1. Reimagine the business model
With transformative technologies, firms can set themselves up for the greatest success by developing a strategic vision for the disruption of their business models and aligning their efforts and investments accordingly. Wealth managers should think about how GenAI can democratize advice and transform client and advisor experiences. Asset managers can search for alpha by taking advantage of external information to generate investment ideas and differentiate their offerings.
Where to act now
In creating a vision for the future and a roadmap for the next three to five years, firms should apply lessons from previous implementation of high-impact technologies. Firms should reimagine legacy areas that are ripe for overhauling and optimization while balancing broader enterprise risk. Use initial use cases as a testing ground to build up the skills and insights necessary to launch into more strategic business shifts. Wealth managers should focus on knowledge management, client contact centers and other areas where automation can free up advisor time. Asset managers should focus on automating manual processes like client onboarding, lead generation and prospecting, and augmenting investment strategy and portfolio development.
Looking ahead
The future-state vision should be continuously refined based on results from initial deployments, advancements in LLMs and regulatory developments. Asset managers should enrich portfolio strategies in real time through continuous assessment and validation of market data via analyst reports, transcripts from quarterly earnings calls and other data, as well as explore further product customization. Wealth managers should look to personalize client interactions, advice and optimize portfolio construction through the usage of GenAI and external data.
Over the longer term, both wealth and asset managers will use GenAI to attract and capture new business. For asset managers, GenAI may enable new product development, as well as direct distribution and entry into new channels. For wealth managers, GenAI tools, can inform and empower client-facing teams to identify and connect with prospects and ultimately offer hyper-personalized solutions.
2. Rethink operations
Automating and optimizing repetitive, data-driven tasks can yield significant gains across the business. Data aggregation and analysis and data entry are promising starting points for many firms. Tracking results with appropriate metrics can help firms identify the most beneficial use cases and adjust future investment priorities.
Where to act now
Wealth managers can use GenAI to build new support models for advisors and smarter processes throughout the business, including those that help advisors accelerate positive client outcomes, including report generation, account setup and real-time risk monitoring. Asset managers can use GenAI to enhance functions like trade processing, performance management, fund accounting and administration. They can also automate operational tasks, like tracking and coding of investment management agreements and other compliance activities. Cash management is another area where asset managers can adopt GenAI to optimize performance.
Looking ahead
Firms can deploy GenAI tools to monitor market volatility and produce appropriate client guidance, track shifts in the regulatory and legal environment, and monitor firmwide compliance with investment mandates and guidelines.
3. Build a robust governance framework
As GenAI models are adopted more broadly across the front, middle and back offices, they will heighten existing risks and introduce new ones. This makes strong risk management governance more important than ever, for both internal applications and third-party tools. Clear policies, strong testing practices and oversight of people are all necessary to address new and heightened risks (e.g., bias, accuracy/hallucinations, changes introduced with new model releases). They also form the heart of effective and resilient risk management strategies.
Where to act now
Testing capabilities should be expanded and enhanced, with procedures incorporating advanced analytics and agile methods (e.g., scenario simulations) to identify and adapt to emerging risks and insights.
Roles and responsibilities for GenAI risk oversight should be clearly defined, from the board to the front lines of the business. Organizational policies should guide employee usage of GenAI (e.g., prohibiting the use of proprietary data with external tools and models). Broad-based controls for GenAI development, monitoring and risk management should be applied consistently across use cases. Upskilling for risk and compliance teams should be incorporated as part of a broader redesign of governance protocols.
Asset managers that use GenAI to automate compliance and investment guidelines should keep humans in the loop as final reviewers. Wealth managers should put mechanisms in place to monitor conversations between their clients and chatbots.
Looking ahead
Firms should adjust governance models based on technology advancement and regulatory changes, applying enhanced controls and advanced testing techniques to both existing applications and development of new tools.
4. Invest in key data, talent, and infrastructure capabilities
Long-term success with GenAI requires strong capabilities in a wide range of areas, from data management to talent and technology infrastructure.
Where to act now
Strong data management capabilities can provide the foundation for effective security protocols and streamline development of GenAI applications. Robust data capabilities and partnerships can accelerate firms’ ability to mine and monetize internal data assets. In addition, modernizing technology infrastructure, including cloud computing, data lakes and application programming interfaces (APIs), will be necessary to streamline and secure data access for partners.
Looking ahead
Leaders will need to determine the capabilities and infrastructure components that are most important to retain in-house for the future. Build knowledge graphs of internal expertise and consider shared services or centers of excellence for deploying scarce talent. As new capabilities mature, update investment priorities and continue to explore sourcing options for key skills, technologies and services.
5. Build partnerships to develop ecosystems
Partnerships can help firms bridge their GenAI tech and talent gaps, accelerate innovation and gain long-term competitive advantage. Firms should consider partners that can help them execute on high-priority use cases across the front, middle and back offices. Business process outsourcing firms may be a viable option for automating customer service tasks.
Looking beyond transactional outsourcing and software-as-a-service relationships, full ecosystems and strategic partnerships with technology or other firms can promote assistance in LLM access, application development and other critical areas.
Where to act now
Potential partners should be assessed based on their ability to accelerate initial use case development and provide access to scarce skills, advanced tech and high-value data. Security practices and cultural fit are other important criteria. Ecosystem strategies should align directly to top business objectives and prioritize participants with mature capabilities in targeted areas.
Looking ahead
Future partnerships and ecosystems should be designed to accelerate innovation, new product development and operational excellence. Continuous monitoring of results based on clear metrics will help determine which partnerships should be consolidated and expanded.
