Tech-driven finance upgrades for asset managers


Embrace tech to enhance reporting, FP&A and compliance


It’s often prudent to consider whether a widespread trend has applications close to home.


Asset management firm leaders fully understand the market returns technology companies have provided in recent months. At the same time, their firms may have finance functions that are weighed down with operational deficiencies and outdated reporting systems while they face increasing regulatory demands. To address these issues, it may be time for them to explore leading-edge technologies to be incorporated into their own finance organizations.

Headshot of Michael Patanella

“Asset management firms of all different sizes can benefit from modernizing their finance functions.”

Michael Patanella

Grant Thornton National Managing Partner, Asset Management


Finance modernization can deliver the improved operational efficiency demanded by investors, enhanced decision-making capabilities sought by front offices and regulatory compliance to meet ever-increasing oversight demands.


“Asset management firms of all different sizes can benefit from modernizing their finance functions,” said Grant Thornton National Managing Partner for Asset Management Michael Patanella. “Depending on the dollar amounts that they are able to spend, they may find it necessary to approach these improvements in phases. It’s important to set long-term goals, but you can accomplish them in steps or stages.”


The need for finance modernization can be seen when any combination of the following factors is present:

  • Outdated technology
  • Limited automation
  • Manual, Excel-based or archaic business processes
  • Decentralized finance operations performed across multiple locations
  • Institutional knowledge concentrated in a few individuals
  • Deficiencies in employee skills and developmental opportunities
  • Lack of data integrity and accuracy
  • Hindered analytical efforts due to burdensome data validation
  • Inefficient and lengthy month-end close processes
  • Limited planning, budgeting, and forecasting outputs and insights

At an asset management firm, these challenges can be exacerbated by complex reporting and data management requirements across diverse asset classes, as well as manual, complex waterfall calculations. Some asset managers are struggling with intricate valuation model challenges, one-dimensional client portals, increasingly complex fund structures and financial instruments, and cumbersome transformation of custodian and administrator data.


That said, the data challenge may be most vexing for asset management leaders. It’s imperative for them to understand that the foundation for automation and AI — including generative AI — is standard, centralized, timely and accurate data. Historically, finance functions have used sheer will and numerous staff hours to meet the challenges posed by manual processes, decentralized systems, and inconsistent data.


However, the landscape is changing. AI technologies are advancing at a rate that far exceeds the human capacity to manage data. Without a foundation of clean, orderly data, organizations won’t have the capability to harness the full potential of AI. It’s crucial now for CFOs to assess their data maturity and prioritize the modernization of their finance functions as a strategic imperative to thrive in an AI-driven future. This approach aligns with today’s technological advancements and provides a structured pathway for asset managers to significantly improve their operational efficiency and data integrity while preparing to incorporate AI.


Value-driven finance transformation is critical to accommodate future growth. Transformation is the key to remaining competitive against peers, serving customers better, controlling rising labor costs, and seamlessly managing data and reports to drive enhanced business decisions while asset managers focus on differentiation and the maintenance of their overall brand.


In a well-executed finance modernization exercise, performance improvement is evolutionary and sustainable. Once improvement opportunities are identified, they should be linked to return-on-investment metrics that will be tracked through execution. These metrics may measure:

  • Operating cost reductions
  • Operational efficiency and productivity increases
  • Creation of new or alternative revenue
  • Improvement of the customer and/or user experience
  • Creation of additional resource capacity
  • Enhancement of analytical insights that support both internal and external reporting
Headshot of Vikram Gupta

“The lifeblood of this industry is data and processes…When there is more exposure to data and processes, artificial intelligence can play a bigger role.”

Vikram Gupta

Grant Thornton Director, CFO Advisory

In the asset management industry, technological advancements have democratized the ability to scrutinize all these metrics. In the past, the largest asset managers had a competitive advantage due to their scalability, as their large staffs could run models, prepare reports and discover strategic insights that were cost-prohibitive for firms with smaller client bases.


Now technology has leveled the playing field by making critical, data-driven insights available to everyone for a more affordable price.


“The lifeblood of this industry is data and processes, which they’re dependent on to provide their services,” said Grant Thornton CFO Advisory Director Vikram Gupta. “When there is more exposure to data and processes, artificial intelligence can play a bigger role in providing direction than it would in a product-based industry.”



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Modernizing record-to-report functions


Although firms strive to be timely with their reporting, many finance and accounting teams in the asset management industry struggle to produce a timely, standardized and efficient close. Monthly close processes can take as little as three business days if automation is used effectively, but 10 business days or longer if the organization does not use automation and integrated systems. Simultaneously, more complex fund structures and the new SEC private funds rule have increased demand on asset manager finance and accounting functions to produce more quarterly and annual financial statements.


