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Transforming Asset Management: The Power of Gen AI

 

Several geopolitical, economic, and market events have placed stress on the asset management industry, particularly concerning Assets Under Management (AUM) and margins. Asset management firms must address three distinct dimensions to achieve significant growth in AUM and, consequently, margins. These dimensions include the capacity to deliver a best-in-class customer experience, the ability to efficiently scale operations at a low cost, and the innovation of distinctive services to fend off competition. 

Here are critical areas that demand the CEO’s attention: 

  • Customer experience:  The organization’s ability to cater to the varying needs of the customer at lightning speed is a differentiator; personalization and digital experience are the name of the game in the world of customer experience. 
  • Scalable operations:  Legacy systems and manual processes are major reasons for the asset manager’s margins being negatively impacted; use modern technology or ecosystems to reduce technical debt and transform business processes.  
  • Innovate:  Demand for improved risk management, alternatives, and crypto has grown in recent years.  These areas offer higher-margin business opportunities. To provide alternatives and crypto asset management, organizations need to develop product ecosystems by integrating third-party platforms. 

Putting customers at the forefront:

In reaction to margin challenges brought on by fee reductions, increasing costs, and higher regulatory requirements, asset management companies are looking for ways to enhance their market share. We examine how business leaders are reorienting their strategies to be more customer-centric. 

Gen AI can help asset managers in:

  • Tailoring personalized suggestions for portfolio holdings—ranging from ETFs and stocks to cryptocurrencies and mutual funds augmented by insights from investment research. 
  • Crafting performance narratives for personalized investor communication and reporting, enhancing transparency. 
  • Providing customized portfolio-specific commentary on the market disruptors, shockers, and drivers. 

By utilizing Gen AI’s capabilities, asset managers can build stronger client relationships, deliver more value, and differentiate themselves in a competitive market while being more customer-centric. 

Tackling scalability issues – Technical debt:  

Technical debt is a challenge often faced by investment managers, and unlike financial debt, it can’t be quantified. This issue becomes particularly frustrating when firms rely on outdated technology from vendors who haven’t updated their tools. 

As per AIMA, an estimated 80% of technology budgets are devoted to simply ‘keeping the lights on’ and maintaining, repairing, and updating old, legacy technology systems. That means only 20% of technology budgets are allocated to new solutions and functionality that can unlock business development and lower operational risk for asset managers. 

Gen AI can facilitate the modernization of legacy systems. It can analyze and refactor outdated or inefficient code into new state-of-the-art languages and frameworks, making it more streamlined and easier to maintain. This helps reduce technical debt by improving code quality and enabling a smoother transition to modern technology, ensuring asset managers can scale operations and operate efficiently and competitively in today’s fast-paced financial landscape. 

Navigating ahead with operational efficiencies and a competitive edge: 

Asset management firms should prioritize investments in emerging technologies like GenAI and cognitive solutions to enhance both operational efficiency and the overall customer experience. 

  • Gen AI can automate routine and time-consuming tasks, reducing operational costs and improving efficiency. 
  • It can streamline processes like data entry, reporting, and compliance checks, allowing staff to focus on more strategic activities. 
  • It can assist in identifying market opportunities and client demands, enabling asset managers to develop innovative investment products and strategies. 

By analyzing client feedback, performance data, and market benchmarks, Gen AI can suggest improvements to existing products. It can identify areas where products may have become dated and recommend updates or new features to maintain competitiveness and reduce R&D costs. 

Balancing uncertainty for resilience: 

To hedge against numerous risks, several asset management companies are implementing a proactive approach to risk assessment. Many are planning “what-if” scenarios to be ready for any regulatory changes or market occurrences. 

Gen AI can quickly and accurately evaluate enormous amounts of data, assisting asset managers in identifying possible risks and correlations that would not be obvious using conventional approaches. 

  • Delving into risk analysis, spanning liquidity, credit, and market risks, backed by corresponding confidence levels. 
  • Navigating tail risk with some confidence for unique scenarios. 

It can also help ensure compliance with evolving regulations by automating compliance checks and reporting, enabling asset managers to make informed decisions while maintaining the trust and confidence of clients and stakeholders. 

Final Thoughts 

CEOs of asset management companies must adopt new ways of thinking and conducting business if they are to succeed over the long term in the face of constant and rapid technological change and changes in the global economy. 

We have looked at some of their main worries, including the rapid advancement of technology and innovation, growing international competition from both established and upstart competitors, rising risks, an increasingly complex and shifting regulatory and market environment, and finally, shifting consumer needs and expectations. 

In conclusion, asset managers equipped with Gen AI are better poised to navigate challenges and seize opportunities, ultimately serving clients and thriving in this competitive landscape. However, they must be mindful of the ethical, regulatory, and operational considerations that come with the adoption of AI technologies. 

References 

How AI Is Adding Value In Wealth And Asset Management (forbes.com) 

Generative AI models — the risks and potential rewards in business (kpmg.com) 

Northern Trust | Wealth Management, Asset Management & Asset Servicing 

How asset managers can transform distribution (kpmg.us) 

A Guide to Marketing Strategy for Asset Managers – Edgefolio 

How GenAI Can Transform Asset Management | BCG 

The future of mainframe systems | Deloitte Insights 

The Mainstreaming of Alternative Investments (mckinsey.com) 

Megatrends and disruptions Consequences for Asset Management | Amundi Research Center 

top-concerns-of-asset-management-ceos.pdf (kpmg.com) 

Tech debt: The vicious cycle of legacy tech in asset management (aima.org) 

About the Author

V Krishnamoorthy

V Krishnamoorthy

I'm an enthusiastic newcomer to the world of finance, armed with fresh insights and a thirst for knowledge. Recently graduated with a dual background in engineering and an MBA with a focus on finance. During my academic journey, I interned at Union Bank of India in the Treasury Department, where I gained hands-on experience working on the bank's investment portfolio. This experience allowed me to dive deep into the intricacies of financial markets and investment strategies. Additionally, my internship at Mirae Asset Mutual Fund placed me in the Product and Sales team, where I contributed to a project aimed at enhancing fixed income mutual fund penetration. This experience sharpened my understanding of market dynamics and product development. As a beginner in the finance industry, I'm committed to continuous learning and growth, with a keen interest in contributing to innovative financial solutions in this ever-evolving field.

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