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Generative AI (GenAI), the new rage of AI applications, promises exceptional performance while executing information search, retrieval and synthesis of unstructured content using Large Language Models (LLM’s). This ability to process large amounts of information, synthesize within context and auto-generate human-friendly responses has generated excitement with senior executives for its potential to disrupt business value chains and position the enterprise for the future while creating value for all stakeholders.
Wealth and Asset Management institutions have always been leaders in adopting innovative technologies, and many have already leveraged artificial intelligence (AI) in their core business operations. However, many AWM organizations are still finding that the maturity of use cases for leveraging large and complex unstructured information is still evolving.
What is ‘Gen-AI’
Generative AI is a type of artificial intelligence technology that can produce various types of content, including text, imagery, audio and synthetic data. The recent buzz around generative AI has been driven by the simplicity of new user interfaces for creating high-quality text, graphics and videos in a matter of seconds.
The technology, it should be noted, is not brand-new. Generative AI was introduced in the 1960s in chatbots. But it was not until 2014, with the introduction of generative adversarial networks, or GANs -- a type of machine learning algorithm -- that generative AI became a very powerful tool.
The latest annual Mckinsey global survey is predicting a breakout with explosive growth of generative AI tools and services. Across all industries Gen AI could add the equivalent of $2.6 trillion to $4.4 trillion annually in value.
Leveraging Gen-AI in Asset & Wealth Management
GenAI has been leveraged across various industries especially in areas like Service operations, sales and marketing, legal and risk etc. Firms are benefitting from exploiting the low hanging fruits by optimizing use cases that focus on operational process and efficiency improvements. However, in the future value creation will come from personalizing user engagement and improving the customer self-service experience.
In a recent study it was found that the following areas within AWM space is where GenAI could have the greatest impact
- Alpha generation – generating extra returns over benchmark without any extra risk.
- Financial advice – delivering curated insights and market intelligence.
- Client onboarding
- Marketing and investment operations
- Back-office operations
Reimagining the Wealth Management Space with GenAI
Clients are reimagining advisor desktops to deliver intelligent client insights, enhanced productivity, and enhanced experience to financial advisors (FA). HNW clients are keen to work with FAs who are more attuned to using AI during client engagement.
Competition is forcing firms to rethink their GenAI strategy –deploying GenAI-powered solutions to support FAs will lead enhanced client engagement and will positively impact business growth through new client acquisition and increased wallet share of existing clients. Companies are leveraging the technology by integrating customer relationship management (CRM) platforms to deliver next-best-action recommendations to help improve lead generation and deliver productivity enhancements.
Gen AI is being used by companies to train chatbots to provide financial advice, generate financial reports, and even complete financial transactions.
For example, Morgan Stanley Assistant marks a new era for financial analysts. The AI model is built on ChatGPT software with Open AI. With the catchy name ‘AI @ Morgan Stanley Assistant’ the new tool is designed to help analysts get access to over 100,000 research reports and documents. This will help FAs get real-time information related to financials markets, stocks and internal processes.
Leveraging Gen-AI for Asset Management
Asset Managers are leveraging Gen-AI for portfolio optimization, asset allocation, algorithmic trading and enhancing risk management processes. GenAI, can process large amounts of unstructured information, delivering curated insights and market intelligence to portfolio managers in real time to assist in investment research and help them make informed and data-driven investment decisions.
Another area where GenAI can help is allowing asset managers to proactively manage risks by continuously monitoring market conditions, news and analysis sentiments, and providing early signals.
Client onboarding process can be enhanced significantly with dynamic electronic know your customer (e-KYC) on a self-service channel or bot-assisted client onboarding.
In the Risk and compliance area automating the compliance review of various documents and advisor-generated content could create a material upside for organizations.
Personalization using GenAI models can be integrated with market attribution models and open-source data to generate insights specific for each client.
While GenAI has great potential for the AWM industry, there needs to be caution while deploying this new technology due to regulatory restrictions and potential risks.
A pragmatic approach to implementation with less risky use cases and a well-defined solution design and performance testing framework, will ensure success. Organizations should develop a robust risk and governance framework before institutionalizing the technology and reaping benefits.