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.