Bain & Co.'s Avishek Nandy Discusses Generative AI's Transformative Impact on Wealth Management

Avishek Nandy, a Partner at Bain & Company located in the Singapore office, specializes in the Financial Services practice. He heads the Wealth and Asset Management sector for the Asia Pacific region, concentrating on comprehensive transformations. His clientele includes several of Southeast Asia's most prominent financial institutions. Hubbis recently met with Avishek to discuss the potential of generative AI for the wealth management industry, including optimal implementation strategies, challenges it can address, and its role in advancing the industry and improving client services.

Discussing the potential role of AI, Avishek opens the discussion by commenting on industry's struggle with productivity, the integration of new customers, the exploration of new delivery models, and the limitations imposed by a supply-constrained business environment. Avishek argues that generative AI should be considered within the context of these challenges, suggesting that the technology has potential to enhance the productivity of relationship managers (RMs), enrich the information and data offered to customers beyond mere products, and contribute to the development of new business models. He points out the limited scale of digital or robotic advisors due to challenges in brand building and trust, alongside the need for a mass-customized experience. By focusing on the needs of both RMs and clients and the fundamental issues within the wealth management industry, Avishek posits that generative AI could indeed play a significant role in addressing these challenges, a sentiment echoed by wealth managers globally.

The Five Pillars of GenAI

Avishek then turned his attention to what he describes as the ‘Five Pillars’ through which generative AI (GenAI) can enhance efficiency and productivity in the wealth management industry. “The first pillar is that GenAI can bring to back-office operations, such as service assistance, reporting, and regulatory compliance tasks like KYC and AML processes,” he reports. “By leveraging GenAI's ability to synthesize information and generate content, these tasks can be accelerated, streamlining operations and reducing manual workloads.”

The second pillar focuses on the productivity of Relationship Managers (RMs) and commercial excellence. Avishek envisions GenAI acting as a co-pilot for RMs, aiding in account planning by aggregating and analyzing client information and bank data to create personalized plans. Additionally, GenAI could significantly impact knowledge management, acting as an aggregator and synthesizer of vast amounts of information. “To give an example, Bain's implementation of an AI layer over our 50-year knowledge base means that in a matter of minutes, I'm able to just quickly ask the system a question, and it can point to the right documents, rather than trying to me comb through all those thousands of documents. I think that knowledge management, enabled by AI, is increasingly hugely important for RMs.”

The third pillar, reports Avishek, pertains to how RMs go about giving advice. “If you think about what giving personalised advice means for RMs, there is a need for RMs to bring together all of the information they have on a given client,” explains Avishek. “GenAI could expedite the information consolidation process for RMs by integrating client data, investment views, and product platforms, thereby saving time and improving the rationale behind product recommendations to clients, particularly from a personalisation perspectives.”

The fourth pillar pertains to the need to recognize that a significant portion of the value offered to clients is in the form of data, information, and insights.

“A large part of the proposition that wealth managers bring to clients is the data, information and insights they can share,” Avishek reports. “GenAI can serve as an effective tool in making these valuable deliverables more accessible to clients, particularly in the sense of making the process more interactive and conversational.”

“This is especially beneficial for individuals at the lower end of the wealth spectrum who may have basic questions about financial concepts.” GenAI could even transform traditional methods, such as FAQs and training materials, into more engaging and efficient forms of communication, he notes.

The fifth and final pillar is imagining business models through the lens of robo-advisory and WealthTech models. This is particularly relevant for financial planning and portfolio construction for the mass affluent segment, where traditional hands-on client support is not economically viable. Here, GenAI is proposed as a potential substitute, capable of providing the necessary guidance and support to clients in this segment, with GenAI capable of providing the ‘hand-holding’ in the place of portfolio managers or RMs for those clients falling within the mass affluent bracket.

Delving deeper into the WealthTech proposition

Avishek goes on to explain that, in the realm of WealthTech and direct-to-client digital platforms. “For example, in the context of solutions such as robo-advisory services, there are notable challenges, particularly in achieving scale, with these models capturing less than 5% of the market. And large banks have also faced difficulties in penetrating the mass affluent and mass retail investment sectors,” he notes. In turn, a significant issue in this context is coverage, with many attempts to offer AI-powered model portfolios reportedly failing to fully addressing the needs for financial education, planning, and engagement, which continue to prove lacklustre in purely digital models. As such, the question arises whether GenAI could effectively address these coverage issues, enhancing the effectiveness of WealthTech and digital models by substituting for the traditional advisory process.

However, adopting any new technology necessitates a cautious approach, starting with fundamental applications before advancing to more complex implementations. “With any new technology, you have to first walk before you run,” reports Avishek. “What we are seeing is that the second pillar, RM productivity, is by far the number one thing that industry players need to figure out. And we have already built solutions which are going to show us proof of the value of using AI to boost RM productivity. And that is something we would recommend firms to double down on over the next couple of years.” The advantage of including a human in the loop in these AI-driven solutions, as well, is that it helps manage risks and increases user comfort with the technology, serving both as a learning tool and a means to generate revenue, adds Avishek.

