At the Hubbis India Wealth Management Forum 2026, Anant Agarwal, Head of Growth & Partnerships at MProfit, examined how artificial intelligence (AI) could change the way India’s family offices and wealth advisers manage increasingly complex portfolios.
His presentation started with the growth of private wealth. Family offices are becoming more common, liquidity events are creating fresh pools of investible capital and wealthy families have far more investment choices than they did a decade or two ago. The drawback is complexity. Assets, valuations and performance data can sit across numerous managers, brokers, entities and reporting formats.
Agarwal sees AI as one way to reduce the administrative burden. Reporting, analytics and other back-office tasks can increasingly be handled by technology, giving advisers more time to interpret information, understand the family and deal with investment, governance and succession questions.
Key Takeaways
Growing Wealth Is Creating More Complex Portfolios: India’s family office sector is expanding while the investment universe available to wealthy families becomes broader.
Diversification Creates A Data Problem: Portfolio management services (PMS), alternative investment funds (AIFs), private markets, listed securities and other holdings often arrive with separate statements and reporting formats.
AI Can Make Advisers More Productive: Agarwal compared the development with online medical information, where better-informed patients changed the doctor’s role without removing the need for medical judgement.
Financial Services Already Offers Evidence At Scale: Bajaj Finance has used AI to process millions of customer calls and generate loan opportunities, showing where automation can handle volumes that would be difficult to process manually.
The Next Generation Expects Faster Information: Younger family office decision-makers increasingly want interactive, on-demand portfolio information instead of static reports and lengthy spreadsheets.
Technology Can Ease The Adviser Talent Crunch: Automating administrative work leaves scarce human talent available for relationship management and advice.
Good AI Depends On Good Data: Useful analysis requires portfolio information to be organised across assets, entities and providers.
AI Outputs Still Need Oversight: MProfit’s AI Connector allows authorised portfolio data to be used with third-party AI services, while users are told to verify outputs independently before acting.
More Wealth, More Complexity
Agarwal began with a change he has watched during MProfit’s 17 years in the Indian market.
Promoters once tended to recycle a large proportion of their wealth into the operating business. Today, business sales, listings and other liquidity events are giving families more capital to allocate separately, and dedicated family offices have become more common.
The presentation highlighted the concentration of financial wealth among the country’s wealthiest households. Its USD 4.5 trillion figure refers to financial assets held by that household segment, indicating the growth within the top of India’s wealth pyramid. Investors also have a far wider menu of products. Agarwal recalled a market centred largely on insurance, housing, equities and mutual funds. Wealthy families can now add PMS strategies, AIFs, private equity, pre-initial public offering investments, unlisted securities, real estate investment trusts (REITs), infrastructure investment trusts (InvITs), derivatives and specialised investment funds (SIFs).
The Liberalised Remittance Scheme (LRS), which also appeared in the presentation, is different. It is the Reserve Bank of India framework under which resident individuals can remit funds overseas for eligible purposes, including permitted investments.
As portfolios spread across more products and providers, assembling a single view becomes harder.
“Every product, asset manager and fund gives you a report in its own format,” Agarwal said. “But the family ultimately wants to know one thing: what does my total wealth look like?”
AI As An Adviser Multiplier
Agarwal used medicine to illustrate how he expects AI to affect wealth management.
When Google, WebMD and similar services became widely available, some expected easier access to medical information to reduce the need for doctors. Patients instead became better informed before they reached the consulting room.
“Technology made patients more informed; it did not remove the doctor,” Agarwal said. “AI can do the same in wealth management.”
Clients can retrieve more information for themselves and are likely to arrive with more questions. The adviser still has to interpret the information, establish what is relevant and decide how it fits the family’s circumstances.
MProfit’s presentation described this as a combination of informed investors and empowered wealth advisers.
Routine portfolio queries and basic analysis can increasingly be handled through software. Time spent with the client can then move towards portfolio decisions, family objectives, governance, estate planning and succession.
AI At Scale
Agarwal used Bajaj Finance to show how AI is already being applied within financial services.