“The month-end close and financial reporting of asset managers continue to be a pain point for finance and accounting teams due to a variety of reasons,” said Grant Thornton CFO Advisory Senior Associate Malika Murodova.


Finance professionals can encounter:

  • Manual errors
  • Outdated knowledge of GAAP and IFRS
  • Inadequate review processes
  • Inefficient controls
  • Poor knowledge of business process maps and existing software capabilities

Furthermore, reporting and the monthly close rely on static reports that seem far too robust for timely updates — that is, until these processes are enhanced with technology.


“Automation and artificial intelligence can enhance the monthly close and financial reporting in limitless ways as new technology emerges,” Gupta said. “These enhancements include many immediate fixes that can greatly relieve the pain points.”



Immediate fixes made possible by automation, RPA and AI include:

  • Reduced human error. Correctly configured data automation results in 100% accuracy.
  • Decreased hours spent on repetitive tasks such as rolling forward financial statements, basic calculations, and formatting.
  • Increased productivity. Relief from tedious, manual tasks will enable professionals to focus on complex issues within their function.
  • Lower overhead. Automation can free up capital to invest in existing employees and other expenditures.
  • Clear mapping of system interactions through business process mining and automation. This can enable enforcement of internal controls and the maximization of software capabilities.
  • Dynamic reporting. AI and automation can produce reporting live by analyzing the reporting needs/requirements and configuring the ERP to generate the relevant reporting package.
  • Immediate analysis. AI can read patterns in financial data to analyze trends and predictive behaviors. A written or visual analysis will be available immediately instead of relying on the availability of team members.
  • Run on schedule. Regularly scheduled reports, reminders or task catalysts could be automated to prevent delinquency or overload.

AI can enhance the financial reporting review process by acting as the preliminary reviewer, identifying outliers, and generating variance commentary and disclosures. AI also can free up associates’ workload by creating routine client communication and marketing data and summarizing daily market data, allowing junior associates to focus more on strategic operations.


Establishing policies and governance over AI use has become essential as employees using AI (particularly open-source tools) in the absence of guidance may expose a firm to cybersecurity or data privacy risks. Strong oversight and clear communication can enable AI tools to augment operational integrity instead of compromising it.


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Getting more out of your FP&A


Today’s FP&A operations need to move far beyond their traditional budgeting and variance analyses to provide continuous financial and operational forecasting aligned with business needs. Despite the obvious need, many asset management firms still rely on outdated processes and technology that hinders real-time insights and decision-making.


This challenge can be addressed by integrating AI and machine learning into FP&A processes and enabling data-driven forecasts, ad hoc scenario planning, and “what-if” analyses to improve accuracy and drive innovation across the firm.


“Modern planning platforms empower financial planners to produce accurate plans, enhance insights, and optimize demand forecasts,” Murodova said. “These solutions eliminate manual efforts, accommodate unlimited scenarios and variables, and offer real-time insights to augment decision-making.”


AI-powered planning solutions steadily learn from data, detecting anomalies and errors in real time, and increasing accuracy and efficiency. Comparative analytics enable teams to efficiently identify differences between forecasts, budgets and scenarios, providing accuracy and predictability.


Furthermore, predictive forecasting capabilities incorporate historical and external data, such as interest rate trends, market outlooks and industry benchmarks, enriching and improving forecasts for better future planning. AI and machine learning integration revolutionize FP&A processes, enabling organizations to adapt to dynamic business environments and maintain a competitive edge.


Enabling regulatory compliance


Asset management and banking CFOs cited regulatory compliance as their top concern in a recent Grant Thornton survey, and it’s easy to see why.


The SEC’s new private fund regulations are scheduled to take effect soon, and the SEC’s new climate disclosure rules will drive changes in the reporting of firms that are subject to the SEC’s compliance requirements.


“As you embrace a new regulation and its requirements, think more broadly about the different processes you can address related to that regulatory compliance activity,” Patanella said. “There are likely to be opportunities to do more than comply with the rule, and to improve associated processes and get more value out of the changes you’re making.”


Of course, modernization efforts in the finance function represent just a portion of the overall work that risk, compliance and internal audit leaders need to do to drive regulatory compliance efforts throughout the organization. But in finance, compliance efforts can be aided by tools that:

  • Identify gaps in internal controls.
  • Continuously monitor changes in regulatory requirements.
  • Analyze the reporting of competitors and other organizations to determine best practices for reporting.
  • Scour enforcement actions by regulators for commonalities that indicate compliance risks.

Meanwhile, firms that outsource risk management activities may be able to take advantage of third parties’ use of AI tools. For example, Grant Thornton professionals use CompliAI™, a tool with generative AI functionality that the firm developed using Microsoft technology, to streamline clients’ control design and assessment processes.


