Wealth Management: Enhancing the Investment Advisor toolbox to better meet Investor needs

Wealth Management firms are facing challenges in providing the right set of information about their clients and about product & market details to their Relationship Managers which is impacting the efficiency and meaningfulness of client meetings. 

This is reflected in the major trends observed in the area of Wealth Management: 

• Improved client experience and advisor productivity:
  • A tier 1 bank is focusing on transforming salespersons to play an advisory role.
  • A tier 2  wealth management firm is aiming to improve advisor productivity by providing contextual information. 
• Boutique firms are looking to give clients much greater control of their investment decisions. 
• All firms are focusing on compliance and the suitability of products for clients. 

Developing a relationship with investors 

Exploring these trends further, we can see that the Wealth Management business is facing a key challenge with the provision of investor advice and engagement: 

• Lack of time for advisors/Customer Service teams to aggregate data from multiple, disparate systems, providing the insights of the data aggregated and helping them to provide contextual advising. 
• Lack of real-time, contextual portfolio and market information. 
• Inability to get customer & portfolio insights to provide personalized advisory to customers. 
• Addressing the requirements of a new set of clients who are tech savvy, use digital channels, and are reluctant to face-to-face meetings.  

This has resulted in a disjointed investor experience resulting in customer dissatisfaction and advisor frustration. 

Meeting the Challenge 

To address the above challenges a solution needs to be identified which enables: 

• A single pane view of all the customer information. 
• Automation of transaction execution. 
• Access to all of the product and portfolio information on mobile devices. 
• Customer trade recommendations leveraging the framework to provide different perspectives and alternative recommendations. 
• Tailored information and customer behavioural patterns to contextually map the next best action. 

This framework aims to: 

1. Create a unified advisor front-end to efficiently manage daily tasks and gather real-time advisory that:
   • Enables investment advisors to map customer behaviour and provide contextual advising. 
   • Provides timely tailored information to increase touch point with customers. 
   • Automates daily activities to free up time to manage more customers & portfolios. 
2. Provide actionable intelligence on products & offerings that:
   • Leverages AI & ML powered data analytics to provide timely information on products, markets and customer portfolios. 
   • Exploits Machine Learning & Natural Language Processing to make intelligent inferences about customers’ emerging needs by incorporating demographic, transaction & interaction data. 
3. The key activities involved in building the solution framework are:
   • How to leverage the stored data
     • Efficiency in terms of aggregating diverse data sets/sources. 
     • Aggregates various types of data within the enterprise data sources 
     • Leverages the capabilities of cognitive analytics, and machine learning to create contextual insights for enhancing advisor efficiency. 
   • How to exploit Machine Learning & Natural Language Processing
     • To make intelligent inferences about customer’s emerging needs even with some ambiguities in data  
     • To create more intuitive ways for businesses to seek information. 
4. Combining and understanding the data is the key.
   • We combine 3 sets of data – demographic, transaction, and interaction data – to create a wide-angle view of the client and their needs. 

The above diagram gives a high-level view of the various sets of data available in the firms eco system. 

• The key idea is to aggregate these sets to provide meaningful insights to various stakeholders. 
• A holistic approach to get insights from the data to address the firms and advisors challenges leveraging RPA, AI & ML  

The above diagram depicts an indicative target front office application accessed by Investor advisors or any customer-facing stakeholders.  This application enables access through various user interfaces and provides holistic information at various stages of the client journey. 

Benefits realised

The business benefits delivered through this framework are: 

• Improved understanding of customer investment drivers. 
• Informed discussions about customer portfolio performance & market impact. 
• Understanding the impact of new and prospective transactions on the overall portfolio and financial objectives. 
• Identify & leverage cross sell opportunities. 
• Tailor products more closely for clients sharing the same profile. 
• Enhanced Advisor productivity by an estimated 20-30%.  Advisors will be able to have more informative discussions in a higher number of customer meetings. 
• Potential improved business by an estimated 20-25%.  More productive customer meetings and contextual recommendations enable trust to be built and give access to an increased share of the customer portfolio.  

 The end-stage application will enable firms to provide more informative & interactive channels to connect with the customers.

With the above framework and benefits, as Brickendon we can bring in our expertise of our business process understanding and technology expertise  to: 

• Update CRM and Sales dashboards with the real-time status of the sales pipeline, including continuous traceability. 
• Efficient workflow management for consistent follow-ups, and better visibility of the workflows created. 
• Enable usage of multi-modal channels for advisors and customers.  
• Faster onboarding through various digital channels and technologies. 

Brickendon can work with our clients to enable: 

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