Advanced Risk Management

Published on February 25, 2025 by Priya Vaidyanathan and Nuwan Jayawardana CFA

AI is reshaping risk and compliance, enabling firms to stay ahead with predictive insights and proactive strategies.

In the near term, AI will empower firms to strengthen both risk and compliance management through real-time monitoring, automated reporting and rapid detection of market volatility or regulatory anomalies. These capabilities would help firms mitigate risks arising from sudden market volatility while remaining compliant with evolving regulations, reducing the risk of costly breaches.

In the longer run, the role of AI will likely widen to predictive compliance and proactive risk management. By leveraging advanced analytics, asset managers would be able to anticipate market manipulation, assess their impact and adjust strategies proactively. Firms that integrate AI-driven insights into their risk management and compliance processes are likely to gain a competitive advantage as the regulatory environment continues to evolve.

To fully realise the potential of AI, firms must combine AI strategy with complementary measures. Talent development is crucial; asset managers need to upskill their workforces to ensure that staff can effectively work alongside AI solutions. Moreover, strategic partnerships would be essential for accessing external expertise and remaining ahead of rapid AI advancements. Strong governance systems would be crucial for ensuring the ethical application of AI solutions and compliance with evolving regulations. Furthermore, data infrastructure would need to be optimised continually to ensure the data feeding AI solutions is accurate, secure and verifiable.

However, these complementary measures could be challenging to implement, especially for midsize firms, due to their resource-intensive nature and time to execute. This increases the strategic role that outsourcing can play. Knowledge process outsourcing (KPO) providers such as Acuity Knowledge Partners (Acuity) can be highly effective in terms of access to specialised expertise, technology resources and compliance support for asset managers to integrate AI into their operations. Moreover, outsourcing enables firms to minimise risks and costs associated with AI integration while enabling them to focus on their core strengths and remain competitive in a fast-evolving market.

AI’s potential as a transformative tool for the asset management sector is clear; however, it is not a silver bullet that can solve all challenges. AI-driven solutions would be a crucial part of strategies to enhance operational efficiency, improve client management and mitigate risk, particularly in the medium to long term. However, the limitations of these technologies cannot be ignored.

For instance, AI systems are only as good as the data they are trained on. They may lack the subtlety of human judgement, ethical perspective and emotional intelligence in maintaining client relationships. Additionally, the brisk pace of technological advancement means that AI solutions require continued updates and refinements to remain relevant. The successful rollout of AI solutions also requires significant investment in both infrastructure and talent. Moreover, firms must navigate complex regulatory frameworks where the use of AI creates compliance-related challenges. Furthermore, while automation would be a low-hanging fruit for AI, it cannot fully replace the strategic insights and judgement of seasoned professionals. It will remain challenging for a while for AI to completely replace tasks such as fundamental investment research that demand highly accurate and verifiable information along with human judgement, experience and expertise. Human judgement remains critical in interpreting AI-generated insights and making sustainable decisions that align with short-term and long-term objectives of businesses.

Read the full outlook for Asset Management 2025 here.

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