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Perspectives

Artificial intelligence

The next frontier in investment management

The operating environment for investment management firms continues to evolve, with technological innovations and shifting investor preferences at the heart of this change. While traditional sources of differentiation in investment management are becoming increasingly commoditized, artificial intelligence (AI) is providing new opportunities which extend beyond cost reduction and efficient operations.

The four pillars for transformation

Deloitte Global’s latest report, Artificial intelligence—The next frontier for investment management firms, focuses on four pillars for transformation which can empower firms to develop new propositions, and deliver new kinds of value. These four pillars are:

  • Generating alpha: For firms seeking organic growth through outperformance, adopting alternative data sets, and AI have proved to be a differentiating factor for generating additional alpha.
  • Enhancing operational efficiency: Firms will continue to deploy AI and advanced automation to continuously improve the efficiency of their operations. Beyond this, firms can transform these traditional cost centers into AI-enabled “as a service” offerings.
  • Improving product and content distribution: Customer experience is a new battleground and AI is helping advisors to generate more insights, customize content more effectively, and deliver it to clients with greater agility and speed.
  • Managing risk: AI is a game changer for risk management. AI equips firms with the tools to bolster compliance and risk management functions, augment and automate data analysis, and anticipate and manage ambiguous events.

The report suggests that when these four pillars are augmented with AI, investment management firms can rapidly transform business models, operations, and internal capabilities. However, to fully benefit from AI, firms will need to carefully consider and manage the intersection between technology and talent.

Read this report to see how you can unlock the full potential of artificial intelligence for your business.

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Artificial intelligence: The next frontier in investment management

What is artificial intelligence?

While there is no single, universally accepted definition, AI generally refers to the ability of machines to exhibit human-like intelligence and a degree of autonomous learning. An example would be machines solving a problem without the use of hard-coded software containing detailed instructions. Deloitte recently worked with the World Economic Forum on a report and through that project we developed this definition of what AI is:

Artificial intelligence is a suite of technologies, enabled by adaptive predictive power and exhibiting some degree of autonomous learning, that dramatically advance our ability to:

  • Recognize patterns
  • Anticipate future events
  • Create good rules
  • Make good decisions
  • Communicate with other people

To put it another way, AI is a suite of technologies and capabilities which, when adopted, can enable firms to dramatically deliver new kinds of value and reshape operating models.

The adoption of AI in investment management is now empowering firms to do things they couldn’t do before: augmenting the intelligence of the human workforce, and facilitating the development of next-generation capabilities.

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Ten use cases in investment management
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Portfolio management and client enablement:

Front, middle, and back office efficiency:

Automated insight: Reading earnings transcripts to assess management sentiment

Operations intelligence: Using machine learning to automate functions 

Relationship mapping: Identifying nonintuitive relationships between securities and market indicators

Powering risk performance: AI-based algorithms and machine learning to monitor for suspicious transactions, and trigger response protocols

Alternative datasets: Analyzing alternative data such as weather forecasts and container ship movements, monitoring search engines for words on specific topics to structure hedging strategies

Reporting and servicing: Generating reporting for clients, portfolio and risk commentary, and marketing material using natural language processing

Growth opportunities: Using corporate website traffic to gauge future growth along with clients’ behavioral patterns

On-demand reporting: Chatbots and machine learning used to respond to employee or investor queries, generating management reporting on-demand

Client outreach: Smart client outreach and demand generation via analytics, using alternative data sources such as social media data

Employee insights: Monitor employee conduct risk and employee morale

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