Looking more closely at GenAI in particular, Avishek notes that the industry currently shows a varied pace of adoption, with many still in the early stages of discussing, prioritising, and experimenting with GenAI applications. However, despite the buzz around strategy and potential use cases, the emphasis should be on building and implementing solutions that can make an immediate impact. “Through partnerships and developments in large language models (LLM), like ChatGPT, there's an opportunity to pioneer in applying GenAI, moving beyond experiments to deliver practical tools to the frontline and market.” And many continue to be surprised by just how capable and adaptable models like ChatGPT are, so long as the right fine-tuning takes place. “Models like ChatGPT can do things like summarisation, language synthesis, and can even help in writing advice communications. But on their own, these models are not set up to be able to curate actual advice,” says Avishek. “But that is where the prompt engineering or the fine tuning comes in, where you take an LLM, and gear it towards mimicking the type of reasoning or conclusions RMs make based on the same sorts of inputs. And it is in developing this reasoning capacity that the real value in these LLMs is to be found.”

Strategizing GenAI Integration

Turning his attention to key opportunities in the context of leveraging GenAI, Avishek pointed towards three key areas where Bain & Co. can support firms. The first area involves assisting companies in initiating their GenAI strategy. “The approach to integrating Generative AI (GenAI) into business operations can be divided into two main areas,” reports Avishek. “Firstly, it involves guiding companies on establishing their GenAI strategy. This includes identifying potential use cases that align with their business unit's goals, determining which ones to prioritize, outlining a strategic roadmap, and designing the operational model to effectively implement these strategies. This encompasses setting up a ‘GenAI factory’, a framework to streamline and scale GenAI applications within the organization, which is part of the broader strategy and operational planning efforts.”

Secondly, Bain & Co. focuses on developing bespoke solutions for firms, rather than offering off-the-shelf software. “We are not a software company, we don’t create software solutions. But most of the work that we're doing globally around GenAI now involves leveraging our advanced analytics capabilities, our data scientists and the team.” The result of this is a combination of the firm's expertise in technology and data, allowing for the creation of tailored solutions that meet specific client needs, offering a unique approach to harnessing GenAI for practical, value-driven applications. The goal is to identify use cases with significant return on investment potential for the client, and employing Bain's expertise to realize this potential, with a focus on delivering tangible solutions rather than just high-level strategies.

The third area focuses on the technological aspects required for scaling GenAI solutions across an organization. This includes dealing with both structured and unstructured data, with a particular emphasis on the latter. GenAI's ability to process unstructured data, such as reports and call records, opens new possibilities for enhancing data utilization and decision-making processes.

“Setting up the right technology architecture to handle unstructured data and scale solutions is a critical component of integrating GenAI into a business's operational framework,” explained Avishek.

A Strategic Approach to GenAI Adoption

Taking a wide view of the industry, Avishek acknowledges that there are some problems within the wealth management industry that cannot be solved with a simple solution, instead requiring a multi-faceted approach. “While GenAI and technology can address aspects of this issue, they are not catch-all solutions,” he notes. “RMs often focus on meeting sales targets for certain products, regardless of client needs. There are some ways to address this issue with technology. For example, Bain has built a solution which conveys the logic behind why a particular product is being recommended, so that the recommendation need not be taken simply at face value. It gives clients a much better view of the logic involved.” However, he also notes that changing deeply ingrained behaviours driven by key performance indicators is crucial for a lasting solution.

Building on this ideology, Avishek notes that the integration of GenAI should be viewed as part of a broader strategy that includes adjusting KPIs and implementing controls to align RM incentives with client interests. “The demand for expertise in wealth management will continue, fuelled by the increasing sophistication of the HNW and UHNW client. This shift necessitates a re-evaluation of how banks and wealth managers standardize and support their advisory services with technology.” Thus, while GenAI and related technologies offer significant potential to enhance the services provided by RMs and wealth managers, the success of these technologies ultimately hinges on their integration within a framework that prioritizes genuine client needs and outcomes.

Bringing the conversation to a close, Avishek notes that he sees generative AI as a groundbreaking development with significant potential to transform the industry, highlighting an essential shift towards the next digital innovation era. “My concluding thought, therefore, is a call to action for those in the wealth management sector: it’s crucial to develop a strategy for integrating GenAI into our operations and services. Remaining on the sidelines is not an option for those who wish to capitalize on the transformative potential of this technology.”

Getting Personal with Avishek Nandy

Avishek Nandy serves as a partner at Bain & Company's Singapore office, where he works in the firm's Financial Services, Organisation, and Strategy practices. He brings a wealth of knowledge in the financial services industry, with a special focus on wealth and asset management, private and retail banking, and insurance. Avishek assists organizations in strategic planning and achieving their full potential, with a particular specialization in digital innovation, organizational design, and customer strategy & marketing. His client base includes some of Southeast Asia's most prominent financial institutions.

Originally from Kolkata, a major city in Eastern India, Avishek relocated to Singapore for his studies. Avishek earned his MBA from the Kellogg School of Management at Northwestern University and his bachelor's degree from Nanyang Technological University (NTU).

Outside of his work, Avishek is married with a four year old son. He also harbours a passion for photography. “I’m a Leica fan,” he professes. “I've got a few Leica variants. I have a Leica M10 Monochrom, a Leica Standard, the Leica Rangefinder, and the Leica SL2.”

He also enjoys travelling, having most recently journeying to South Africa. “We flew into Cape Town, before spending some time in Franschhoek, which was just beautiful. We then drove the Garden Route, a route from between Mossel Bay and Storms River. And then on the way back along the Cape Route 62. The weather was amazing, and my son loved it.”

For more insights from Avishek, follow this link to view out previous feature with him, which took place in 2020: Bain & Co.’s Avishek Nandy on Transformational Priorities for Asia’s Wealth Management Communit