Top Technology Trends Disrupting the Wealth Management Industry

The emerging FinTech trends are shaping the wealth management landscape, enhancing efficiency, accessibility, and client experience while ushering in a new era of innovation in the financial services industry. With the new generation of investors joining the wealth management space, demand for automation, highly data-driven integrated advice, and digitized experiences has increased. 

With the changing client relationship dynamics, the digital makeover is the need of the hour for wealth management companies to offer holistic digital experiences to customers. 86% of wealth management companies believe digital is the future and are focused on investing in digital infrastructure

Let us explore the top emerging technology trends realigning the FinTech wealth management business:

Artificial Intelligence (AI) and Machine Learning (ML)

The Artificial intelligence and machine learning are hot topics in the financial services industry today. Artificial intelligence is used in almost every area of wealth management right, from consumer-facing solutions to risk management, product, reporting, middle, and back-end operations. 

Artificial intelligence and machine learning technologies offer endless possibilities to scale the wealth management business. Here are the main benefits of using artificial intelligence and machine learning in wealth management.

Benefits of AI and ML in The WealthTech space

  1. Streamlined lead generation

AI helps find new clients and collects information from various channels to guide them and streamline the process. For example, generative AI-based chatbots in wealth management interact with new leads, give answers, provide recommendations based on their preferences, and guide prospects. 

  1. Hyper-personalization

Customer Relationship Management (CRM) systems powered by machine learning are helping wealth managers and financial advisors to offer hyper-personalization to their clients. Data accumulation power helps analyze clients’ preferences and needs like never before and make highly personalized recommendations.

For example, Morgan Stanley has a machine Learning-powered engine, Next Best Action, which delivers customized messages to clients and helps financial advisors increase client engagement. Morgan Stanley has also recently announced its strategic initiative with OpenAI to leverage the technology to provide hyper-personalized services to clients.

  1. Next-level automation and cost reduction

The introduction of AI-powered stock market analysis tools and robo-advisory platforms has taken automation to the next level in wealth management. Automation has made wealth management solutions highly accessible and cost-effective.

  1. Compliance and risk management

AI and ML-based compliance and risk management tools are enhancing the wealth management FinTech companies’ efficiency. It can detect suspicious activities, anomalies, and potential regulatory breaches by analyzing large volumes of data and can reduce compliance risk. 

WealthTech companies can use these tools to manage risk effectively with better analysis. For example, BlackRock uses AI-powered risk management software called Aladdin Risk, which helps manage risk with highly sophisticated risk analytics.

  1. Product/service innovation

Integration of technologies like artificial intelligence into the wealth management system enables the emergence of new, innovative, and more sophisticated wealth management products and services. 

  1. Informed decision-making and real-time monitoring

AI and ML-powered systems and tools provide deeper insights into market and customer data and enable wealth managers and customers to make effective and informed decisions. 

Unlike monthly portfolio updates used in traditional wealth management, AI gives WealthTech companies the power to offer real-time portfolio monitoring features to their clients.

  1. Fraud detection

WealthTech companies can easily detect fraud in any financial activity, real-time money transactions, application usage, etc., using AI.

Robotic Process Automation (RPA)

WealthTech companies are leveraging robotic process automation (RPA) to automate mundane tasks, operations, and processes. Automating repetitive tasks with the help of digital employees/bots can help them redeploy valuable human capital for more productive and meaningful activities.  

As per KPMG Report – Rise of the Robots, integrating robotic process automation can reduce costs by up to 70% for financial services firms. Also, the ESI Thoughtlab: Wealth and Asset Management 4.0 study, supported by Deloitte, HCL, and other sponsors, sees a steady boost in key performance indicators of the industry such as productivity, revenue, assets under management (AUM), market share, and shareholder value. 

RPA is mainly used in wealth management for swift client onboarding, reporting, compliance, back-end processes, data management, and more. Here are some essential benefits of robotic process automation in wealth management.

Explainable Artificial Intelligence (XAI)

Output from AI models can be complex, and then XAI can play a crucial role in mitigating this problem. Explainable artificial intelligence provides explanations and helps to interpret the AI output for easy understanding. 

For example, machine learning algorithms and artificial intelligence tools can analyze large volumes of data, identify market trends & patterns and make future predictions. This can help wealth managers to identify the best investment combinations to optimize the investment portfolio. However, concerns about interpreting the inner workings of these AI models can become an obstacle to their practical deployment. This is when explainable artificial intelligence (XAI) can complement AI models. XAI can provide explicable insights and make investment recommendations with explanations. 

In the wealth management industry, XAI is used in areas like fraud detection, data analysis and digital client onboarding for identity verification. 

Cloud-native Computing

The cloud-native applications market is continuously growing as more industries leverage technology to optimize their scalability. As per the industry report by GlobeNewswire, the market size of global cloud-native applications is expected to at a compound annual growth rate of 22.9% to reach $16.2 billion by 2028

Many WealthTech companies are already leveraging cloud-native computing technology to reduce costs. Wealth managers can avail of the SaaS (Software-as-a-service) subscriptions suitable for their specific needs. Cloud applications also offer wealth management providers flexibility, scalability, and increased security. 

For example, Wealth OS, a UK-based WealthTech startup listed in the Forbes WealthTech 100 list, provides a cloud-native wealth management SaaS platform. 

Predictive Analytics

Predictive analytic tools analyze historical data and make future predictions. This enables wealth managers to forecast market trends in the future, identify investment opportunities, and manage risk effectively. These algorithm-based tools can generate deep insights by analyzing large datasets. 

The adoption of this technology in the WealthTech space is rising to gain a competitive edge with the increasing market size of the global predictive analytics market. As per the industry report by Markets and Markets, the global predictive analytics market is projected to grow at a compound annual growth rate of 21.7% to reach a market size of $28.1 billion by 2026.

ESG (Environmental, Social, and Governance) Analytics

The ESG (Environmental, Social, and Governance) intelligence/analytics is a rapidly growing technology trend in wealth management. ESG (Environmental, Social, and Governance) is a sustainability concept in the investing landscape that many investors are embracing across the globe. As per the PwC’s Asset and Wealth Management Revolution 2022 report, asset managers worldwide are expected to increase ESG-related AUM (asset under management) to $33.9 trillion by 2026 at a CAGR of 12.9%. 

ESG intelligence/analytic tools enable wealth managers to incorporate ESG data into the wealth management process, access plenty of investment opportunities and enhance customer satisfaction. 

For example, Refinitiv, a WealthTech company in the Forbes WealthTech 100 list, offers ESG analytics-based wealth management solutions. 

Decentralized Identity Solutions

A decentralized identity solution uses blockchain technology and decentralized identifiers (DIDs) to provide access to financial and personal data to clients in the WealthTech space. The technology can enhance transparency, privacy, and security in the wealth management industry. 

Conclusion

Advanced technologies strengthen customer trust, improve efficiency, and reshape the industry with innovative wealth management products and services. As technological innovations and customers’ digital expectations grow, WealthTech companies and the wealth management industry will evolve rapidly to address clients’ ever-changing needs. 

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