Less Art More

AI for Net New Assets. TIFIN AG’s advanced algos help advisors with better client acquisition, retention, and expansion.

Delivering enriched
data for actionable intelligence 

TIFIN AG is powered by a proprietary algo ensemble, unifying wealth data sources, and delivering growth through actionable feedback loops.

Modules for AI-
Powered Growth

Prioritize Prospects

A ranked list of your existing prospects based on their similarity to your top clients and the propensity to engage with your content digitally.

Network Prospects

A list of new leads with direct connections to current clients, ranked by similar characteristics and propensity to engage with your firm digitally.

Asset Consolidator

A ranked list of your existing clients who are most likely to consolidate their held-away assets under your management, prioritizing those who “look and act like” previous consolidators.

Assets At-Risk

A ranked list of your most at-risk clients based upon their historical transaction activity, behavior, and similarity in demographics when compared to previously lost clients.

Workplace Prospects

A list of new leads (employees) within an organization at any specific location, ranked by similarity to your current clients and propensity to engage with your firm digitally.

Adjacent Business Leads

A prioritized list of adjacent business clients who are the best fit for the firm’s advisory services.

Advisor Lead Match

A list of your existing prospects to advisors in your firm based on best-fit similarity to the advisor’s client base.



  • One of the largest financial data lakes
  • First party data on over 3 million individuals across our sister companies.


  • Data cleansing and enrichment at speed
  • Convert minimal data into actionable intelligence within 3 days


  • Transform prospect lists into prioritized target lists who look and act like your best clients.
  • Convert prioritized leads to clients using AI/ML models


  • Nurture leads through marketing campaigns
  • Capture engagement data to enhance ML algos and improve future prioritization accuracy.