The future of asset management is rapidly shifting, with many conventional tools, products, and approaches less effective than they were once conceived to be. The good news is that asset managers today have technologies such as automation, analytics, and AI at their disposal, which can help them leapfrog into a future where they have more control over costs and access to newer ways of delivering a differentiated customer experience.

Going Beyond the Hype: Cashing in on the ‘Digital’ possibilities

Over the past few years, a lot has been talked about the potential of analytics and AI in asset management. However, studies reveal that the most significant gap between vision and reality lies in how asset managers leverage advanced technology in their day-to-day operations. In a recent survey, almost all respondents (95%) highlighted that an asset manager’s prowess in building data and digital capabilities will be a key differentiator in 2025. Yet the same survey revealed that as much as 72% of asset managers do not consider themselves as mature when assessed on the grounds of digital prowess.

A large cohort of asset managers are still in the nascent stages of exploration and prototyping around emerging technologies like AI. And in the analytics space, the challenge is still around the volume, velocity, and complexity of handling massive data sets and ensuring that data flows seamlessly through the back, middle, and front office.[i] While the pressure to innovate in terms of technology is intense, the potential benefits of leveraging technology for innovation, especially when building loyal customers, are immense.

Besides driving profitability and focusing on process innovation, successful asset managers must personalize services and products at scale while delivering customized outcomes, communications, values, and product preferences. Analytics can help asset managers achieve just that. The following are the top five analytics strategies that asset managers should employ to develop long-term customer loyalty:

• Create a compelling brand strategy backed by data: The need of the hour for asset managers is to create a compelling brand strategy that can help attract new prospects and reinforce the value of the brand to existing customers. This is one area where the most prominent players in the market are contending for a piece of the pie. Asset managers must revisit their analytics strategy and see how they can best harness data to understand customer sentiments and cater to their digital content consumption patterns. A solid brand strategy needs to also consider elements of trust, from how confidential data is stored, managed, and leveraged to how ethical standards are chalked out and implemented in the first place.
• Optimize portfolio through hyper personalization: Conventionally, customer data used to be collated and stored across disconnected systems often functioning in silos. However, the advent of advanced data platforms today is helping asset managers harness proprietary and third-party data to create detailed profiles of customers, their preferences, and behaviors. By bringing AI into the mix, asset managers can drive better portfolio optimization by recommending adjustments in line with a customer’s financial goals. Machine learning algorithms can also help asset managers assess risk and identify assets that are likely to deliver the best returns.
• Customize investment strategies to deliver value: Customized value delivery is key to building customer loyalty in every sector, and asset management is no different. Analytics can help asset managers create personalized investment strategies based on individual client risk tolerance, long-term and short-term financial goals, and preferences. Tailored recommendations become easier with analytics, and the investment process becomes more client-centric.
• Lower the risk profile for customers: Asset management is an inherently risky space, and there are several macroeconomic factors, such as market volatility and geopolitics, that often influence investment outcomes for clients. With data-driven decision making, asset managers will have the upper hand to proactively identify historical data and patterns through predictive analytics and identify potential factors that may impact outcomes. Correlation, liquidity risk, and volatility are key risk assessment metrics against which analytical models can yield near-accurate results, helping asset managers maintain a balance in portfolios, ultimately resulting in client delight.
• Infuse transparency and compliance into the process: Analytics-driven decision-making promotes transparency by allowing asset managers to track, analyze, and report investment activities with increased accuracy. With data and analytics, asset managers can also comply with stringent regulatory requirements, simplify compliance reporting, and minimize the risk of errors. Enhanced transparency in compliance can be a great way to build credibility with clients and earn their loyalty because it can clearly explain performance metrics and investment choices.

Emerging technology has allowed the asset management industry to transform how customer value is delivered, and loyalty is achieved. By embracing the right tools and platforms, asset managers can reduce risks, make smarter decisions, and stay ahead of the curve. The time to act is now.