Industry
Banking
Banking Services Transformation: Unlocking Exponential Value
Highlights
- Leveraging Business Process Management (BPM) frameworks and AI-driven automation enable mutual funds to achieve near real time NAV computation by streamlining key accounting functions.
- By integrating AI within well-orchestrated BPM workflows, fund accounting firms can enhance data integrity, exception management, and process transparency.
- This convergence minimizes manual touchpoints, reduces latency, and moves fund accounting from the conventional end-of-day cycle to a near real-time NAV environment.
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Background
The mutual fund industry is at an inflection point shaped by increasing regulatory oversight and growing investor demand for speed and transparency. Traditional fund accounting processes built around end-of-day NAV recalculation are struggling to keep pace with real-time market movements and operational complexity. Emerging technologies such as AI and GenAI, when embedded with Business Process Management (BPM) frameworks, offer a path to reimagine fund accounting as a dynamic, data-driven ecosystem. Fund administrators can leverage AI-enabled automation, predictive analysis, and process orchestration to achieve near real-time NAV re-calculations, ensuring valuations reflect the market as it moves.
The Fund Accounting practice - T+1 holding.
Mutual funds in the US do not use the current day’s portfolio holdings to calculate the Net asset values (NAV). Instead, the previous day’s holdings are valued at the current day’s closing prices, and that becomes the NAV at which investors buy or sell shares (units) of the fund. This method is allowable under SEC Rule 2a-4 which was constructed many decades ago and not revised for various reasons. One of the reasons could be that in the times when technological interventions were few, gathering the daily portfolio changes before the deadline was a tedious task.
With the new digital technologies, this practice could be changed for the better. The investors will benefit as a result of accurate pricing. There will be better investor trust, better compliance, and it will be in line with the best accounting practices.
But the question remains if the investors would still get a fair deal if the NAVs were computed at the end of each day on the current day’s trades. While the markets prices of securities fluctuate by the fraction of a second, the NAV still must wait for the end of the day.
Of course, there are ETFs which trade on real time which partly address this issue of pricing, but those prices are based on market forces viz. demand and supply than a scientific basis of valuation.
While these challenges exist, would it be possible to compute NAVs on a real time basis?
It may seem ambitious to think about it currently. But the answer would lie in the ability to bring in the relevant technologies for each of the sub-processes in the fund accounting process. It will depend on how intelligently BPM principles and AI/GenAI technologies are applied across the fund accounting value chain. Let us examine the key considerations -
If all trades are booked in real time (e.g. via Swift), then it will address the issue of batching of trades which is done on T+1 under the present scheme of things. However, this alone will not be the answer. These securities ought to be priced with the real time market prices. There are various activities involved like price scrubbing and validations which are done to arrive at the prices. AI-driven trade capture can be embedded into a streamlined booking workflow, ensuring trades move seamlessly from confirmation to data input in the system. GenAI can enable intelligent capture, validation, and autobooking of trades in real time eliminating batch dependencies.
- Intelligent Capture & Validation: Enable reading of trades from multiple sources (emails, PDF, SWIFT, etc) and auto extract the key details. Validation engine can cross-check trade attributes against business rules and flag exceptions.
- Auto-Booking: Populate trade and book directly in the core system without manual intervention.
There are also other accounting aspects like income and expense recognition. Since these are provided for and are done on an accrual basis, it will not be as complex an issue to deal with. Similarly, trade fail issues can be identified by deploying Artificial Intelligence tools which can predict trade failures and prevent potential regulatory issues.
BPM Process orchestration – automate the end-to-end flow of capturing dividends, interest accruals, fees and expenses and ensuring these are posted in near real time. The rules for accruals should be defined as per the prevailing accounting standards.
This an important function in the process – be it the reconciliations with the Transfer agents, custodian, or other internal stakeholders. But if the accuracy of the transactions can be ensured with straight through processing, there is little need for reconciling items and that could lead to cost leverage in the longer run.
BPM Process orchestration can be deployed to structure the reconciliation workflow from ingesting custody reports to resolving breaks.
AI-Enabled matching can support in aligning the FA books with the Custody booking in shorter batch runs.
Corporate actions which affect the fund’s securities need to be evaluated for their impact and entries have to be recorded as applicable. These announcements come in at various intervals and can be tricky if not applied correctly. However, with Swift messaging and better interfaces with the data vendors most of these issues can be alleviated.
BPM process orchestration can help establish a structured lifecycle for corporate actions from announcement capture to posting and ensure there are no misses.
AI enabled capture and classification from multiple sources (Custodians, depositories, market data vendors, corporate actions group emails etc) will help in automatically classifying them into categories. However, more complex / exotic actions will need to be looked at on case-to-case basis.
AI copilots can assist fund accountants by continuously monitoring exception queues, analyzing root causes of breaks, and suggesting resolution steps based on historical data. LLM based knowledge layers act as an intelligent interpreter. They can help read and understand fund specific rules, regulatory updates, and adapt workflow rules dynamically. This helps ensure that the process stays compliant and up-to-date.
Opportunities/ Takeaways
BPM and AI together are redefining fund accounting – turning it into an intelligent, compliant, and adaptive ecosystem. BPM serves as a strategic backbone ensuring controls and resilience, while GenAI drives predictive insights, exception resolution and faster reconciliations.
Use cases like predictive NAV monitoring, AI-assisted exception handling, and dynamic compliance validation show how human expertise can be augmented for speed and accuracy. The goal is a continuous audit and near real-time operations model, where fund accounting responds instantly to market shifts and strengthens both efficiency and investor confidence.
Conclusion
Fund accounting should be looked at as a strategic enabler of transparency, compliance and investor trust.
With BPM principles and leveraging AI/GenAI across critical processes, we can ensure a future ready fund accounting ecosystem. We could certainly move to a shorter time interval for NAV computations – perhaps on an hourly basis. This would then pave the way for real time NAV computation in the future
When investors start expecting real-time fund valuation, will your fund accounting ecosystem be equipped for that reality?