Overcoming obstacles


Asset management leaders sometimes have difficulty producing custom reporting because their back-office functions have been outsourced to third parties with inflexible reporting procedures and structures. In other cases, their software provider’s general ledger or ERP system doesn’t support the way they manage their business, so they feel like they are trying to fit a square peg into a round hole.


In either case, this need for customization can result in team members spending a lot of time pulling customized reports that are manual and repetitive. The good news is that this, too, is a process that firms can address through RPA. Private equity funds, meanwhile, are using tools such as RPA to transform the data they receive from fund administrators into the format they desire.


Managing disparate data sources, integrating systems after mergers and acquisitions, and navigating outsourcing or vendor relationships are all common challenges for asset management firm finance functions. Grant Thornton has assisted clients in overcoming these obstacles by adopting a strategic approach to data governance, prioritizing system interoperability, and working with vendors and partners to establish data standardization and timeliness.


“Addressing these challenges requires a robust strategy that includes streamlining vendor relations to ensure uniform data delivery and investing in technology solutions that can integrate and cleanse data, paving the way for a seamless and efficient finance modernization journey,” said Grant Thornton CFO Advisory Senior Manager George Alexander.


After M&A, meanwhile, firms need a focused effort on system integration to achieve a unified, efficient operational framework that enables seamless data consolidation, reporting and month-end close.


Driven by the CFO


As organizations prepare to embark on their finance transformation journey, the active and visible support of executive leadership, led by the CFO, is one of the key drivers for the success of any finance modernization program. It’s critical that the CFO and the executive letingadership team start by developing a clear, uniform vision and set the tone at the top with the aim of empowering those who deliver the improvements, which will then trickle down to all affected end-users.


“Based on the long-term growth goals established within their enterprise, CFOs must be intimately involved in defining their overall organizational vision, key success criteria, and program objectives to be achieved throughout any transformation effort to drive strategic direction and maximize sustained value,” said Grant Thornton CFO Advisory Managing Director Patrick Boruta.


At the same time, it’s important for CFOs to build support throughout the organization surrounding the financial modernization effort. Since finance processes are intertwined throughout the organization, CFOs need to clearly articulate the drivers and rationale fueling the change in addition to the upstream and downstream impacts that the transformation may have on other departments. The expected benefits and return on investment should also be communicated throughout the organization.


“CFOs need to obtain approval and buy-in so the organization will realize maximum value from these improvements,” Patanella said.


It’s critical for CFOs to enlist organizational change management personnel and processes from the very start of the finance modernization work. Larger asset management firms are likely to have dedicated change management functions to assess stakeholder impacts and craft internal and external program communications tailored to the appropriate stakeholder groups. Change management will ensure that proper impact assessments, user readiness and training methods are used to facilitate a seamless transition and enhanced user preparedness and adoption of their newly defined target operating model.


At smaller asset management firms, CFOs may have to take the lead in the change management process, enlisting the help of human resources and perhaps other functions to manage the transition. Smaller firms that contract with a third party for finance modernization services may also use the contractor’s dedicated change management services to assist with the effort.


Finally, once transformative change has been executed, it’s important for firms to establish a governing body or process to ensure long-term value is sustained and that there is an organizational commitment to maintain incremental performance improvement into the future. Many organizations use third parties to assist with managing continuous improvement, but an in-house dedicated team is recommended to keep the effort focused and ensure there is follow -through.


Where to start


Asset management firms that undertake finance modernization may vary greatly on the maturity curve when they start this process. Regardless of where they begin, though, it’s possible to drive continuous improvement — whether it’s from nascent to baseline or from advanced to optimized.


Firms with less mature finance functions will need to launch their modernization efforts by getting the basics in place, including effective processes for booking transactions, seamlessly working with vendors and customers, consolidating data, and developing the necessary internal and external reports. Finance organizations that already have the appropriate foundation in place will have more flexibility in determining which improvements are most desirable.


“Regardless of the maturity of your finance function or the improvement opportunities that you choose to pursue, you still need to perform a prioritization assessment, which links each identified enhancement to a clear ROI,” Boruta said.


Many asset management finance leaders are working with disparate processes and systems that are increasingly difficult to manage through manual workarounds. A current-state assessment can highlight key reporting needs, identify broken processes and inadequate data, and help firms prioritize their standardization, centralization and automation efforts.


An assessment can help finance leaders align with technological advancements and provide a structured pathway for improving operational efficiency and data integrity to enable the successful adoption of AI. Implementation of AI also requires the development of policies and procedures that align with organizational principles and the board’s oversight.


The most elementary and basic strategy, though, is to get started. The most competitive companies in the market are developing technology applications that organizations in all industries will use to make improvements that asset management and finance functions will need to achieve efficiencies and accelerate growth as well.


Your competitors may be using these tools soon — or they may already be using them. Modernizing your own finance processes and enabling technologies can help you keep pace, and hopefully drive the necessary differentiation to keep you ahead of your competition.




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