FINANCIAL SERVICES The resulting fall in activity has been rapid and
severe. This serious decline means that it’s essential for investors, banks and other players in the NPL market to develop a strategy that allows them to identify and manage vulnerable loans with appropriate risk mitigation. Such a strategy starts with the creation of a proactive, tailored debt management mechanism. A solid strategy for managing and storing data can help optimise data scientists’ skills and time, especially after the impact of the disruption/ acceleration of trends made by the Covid crisis. By simplifying the process of classifying data and controlling access, automated data management can help address data governance challenges. Increasing the simplicity of automatically setting up investments for loan administration and portfolio monitoring will be essential. Customised advisory solutions are key for
ultra-high-net-worth individuals. The digital interface remains an interesting tool for a more agile analysis but it’s not the most important part of the relationship between client and adviser. No matter how capable machines become, human interaction and trusted, personalised relationships will remain key, especially for clients in the upper wealth bands, who tend to have more complex needs. Human judgment, creativity, and empathy are essential to forging meaningful, trust-based relationships; and robots and AI cannot easily replicate these qualities. The head of digital strategy at a global wealth manager said: “Trust will remain essential. Platforms and digital solutions alone will not be sufficient to establish trust.”
A wealth of opportunities Over the next two decades, the most advanced wealth management providers will be able to think five steps ahead and see what types of solutions and support clients may need even before those requirements present themselves. Next-generation ML analytics will help providers to make incisive connections that reveal potential client opportunities. Visualisation tools built into the models will enable advisers to walk their clients through different financial and investment choices, giving them a more visceral feel for how different scenarios might play out. Personalisation will be key to success. Winners will be able to reach each client at the
right time with the right offer or advice. They will know how frequently a client wishes to be informed, what length and format to use for specific interactions, and what emotional tone or style is most suitable. Using them, they can deliver curated investment themes, peer-to-peer networks, interactive simulations, and exclusive offerings that foster fun and engagement.
ESG and impact investing Wealth management providers should not let near-term challenges, such as lack of scoring models or data, prevent them from developing a thoughtful ESG portfolio. They need to offer investments that generate measurable social or environmental benefits alongside strong financial returns, backed by solid compliance measures. Firms should encourage advisers to discuss values and sustainable development goals in detail with their clients, and should give them the right training and incentives to do so. Those conversations should also look outward. Committing to ESG requires an internal reckoning and the ability to excel in ESG standards, and wealth management providers need to reflect those standards in their internal agenda and practise what they preach. Reducing carbon emissions or resource
consumption can help organisations reduce or mitigate costs. Organisations are using these tools to continually identify internal and external strategic forces, inform strategic decisions, and monitor outcomes. Technology can also help leaders gain insight into seemingly unrelated occurrences that can drive smarter strategic choices on a continual basis. As a result, companies are transforming strategy development from an infrequent, time-consuming process to one that’s continuous and dynamic, helping strategists think more expansively and creatively about future possibilities. Strategists should evaluate technologies that help empower their imagination by identifying driving forces, informing strategic decisions, and monitoring outcomes. With ML poised to overhaul enterprise operations and decision-making, a growing number of AI pioneers are realising that legacy data models and infrastructure — all designed to support decision-making by humans, not machines — could be a roadblock to the use of ML for future success in this landscape.
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