Savvy investment firms realize the need to modernize their portfolio accounting software. An ideal path to achieve this is to update legacy portfolio accounting solutions with those that can harness the power of AI (artificial intelligence). By integrating AI into their investment management tech stack, organizations can automate and innovate based on their own proprietary workflows.
AI has become a supplemental tool for managing the portfolio accounting lifecycle, which includes investment accounting, reporting, performance, and client billing. Explore the transformative power of AI within portfolio accounting, its benefits, and why investment firms should consider replacing their legacy portfolio accounting vendors.
Understanding AI’s potential in Portfolio Accounting
Portfolio accounting is a key component for most investment managers. This area of the business requires robust software that can track, analyze, and report on asset values. Accomplishing this can create challenges related to data consolidation and reconciliation, resulting in inefficient workflows, tedious manual work, and delayed reporting. Enter AI as a potential solution to alleviate these challenges.
AI Can Help with Data Integration
As multiple data sources are needed within any portfolio accounting solution, consolidating data sources via a single platform is helpful.
Data aggregation challenges can prevent a timely and transparent view of asset values, investment diversification, and rates of return. As data has become ever more voluminous and complex, the industry is exploring whether AI can solve these problems.
With an AI-driven workflow for data aggregation, investment firms can future-proof their back-office operations and easily add more sources.
Smart Automation Drives Efficiency
AI can also elevate task automation. On a general level, AI routine can execute rules-based workflows to move a process to the next step. When there are stages requiring more in-depth decision-making, intelligent automation can support this and offer user recommendations based on past workflows.
In this scenario, natural language processing (NLP) can work in conjunction with machine learning to improve understanding of inefficient or repetitive workflows that are often complex. These efficiency gains support back office portfolio accounting positions across the firm.
Enabling AI-based workflow automation can reduce manual work and the risk of errors it carries.
Machine Learning Delivers Insights
Machine learning models work well as a means to manage data aggregation and integrity. After consolidating data, AI tools can analyze it and identify trends or patterns. Some of these will often be actionable, leading to making changes that benefit efficiency for the firm.
With the extensive historical data involved in portfolio accounting and performance-related activities, machine learning has the potential to provide predictive analytics since AI tools will be able to access historical data within the firms’ portfolio accounting software. With this data analytics, managers will be able to access potentially valuable information from their data.
AI Risk Remains
AI is sure to have a positive impact on investment firms’ operationally when it comes to their back office portfolio accounting activities. However, the industry needs to be aware of certain risks. First, data processing and sourcing must be compliant based on the firm’s own data privacy and security standards and adhere to the regulations that apply to the firm. This is especially important when it comes to large language models (LLM), which are used in generative AI tools like Chat GPT.
Second, there are always cybersecurity concerns when introducing new technology. Any portfolio accounting software replacement being considered should have layers of security to protect a firm’s data, including a SOC2 audit. When discussing options, firms should ask questions about data security practices and policies. For SaaS-based providers, a good question to ask is whether your client data will be commingled with other clients. In this respect, a private cloud-based solution should be preferred.
Key Benefits of AI in Portfolio Accounting
Investment firms can experience many advantages with an AI-powered portfolio accounting solution. As there is a mix of solutions available, one of the first things to consider is the practicality of the AI that is contemplated for us. Often, the focus of AI is its “flashiness” rather than its substance.
The practical side of AI offers many more tangible benefits, including greater data accuracy and speed for performing workflows and activities. Along with those gains, investment firms should consider the following areas when evaluating AI-powered portfolio accounting solutions over their legacy vendors.
More Accurate Reporting
AI tools can consolidate and enrich data, producing reports with an exceptional degree of accuracy. Investment firms must be accurate in reporting for obvious reasons. AI can help ensure the integrity and timeliness of the information used to generate reports.
Reduced Operational Expenses
It’s becoming increasingly expensive to manage a business, with additional fees and costs rising for technology. The latter is more controllable than the others. Transitioning to a consolidated AI-powered portfolio accounting platform that boosts efficiency and decision-making helps firms save on actual and opportunity costs gained from eliminating inefficient processes.
Upgrading investment management software to a SaaS-cloud-based system with AI can lower firms’ operational budgets over time.
Risk Management Improvements
Risk is unavoidable but can be managed more effectively with AI tools that provide data analytics. A sophisticated system can use both historical and real-time data to formulate near-real-time risk assessments.
AI Tools and Technologies Transforming Portfolio Accounting
Across the landscape of AI in portfolio accounting software, there are specific functionalities to seek out in a solution. These features provide the most value in streamlining and simplifying portfolio accounting activities when supplemented with AI-based approaches:
- Multi-instrument and multi-currency accounting: Ensure the portfolio accounting solution allows for the flexibility to access numerous and accepted methodologies for portfolio valuation, performance calculations, and NAV reporting.
- Integrated workflows of all the necessary tasks associated with portfolio accounting: Select a system that supports all of the workflows surrounding holdings and transaction archives, dividends, pricing, capital charges, and any transaction entry.
- Automated reconciliation: Prioritize back office managed services supplemented with AI technology to eliminate manual work and potential for errors.
- Performance measurement and attribution: Access this powerful analytical functionality to generate and store performance history.
- Advanced reporting: Implement a portfolio accounting solution that enables custom reporting and data visualizations.
- Fee structure customization: Eliminate manual work with a system that lets users tailor fee structures for different types of clients.
Future Trends in AI and Portfolio Accounting
What will AI tools help with next? AI is sure to become a more intertwined part of investment portfolio accounting software. Predictive analytics will improve as machine learning algorithms train on more industry-specific workflows and data.
Since compliance is also a crucial concern in portfolio accounting, especially the audit trails surrounding system usage, AI has some potential use cases there as well. AI is a big topic for discussion in conferences that deal with the Global Investment Performance Standards (GIPS).
Another emerging AI trend concerns faster and more accurate performance calculations. Calcs are already part of most platforms, and AI tools have the potential to enhance their capabilities.
Why Migrate to AI-Powered Portfolio Accounting Software?
AI has driven innovation in many facets of investment management and stands to do so in portfolio accounting, supporting data aggregation, automation, analytics, and more. It’s still in its infancy, with future capabilities that can further streamline processes and enhance performance.
Investment managers and wealth management firms should embrace AI to achieve operational efficiency and achieve better results. Stand out from competitors with an AI-driven strategy. Request a demo to learn more about how INDATA can help.
