The Next Era of Wealth Management: AI, Behaviour & Judgment | Bengaluru

EVENT DETAILS

Date- 19^th September 2026

Time- 10:00 AM to 4:00 pm

Venue- Vivanta Bengaluru Residency Road.

Session 1: The AI-enabled Wealth Manager: Applications, Risks and the Human Edge

2-hour Practical Masterclass by Kashyap Kompella, CFA

Session Overview

AI is becoming a practical productivity and decision-support tool across wealth management and mutual fund distribution. It can help professionals research faster, communicate more clearly, structure client conversations and manage routine workflows more efficiently.

The emphasis of this workshop is practical rather than technical, with live demonstrations, realistic advisory workflows and clear guidance on responsible use.

What Participants Will Learn

• Where GenAI can add value in wealth-management and MFD workflows
• How to use leading AI tools such as ChatGPT, Claude and Gemini more effectively
• Practical techniques for better, more reliable outputs
• How AI can support research, client communication and financial-planning discussions
• How to distinguish useful AI assistance from investment judgement
• Key risks around accuracy, confidentiality, suitability and over-reliance
• How AI may affect investor behaviour, biases and adviser-client trust
• Where human judgement continues to provide an edge

Key Takeaways

• AI is most useful as an assistant across research, communication and planning workflows.
• Better prompting improves outputs, but verification remains essential.
• Personalised language is not the same as personalised financial advice.
• Client access to AI increases the importance of judgement, context and trust.
• Responsible adoption requires clear boundaries for data, compliance and human review.
• The winning model is likely to be an AI-enabled adviser, not AI replacing the adviser.

Who It Is For

Financial advisers, Wealth managers, Mutual fund distributors, Investment professionals

 Session 2: Against Ourselves: Biases of the Successful

90-minute workshop on judgement, bias and manager selection, by Megha Malpani, CFA and Harsh Kumar, CFA

Loss aversion. Recency. Anchoring. Confirmation bias. We know them. We can spot them in others. But what happens when the bias comes from something much harder to question?

 This workshop turns the lens on ourselves – exploring how conviction, experience and expertise can shape the way we select managers, make investment decisions and respond to clients.

 The workshop examines decisions wealth practitioners make every day:

• A manager’s philosophy versus the portfolio actually being run
• A market problem versus a behaviour problem
• The evidence supporting a conviction versus the story built around it
• The judgement we make, and the assumptions underneath it

 Participants leave with practical frameworks to examine these decisions more rigorously, including a one-page decision practice designed to make conviction more accountable to evidence.

 Harsh and Megha bring the perspective of practitioners who assess portfolios together, challenge each other’s thinking and don’t always arrive at the same conclusion.
The workshop is practical, reflective and evidence-based (with no product recommendations or return projections).

Session 3: AI, Behavioral Finance and the Future of Wealth Management

30-minute Fireside Chat, with Kashyap, Megha, and Harsh

Behavioral finance has long helped advisers understand why clients may panic during market declines, chase recent performance, hold on to losing investments, under-diversify, or abandon long-term plans at precisely the wrong time.

The evidence suggests that the real value lies not in merely profiling clients, but in designing advice around better decisions: using SIPs and defaults, pre-agreed rebalancing rules, crisis protocols, simpler communication, structured choices and goal-based planning.

AI is now changing both the practice and the subject of behavioral finance. It can help advisers identify panic behavior, concentration, return chasing or deviations from a financial plan; personalize explanations; generate scenarios; and intervene before poor decisions are made. But the same capability can also be used to personalize persuasion, reinforce biases, or steer clients toward commercially attractive outcomes.

As clients increasingly use AI systems for investment research and as AI agents begin to move from recommending actions to executing them, the central question is no longer simply whether investors are biased. It is how human behavior, AI systems, adviser judgment and institutional incentives interact to shape financial outcomes.