Bassam Chaptini is a co-founder at Avantos [1], a company operating in the financial services technology sector in New York. Avantos focuses on client onboarding processes through an operating system platform designed for the financial services industry [1].
Founded
Insights & ideas
Chaptini argues that client management in wealth management has long been a neglected "white space," with most platforms focused only on the easy sales pipeline stage while the real complexity begins once a client signs up, since a client is never just an individual but a household, family, or set of entities spanning multiple products and custodians [1]. He calls onboarding "the hornets nest," describing an exponential data problem driven by differing custodian requirements, firm-specific forms, and advisor team structures, which has historically pushed firms toward manual, PDF-based workarounds rather than scalable systems [1].
His core idea for solving this is representational, not just technological: because complexity stems from relationships between entities, the problem should be modeled with a knowledge graph rather than traditional linear tables [1]. He insists firms should never have to migrate their source data; instead AI should map existing systems into the knowledge graph with bidirectional updates, letting advisors work from a unified, AI-native view while onboarding clients once across multiple custodians and product types, including offerings like life and annuity products [1].
Education
Massachusetts Institute of Technology · Ph.D., Artificial Intelligence
American University of Beirut · Bachelor of Engineering
Media & appearances
- Videos
Bassam Chaptini, co-founder of Avantos, discusses how the company built an AI-native operating system for client management in wealth management, addressing the complexity of onboarding and servicing clients across multiple households, entities, and custodians. He explains that Avantos uses a knowledge graph to represent relationships between different entities, an agentic orchestration layer, and AI-native experiences for advisors, while keeping clients' source data in their original systems rather than requiring migration.
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