Situation and challenge
Making first meetings effective with prospects and customers is the aim of every Relationship Manager (RM) in Wealth Management. Effective meetings require good preparation and RMs to create a 360-degree view of customers regarding their source of wealth and interests. For this purpose, RMs traditionally inform themselves by reading news from different data sources (Internet, Dow Jones, Lexis Nexis, World-Check) and extract relevant insights for meetings. This process may be incomplete depending on which data sources the RM reads, is time-intensive, and limits the number of meetings an RM can have. Manually unifying disparate data sources and keeping data always up to date is neither feasible nor scalable, and requires automation.
Approach and solution
On top of the user's application landscape build a tool with AWS services by augmenting the manual/semi-manual process to automatically generate relevant insights from large amounts of structured and unstructured (webpages, PDFs, social media, etc.) internal and external data, giving the RM the ability to search with natural language queries (full sentences going beyond keyword search), and always have an up-to-date visualized view of the customer and their relationships. The following AWS services have been used in this solution.
Data Exchange is a data marketplace with more than 3,500 pre-approved data providers that users can easily subscribe to from a single place. Instead of negotiating with each data provider in Data Exchange, users can easily select and test providers to determine if they match their use case, and either continue or discard them and select new ones.
Amazon Athena is a serverless query engine that provides processing and analytics capabilities without requiring infrastructure management.
OpenSearch gives users the ability to run and search through vast amounts of data (individuals, events, company news).
Amazon Neptune is a fully managed graph database designed to store and query highly connected data with complex relationships. This is important as networking and relationships are key components of 360-degree customer value.
Amazon SageMaker allows secure hosting of different Generative AI models. All data remains private and within customer boundaries. This enables the integration of generative AI functionalities in the application, like natural language search for prospects, simplifying the identification of key individuals for RMs.
Amazon Comprehend enables automated insights. Comprehend's event detection functionality can detect up to 11 business events, including corporate acquisitions, general investments, stock splits, and IPOs. It is used to detect relevant news for individuals. It also provides sentiment analysis, offering more insights about prospects and customers.
Explanation of how it works
All data names have been processed through anonymization and randomization for demonstration purposes. In a real-world scenario, there are thousands of individuals (prospects) with hundreds of attributes, news, and other data. The demo shows prospects with attributes such as company name, sector, and other columns representing third-party data providers' data integrated into the solution, with indicators showing whether individuals/prospects match with specific third-party data providers.
Generative AI enables natural language search. For example, if an RM knows about an upcoming golf event and wants to find prospects interested in golf, they can input the sentence "show me prospects who like golf." This is sent to the LLM hosted in the SageMaker endpoint. The LLM translates the natural language sentence into a query that OpenSearch can understand, finds relevant individuals with that interest, and returns the response. The same question can be phrased differently, such as "Show me people interested in golf," and yield identical results, as the LLM understands the intention and transforms it into the same query for OpenSearch. RMs can additionally filter for specific age ranges of prospects. For example, "Show me prospects who were born after 1953" will display all customers interested in golf who were born after 1953. If the event is happening in NY, the RM might want to see only customers who, besides being interested in golf and born after 1953, live in NY. Similarly, users can expand queries to include any attributes in the database (e.g. questions about company, interests, or networks).
Once users find prospects matching their criteria, they can dive deeper into individual profiles. The system can display all data about individuals, including their networks and relationships. If the RM is interested in another individual from the network (e.g. a family member of the prospect), they can view all data about this person (their network, companies, financials, shareholders). In this example users can also see related stories, Twitter tweets, metadata, and sentiment analysis (ranging from -100 for very negative sentiment to +100 for very positive sentiment) extracted by the Comprehend service. Processing news and tweets provides significant value to prospecting, offering real-time sentiment analysis and all events related to individuals. These insights can be used to find potential new prospects who are related to recent corporate acquisitions or investments.
Summary
In summary, there are several benefits of this built solution:
1. Time to value in getting a 360-degree view of customers with rich insights (strategy, business events, news, social media, sentiment analysis). Ability to visualize and traverse connections of prospects/customers. Any data format, including emails and audio (from calls), can be added and analyzed.
2. Significant increase in RM productivity, freeing them from manual tasks and allowing focus on higher revenue-generating activities.
3. Powerful natural language search capabilities powered by Generative AI.
4. Business agility enabling organizations to add new data feeds faster when implementing the solution across geographies.
5. Ability to provide proactive service to prospects/customers, enhancing customer experience and leading to higher conversion rates.
Interested in reading the European WealthTech Landscape Report 2025? You can read the report online here.
About The European Wealth Landscape Report 2025
The European WealthTech Landscape Report 2025 is a new WealthTech Landscape Report from The Wealth Mosaic, focused on the wealth management sector in Europe.
With the rapid pace of change in financial services, understanding technology's impact on this sector is more crucial than ever. This Europe-focused Landscape Report features a series of insightful articles that explore the trends, challenges, and innovations surrounding technology adoption in wealth management. Contributions come from a range of organisations, including AWS, Croesus, Deloitte, ERI, EY, Fincite, Finfox, First Rate, Infront, Intellect Design Arena, Moneyfarm, Raise Partner and WealthOS.
The articles you will find within the report provide valuable perspectives on how technology is transforming the wealth management industry. They discuss various aspects of technology adoption, from the latest innovations to how firms can leverage technology to enhance client engagement, streamline operations, and comply with regulatory demands.
We trust you find this report invaluable to your business needs and supportive of your understanding of the fast-moving technology marketplace surrounding the European wealth management market.
Click here for more information.
About The WealthTech Landscape Report Series
Our goal with our WealthTech Landscape Reports (WTLRs) is to collate relevant, insightful content and comments from both wealth managers and vendors operating in a specific region. Each WTLR is founded on a curated directory of hundreds of relevant technology and related solution providers to the business needs of the wealth management community in focus. The directory is supported by a rich variety of thought leadership articles and interviews with industry participants from both buy and sell side, plus a section of Solution Showcases. We also look at country, regional, and sectoral trends.
If you are interested in contributing to our editorial projects, don't hesitate to get in touch.
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