Asset and wealth management client teams have been stuck using CRM the same way for a decade, creating significant hurdles to unlocking its full potential. Tedious data entry, inefficient workflows, and the struggle to extract actionable insights hinder productivity and the client experience. These challenges lead to missed opportunities and avoidable redemptions.
Embedding an AI assistant into CRM delivers a step change in the user experience by effortlessly connecting users to information available within CRM and other datasets in the distribution ecosystem, while automating monotonous data entry tasks.
Benefiting from the advances in AI technology doesn’t have to take months, with firms across the industry now incorporating AI into their CRMs to achieve rapid business value in a matter of weeks.
Boosting Productivity
Accessing reliable data in a CRM can be a time-consuming challenge for users, whether starting their day, preparing for a meeting, or responding to an ad-hoc call. Even well-configured CRMs are often challenging to navigate quickly, and repetitive tasks like drafting outreach emails or completing RFPs drain valuable time. An AI assistant revolutionizes this process by streamlining data access and automating routine tasks. It enables users to locate information with ease, saving time and reducing frustration. With an AI assistant’s intuitive capabilities, distribution teams can focus on their strategic priorities, driving better client outcomes.
Interrogating client engagement data and drafting an outreach email
Boost workflow efficiency:
- Draft outreach emails automatically based on digital engagement
- Create a snapshot summarizing the key information about a client before a meeting
- Automate drafting of replies to common client servicing requests
Laying the Foundations for Insights
CRM systems are indispensable in modern asset and wealth management, yet their potential is often undermined by incomplete or poor-quality data – largely a result of manual and time-consuming data entry processes. High-quality, comprehensive data is essential for robust reporting, advanced analytics, and the success of machine learning models. By streamlining data capture through intuitive interfaces, image recognition, and voice input, an AI assistant addresses this challenge head-on. This forms the cornerstone of a broader strategy to harness AI and machine learning, unlocking smarter insights and superior outcomes.
Creating meeting notes from a photo – linking attendees and generating follow-up tasks automatically
Preparing for insights:
- Capture meeting details from hand-written notes to enable churn prediction models
- Update opportunities efficiently to improve management reporting accuracy
- Create contacts effortlessly from business card photos to enable marketing outreach
Unifying Information in One Interface
The number of apps and systems which sales, service and marketing teams rely on is ever increasing. Navigating between multiple apps requires extensive training and causes user fatigue. In addition, key data sets often reside off-platform in distribution systems such as Snowflake, limiting users’ ability to self-serve. An AI assistant addresses these challenges by unifying external data into a single, seamless interface.
Visualizing product performance data stored in a data warehouse and analyzing it against a 3rd party benchmark
Streamlining information access:
- Visualize product performance against a benchmark
- Understand client hierarchies and uncover relationships
- Explore warehouse data to see AUM history by client
Technical Information
The demo showcases a version of Alpha’s proprietary industry-specific AI assistant. Alpha is vendor agnostic and has experience working with all the major CRM systems and cloud providers to support clients in rapidly delivering AI assistants for CRM, leveraging existing infrastructure. This version was developed using prompt flows in Microsoft Azure AI Studio which has access to a Snowflake environment, powering a custom user interface developed in Salesforce.
How can Alpha help?
We work with clients across all stages of the AI transformation journey from internal readiness assessments and business case definition, through to deployment of our pre-built capabilities and partnering to develop new solutions using our accelerators. If you are interested in hearing more about how Alpha can help, please get in touch with us here
About the Authors
Divakar Padmanathan
Senior Partner
Divakar is a Senior Partner with responsibility for leading Alpha's UK Client & Digital practice. Over the past 10 years he has supported a number of asset and wealth managers seeking to apply technology to improve efficiency, effectiveness and client experience.
Greg Beazley
Enterprise Architect
Greg is an Enterprise Architect in the Client & Digital technology team. He has been the technical lead on several advanced analytics projects for asset managers, from creating an Agentic-AI investment research tool through to the deployment of data science models to assess client risk and optimize client prospecting. Greg specializes in identifying and understanding business challenges and applying innovative technology to solve them.
Lena Jannibelli
Solution Architect
Lena is a Solution Architect within the Client & Digital technology team. She specializes in delivering global CRM implementations for asset and wealth managers, including cutting-edge AI-powered solutions. With a strong background in data engineering and advanced analytics, Lena has also supported the design and development of an enterprise distribution data platform for a leading asset manager.