Despite the proliferation of powerful data analytics and advanced portfolio tools, many investment firms still rely on overburdened internal teams struggling to keep up with portfolio performance and risk management demands. The gap between available technology and practical application hinders their ability to gain timely insights. In an era defined by generative AI and predictive analytics, asset managers and investors need more than basic spreadsheets or generic software to thrive.
Many asset managers and investors still depend on traditional methods and internal teams that lack the specialized skills for deep data analysis. In increasingly interconnected financial markets, sophisticated analytics are no longer optional for money managers to survive. The industry needs to recognize that the most successful global asset managers thrive not only due to their top talent, but also because their investment in technology far surpasses that of smaller industry players.
Smaller firms often attempt to bridge this gap by investing in generic analytics software that they don’t fully understand, and which often cannot adapt to suit their specific needs.
This approach can result in several challenges:
Collaborating with a specialized firm could solve these challenges, providing deep insights into portfolios and delivering non-negligible benefits in the process.
By outsourcing analytics tasks, portfolio managers get to spend more time interpreting advanced analytics, leading to better performance. Internal teams can then focus on strategy development and client engagement and enhancing the quality of client service.
Analytics firms specialize in the latest tools and methodologies, using sophisticated algorithms and proprietary models to deliver insights to clients. Clients get access to advanced risk assessments, performance attributions, and scenario analyses that are challenging to replicate internally without significant technological and educational investments.
Unlike generic software, an analytics partnership offers high customization, aligning services with specific investment strategies, data sources, and regulatory requirements. This ensures that insights are directly relevant.
As firms grow, their analytics needs tend to become more complex. An analytics partner can scale services to match this growth, leading to cost efficiencies, while allowing the manager to lean on the expertise and infrastructure of the partner firm.
An analytics partner brings industry best practices into the client organization. Drawing insights from a diverse client base, gaining insights into strategies across different contexts.
As investor sophistication continues to increase, managers are confronted with an increasingly complex landscape, requiring them to deliver deeper insights into performance across various scenarios and risk factor interactions. At the same time, regulatory requirements are becoming more stringent, demanding strict risk management and transparency. An analytics partnership ensures compliance with current regulations and adopts best practices for overall governance.
Advancements in technology, such as machine learning and big data analytics, offer new opportunities for financial analysis. Leveraging these technologies, however, requires specialized skills and significant investment. An analytics partner provides access to these technologies, offering a strategic advantage for asset managers, family offices, and institutional investors. These organizations can now transform how they operate and deliver better results — without the need for substantial internal investment.
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Kevin Becker is a Co-Founder and CEO of Kiski. Connect with him on LinkedIn here.