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Generative AI: Is it all hype or reality — or something in between?

Authors:

Snehal Waghulde: Investment Management AI Strategic Growth Offering Leader, Managing Director, Deloitte Consulting LLP
Jana Borer: Investment Management Strategy, Senior Manager, Deloitte Consulting LLP
Jad El Rez: Investment Management AI and Data, Consultant, Deloitte Consulting LLP

 

Performance Magazine Issue 45 - Article 4

To the point

  • The pace of innovation for GenAI technology is incredibly rapid. While AI is not new to investment managers, GenAI is a relatively new technology.
  • Investment managers can drive value from GenAI through three plays: improving operational efficiency, driving client servicing excellence, and focusing on innovation and growth.
  • In terms of adoption, we see a spectrum of personas: possibility seekers, pursuers, and pioneers.
  • Regardless of where companies are on this spectrum, they can take several no-regret actions to prepare their firm to harness full potential of this technology.

The investment management industry is no stranger to the adoption of analytics and artificial intelligence (AI) across various parts of its business. This pioneering vision, coupled with continuous advancements in cloud technologies and improvement in data posture, created a perfect appetite for exploring the Generative AI (GenAI) advantage. Over the last 20 months (since the launch of ChatGPT in November 2022), investment managers have spent time and money in gathering perspectives, and educating their employees on GenAI, exploring use cases, experimenting, and in some cases, even productionalizing GenAI applications. As they try to keep up with the rapidly evolving technology, uncertainties around costs/Return on Investment (ROI), and what their software vendors will build versus what they should focus on, the industry is faced with the questions around the go-forward approach.

In this article, we share our insights on just that. We start with describing the value drivers to help inform the strategic areas of focus for GenAI within your firm. Then, we will dive deeper into the adoption personas (personas are defined by risk and investment appetite, existing tech and data readiness, and talent availability). We will conclude with some key takeaways for all readers regardless of where you might be on the adoption spectrum.

In 2023, foreign investment surged in India, flowing in from a variety of jurisdictions. The year also saw a spate of regulatory developments that underscored India’s unwavering commitment to fostering economic growth, streamlining investment processes, enhancing transparency, and nurturing a favorable environment for foreign investors.

As the global economy continues to intertwine with India’s financial markets, it’s increasingly essential for foreign investors to understand the country’s regulatory framework and keep abreast of its changes.

This article summarizes the different routes available to foreign investors, taking a closer look at the regulations governing foreign portfolio investments (FPIs) and alternative investment funds (AIFs) in India. It also breaks down the Securities and Exchange Board of India’s (SEBI) rules and compliance requirements for these avenues.

Does GenAI still have the promise of being a new arrow in the “transformation levers” quiver? Yes, it does!

GenAI is novel in that it can create net-new content across various modalities, such as text, audio, video, and images based on how and what the models are trained on. When combined with other forms of AI and automation, there is great potential for investment managers to unlock value from these technologies. We see three key value plays in the investment management sector:

1. Improve operational efficiency. Using GenAI across various middle- and back-office processes to reduce manual effort and improve productivity by doing more with less. Examples:

a) Reconciliation process: Automation for verifying and matching; machine learning models for dynamic adjustment of thresholds; automation for monitoring and reporting; leveraging GenAI to report trends in natural language

b) Exception handling: Leveraging a chat interface on top of a large language model to sift through operations manuals and databases to research and remediate discrepancies faster and simpler; drafting outreach when collaboration is required

2. Drive customer experience excellence. Using GenAI to create hyper-personalized and simpler experiences and services for clients to drive retention and support growth. Examples:

a) Client reporting: Creating hyper-personalized content (reports, marketing materials) based on unique client preferences, historical behaviors, alignment to moments that matter

b) Client servicing: Combining GenAI with automation to simplify client onboarding and ongoing servicing workflows designed to meet customers where they are in their journey.

3. Generate alpha and innovate. Using GenAI to create transformational opportunities, such as supporting new product development and creating new channels for revenue generation. Examples:

a) Research: Leveraging GenAI to scan through news, market data, social media information, and other alternate data sources to identify market signals for potential innovative investment opportunities

b) Business expansion: Boosting the client lifetime value (CLV) and client loyalty index (CLI) models to refine customer segmentation; targeting models leveraging alternative datasets and layering in GenAI to equip distribution teams with preferences for target growth groups.

While the applications are endless, we see the potential for experimentation within operations, internal sales, distribution, and marketing teams. These areas provide a safe sandbox for experimenting with new technologies, as they are often internally facing, have the data available, and can drive quick value. We also find that the firms gaining the most value from their investments in these technologies are often those that are transforming end-to-end workflows using a mix of GenAI workflow solutions, along with improvements with managing their teams, process, and risk.

It is important to note that not every investment manager has adopted this approach. As we zoom out across the investment management industry and study various strategies to the application of GenAI, we see three clear personas: possibility seekers, pursuers, and pioneers.

  • Possibility seekers are exploring the potential of GenAI but are cautious about how far they go with it. They adopt a “watch and see” approach, potentially due to talent limitations, a risk-averse stance, or limited investment resources. These firms prefer to observe the effectiveness and tested value generation from GenAI at other peer firms before considering full-fledged implementation. We often see firms in this group learning through limited experimentation using easily available tools. They have also engaged experts to understand third-party risk management in preparation for the likely adoption of GenAI capabilities offered by their software vendors.
  • Pursuers are widely experimenting and are in the early or intermediate stages of applying GenAI in production environments. They have completed several successful proofs of concept and proof of technology and are moving toward scaling the technology to harness its full potential. They prefer a more federated approach that allows freedom within the business groups to try out various use cases. They also invest in defensive risk management capabilities for their specific use cases, as well as boost their third-party risk management capabilities to fully tap the potential of GenAI capabilities from their software vendors.
  • Pioneers are trailblazing the adoption of GenAI across the enterprise. They have a strong understanding of the technology and are not afraid to take risks with implementing the technology at scale. They have deployed several GenAI solutions to production. Furthermore, they are centralizing some capabilities through Centers of Excellence (COEs) to foster shared usage of prebuilt components to enable faster implementation and deployment. They have also invested extensively in building their offensive risk management capabilities to safeguard against external attacks. Lastly, they are investing to address the human impacts (e.g., change management and workforce strategies).

Similar to past journeys with breakthrough inventions (e.g., internet, cloud), as we learn more about the GenAI technology and regulations, we will likely see a shift toward more mature personas.

We are in the early stages of a paradigm shift, with GenAI use cases continuing to mature into enterprise-ready solutions in the coming months. Regardless of where you are on this journey, the following considerations will help you stay at the forefront:

  • Continue to focus on education for increasing GenAI fluency.
  • Be bold. Don’t be afraid to experiment (responsibly). GenAI allows you to do things differently but also do different things.
  • Keep traditional buy versus build consideration in mind, but also note the unknown factors given evolving maturity of this technology and software vendors building similar capabilities.
  • Don’t make risk management an afterthought.
  • Change management is vital.

In the coming years, GenAI will likely be embedded into almost all major software solutions, and new enterprise-ready solutions will emerge making using GenAI second nature. In the same way that employees should not worry about being replaced by GenAI, but do risk being replaced by employees who know how to use GenAI, investment managers should be focused on not losing market share to competitors who know how to successfully amplify their effectiveness using GenAI tools while staying true to their philosophy and business strategy.

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