Financial Services
How AI and automation are disrupting asset management solutions
Artificial Intelligence (AI) and automation are transforming the asset management industry by redefining traditional operational models and enhancing client value delivery. Integrating AI into asset management solutions is not merely a trend but a fundamental shift toward data-driven decision-making.
By leveraging AI-powered systems, asset management companies can optimise portfolio performance, enhance risk assessment, and deliver highly personalised investment strategies at scale. AI's ability to analyse vast datasets, identify intricate patterns, and forecast market trends far surpasses human capabilities.
Tasks that previously took analysts' days can now be processed in minutes, enabling real-time insights and proactive responses to market fluctuations. This evolution positions AI as a critical driver of efficiency, accuracy, and innovation in modern asset management.
AI technologies revolutionising asset management
AI encompasses a range of technologies that are revolutionising asset management. Below are key AI-driven technologies and their applications:
Machine learning (ML)
ML employs advanced algorithms to analyse data patterns and improve performance over time. In asset management, ML algorithms predict equipment failures, optimise maintenance schedules, and enhance decision-making processes by interpreting complex datasets.
For instance, ML models can analyse historical performance data to predict the remaining useful life (RUL) of assets, enabling predictive maintenance and reducing unexpected downtimes.
Neural networks
Neural networks mimic the human brain's structure to process information and make intelligent predictions. These networks play a crucial role in predictive maintenance models by identifying minor irregularities in asset performance and anticipating potential issues before they arise.
Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) are primarily used to analyse time-series data and identify patterns indicative of asset deterioration.
Optical character recognition (OCR)
Optical Character Recognition (OCR) technology extracts text from physical documents or labels and converts it into digital data. In asset management, OCR simplifies data collection by scanning tags and barcodes, minimising manual errors, and expediting data integration into asset management systems. This ensures seamless tracking and updating of asset information, improving data accuracy and completeness.
Generative AI (GenAI)
GenAI employs advanced algorithms to generate insights and recommendations based on historical data. This technology provides diagnostic guidance by analysing past actions, suggesting corrective measures, and offering real-time assistance for troubleshooting asset performance issues.
GenAI models, such as Generative Adversarial Networks (GANs) and Transformer-based architectures, can simulate various scenarios to predict asset behaviour under different conditions, aiding in strategic planning and optimisation.
AI-powered solutions for asset management
AI and automation offer transformative solutions to address core strategic challenges faced by asset managers. Below are key applications:
Enhanced alpha generation
AI-driven algorithms, powered by sophisticated machine learning models, can analyse vast datasets, including alternative data sources. This capability enables the detection of intricate market inefficiencies and predictive patterns that may elude human analysts.
By leveraging real-time data processing and advanced statistical techniques, these algorithms optimise trade execution, refine investment strategies, and enhance risk-adjusted returns, ultimately driving superior alpha generation.
Proactive risk management
Traditional risk models often lack the agility to adapt to rapidly evolving market conditions. AI-powered asset management solutions address this limitation by incorporating real-time risk monitoring, predictive analytics, and automated hedging strategies.
Through advanced ML algorithms and dynamic stress testing, these solutions enable firms to anticipate emerging risks, strengthen portfolio resilience, and implement pre-emptive mitigation strategies with greater precision.
Personalised client experiences
Modern investors increasingly seek tailored solutions and proactive communication from financial institutions. AI wealth management platforms empower firms to deliver personalised investment strategies, customised reporting, and proactive advisory services. By leveraging advanced data analytics, ML algorithms and client behaviour modelling, these platforms enhance client engagement, foster stronger relationships, and drive higher retention rates through targeted, data-informed decision-making.
The future of AI in asset management
The future of AI in asset management is promising as technologies continue to evolve. Several trends are poised to shape the industry:
Blockchain integration
Blockchain technology will enhance security and transparency in financial transactions through its decentralised and immutable nature. By employing decentralised networks and cryptographic principles, blockchain ensures secure and verifiable transactions, mitigating the risk of fraud and enhancing trust in financial ecosystems.
ESG investing
AI integrates diverse data sources to conduct holistic Environmental, Social, and Governance (ESG) performance analyses. Predictive analytics aids in forecasting sustainability trends, helping investors identify high-potential ESG investments. Additionally, AI-driven risk assessment models simulate potential impacts on portfolios and adapt monitoring solutions to evolving ESG landscapes.
Hyper-personalisation
AI leverages behavioural analytics and ML to assess each investor’s risk profile and financial objectives. By analysing transaction patterns and investment preferences, AI provides personalised financial guidance and identifies gaps that may impact financial health. Furthermore, AI delivers proactive recommendations and transparent reporting, fostering client trust and enabling data-driven financial strategies.
How can Infosys BPM help?
AI and automation are revolutionising asset management by enhancing efficiency, accuracy, and responsiveness to market dynamics. For organisations seeking to harness these advancements, a strategic partnership is essential for seamless integration and optimised outcomes.
Infosys BPM serves as a trusted partner for asset management companies aiming to leverage AI and automation. With a proven track record in business process management and a deep understanding of AI technologies, Infosys BPM delivers comprehensive solutions that drive operational excellence and accelerate digital transformation.
By integrating AI-powered capabilities into asset management processes, Infosys BPM empowers firms to unlock new opportunities, enhance AI risk management strategies, and deliver superior client experiences in an increasingly complex financial landscape.