During Q3 FY2026, the company said AI processed 20 million customer calls by converting voice into text. Text-to-data conversion covered 520,000 customer interactions and generated 100,000 new offers. Its AI-enabled call centre produced around INR 1,600 crore in loan disbursements, roughly 10% of the quarter’s total.
“Think about what it would take for people to listen to those calls one by one,” Agarwal said. “Technology can find patterns across a volume of information that a human team simply cannot work through in the same way.”
Wealth management will use the technology differently, but high-volume processing, pattern recognition and repetitive operational work are obvious candidates for automation.
The Next Generation Wants Answers Faster
Family-office decision-makers are changing as well. Agarwal described younger family members returning from universities in India and overseas and deciding whether to enter the family business, pursue another direction or establish a family office around wealth that has already been created.
Their expectations of reporting are markedly different from the systems many families have used in the past.
Static multi-page statements, complicated spreadsheets and calls to accountants or relationship managers can feel slow when the user is accustomed to retrieving information immediately elsewhere.
“The next generation does not have that patience,” Agarwal said. “They want to ask a question and get the answer in seconds.”
They may want to know the family’s return over ten years, identify its strongest-performing PMS strategy or see its exposure to a particular asset class. A market event can prompt a more immediate question about how the family’s holdings are affected.
MProfit’s presentation contrasted manually consolidated reports with interactive reporting and AI-powered insights.
There is some nuance around speed. Stocks and exchange-traded funds can receive frequent market-price updates, while mutual fund net asset values and other instruments update on different schedules. For a diversified family portfolio, on-demand consolidated analytics is more precise than describing every holding as continuously real-time.
Technology And The Talent Crunch
The growth of family offices is also creating a capacity problem.
Experienced advisers remain a finite resource. If each new relationship brings another layer of reconciliation, reporting and manual administration, scaling the business becomes increasingly expensive.
MProfit’s presentation proposed concentrating human resources in relationship-centred front-office roles and using technology for more of the back office.
“Your job as an adviser is not to spend countless hours building dashboards,” Agarwal said. “Your time should be spent speaking with clients and understanding what they actually need.”
He pointed to governance, estate planning and family objectives as areas where understanding the client remains important. Automating reporting and administration can free advisers to spend more time on those discussions.
Getting The Data Into One Place
MProfit sits at the portfolio-data layer beneath many of these use cases.
The company launched commercially in 2009 and has developed as a portfolio aggregation, analytics and reporting platform for high net worth (HNW) investors, ultra-high net worth (UHNW) families, family offices and wealth professionals.
Its platform brings holdings across entities, products, asset classes and financial institutions into a consolidated portfolio view.
That becomes particularly relevant when AI is added to the process. A system asked about a family’s overall portfolio needs access to sufficiently complete and well-organised underlying information.
“Will AI replace MProfit? No,” Agarwal said. “Can AI make our lives easier and our clients’ lives easier? Yes.”
MProfit has begun applying that approach through its AI Connector. Terms updated in July 2026 describe a user-authorised connection that can transmit portfolio data through the Model Context Protocol (MCP) to third-party AI services including ChatGPT and Claudei.
MProfit also states that it does not verify or endorse responses generated by those external AI systems and advises users to check the output independently before making decisions.
The connector gives users another way to interrogate portfolio data. The answer still needs scrutiny.
Where The Adviser Adds Value
Agarwal closed with the work that remains most valuable for the human adviser.
Technology can consolidate data, carry out repetitive processing and retrieve information quickly. Advisers are still needed to interpret what the information means for a particular family.
If a client can obtain a performance figure immediately, supplying that figure is no longer much of an advisory service. The useful conversation is why performance looks the way it does, whether the portfolio remains appropriate and what the family should do next.
“Focus on what you are good at,” Agarwal said. “Let technology take care of the work that can be automated, and spend your time where your expertise matters.”
India’s family-office market is expanding into a wider and more complicated investment universe. Agarwal’s case was that wealth firms should use AI to absorb more of the processing burden, while keeping advisers focused on the parts of the relationship where context and judgement still count.