bridge the gap;
  • collaborate with many stakeholders: unlocking the full capabilities of AI requires an extensive network of partnerships, and only the collective effort of institutions, from the regulators to the public sector, can ensure that the whole of society benefits from the expansion of AI in finance.

Lastly, the undesirable effects of this transformation will also need to be managed.

AI has created the fear of major job losses and disruptions. Strategies must be developed to effectively manage both the imminent passage of talent and the transition of large portions of the workforce through this fourth industrial revolution.

The enigmatic nature of AI-based technologies may seem “magical” to outsiders, but it has to be understood in order to identify and avoid models that discriminate or exclude marginalised groups and individuals. Since AI will play an increasingly critical role in the daily operations of the financial system, this will create a new source of systemic risk that needs to be assessed for its potential to destroy national and global economies, making new controls and responses necessary.

How will investment management move forward in this scenario?

First of all, customer experience and product offerings are being adapted to the new competition and in response to sectoral trends such as:

  • shift from high-fee active to low-fee passive investments, as consumers and institutions become fee-conscious, AuMs will switch to low-fee passive investments;
  • regulatory scrutiny, e.g. the Financial Conduct Authority has reviewed the compliance of the practices of wealth managers in the UK;
  • saturation of investment strategies, traditional investment strategies in particular have seen lower profitability due to their over-use;
  • intergenerational transfer of wealth, billions of dollars in assets are being moved between customers in developed markets ($30 trillion in North America over the next 30-40 years).

The sector needs to find answers to various issues, such as increasing customer expectations for digital channels (cross-channel switching, dialogue with staff only when the online service is not good), ageing of advisors, risk of new entrants with high customer experience skills (2/3 of millennials are willing to use financial services offered by reliable brands such as Google and Apple), reduced consulting fees, unmanaged global deposits, increased demand for alternative investments.

How will AI work in investment management?

AI will allow investment managers to review their business models by modifying or replacing core capabilities and differentiating them. This will accelerate change in various areas.

Investments will become more personalised as management companies acquire new data on their customers. Passive products will develop active features as, with AI-driven models, complex strategies can be imitated or own strategies developed. Wealth management in emerging markets will develop more quickly, helped by distribution that will help fill any existing gaps. Alpha-searchers will be pushed towards new horizons as systematic investors make greater use of advanced data science and alternative data sources.

Investment management can benefit from the development of several key AI-enabled strategies:

  • develop consultancy (e.g. by providing customers with a branded chatbot that seamlessly integrates with existing consulting relationships),
  • become a hyper-efficient and low-cost investment manager (e.g. use machine learning to make macroeconomic analysis faster and cheaper than traditional methods),
  • offer more personalised investment portfolios (e.g. use of new data sources to inform and define investor profiles and preferences in a structured way),
  • pioneering and inclusive development on emerging markets to manage low-income wealth (e.g. digital account setup and management extended to lower-net-worth customers),
  • use of data to generate alpha and differentiated performance (use of deep learning and other cutting-edge data-science techniques to innovate in the creation of investment strategies)

“…A rebalancing is underway between human minds and machines, between products and platforms and between core business and crowds”, state McAfee and Brynjolfsosson in “Machine, Platform, Crowd. Harnessing Our Digital Future”, the new work by the two MIT futurists, which provides an analysis of the climate of global digital interoperability in which we operate.

* World Economic Forum: “The new physics of financial services: understanding how AI is transforming the financial ecosystem” http://www3.weforum.org/docs/WEF_New_Physics_of_Financial_Services.pdf

Stefano Sardelli, Managing Director InvestBanca 
Graduated at the Faculty of Economics and Banking -  University of Siena, he pursued his professional career in the finance area of various intermediaries. Since 2000 he has taken on the operational responsibility of Invest Banca Spa, becoming its General Manager in 2004.He is a member of the Board of Directors of AssiomForex (National Association of Financial Market Operators). Today he is Co-Head of the Fintech Commission. He is a member of the Board of Directors of Main Capital Sgr. He pursued the themes of innovation, fintech and digital disruption, contributing with Invest Banca to develop multiple innovative solutions that led him to receive the national award for Innovation from the Italian President of the Republic.

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