Latin America Robo-advisor Market Size and Forecast by Service Model, End Users, Industry, Transaction Types, Investor Type, Asset Class, Platform Type, and Country: Statistics | 2019-2032

  Oct 2024   | Format: PDF DataSheet |   Pages: 160+ | Type: Sub-Industry Report |   

 

Latin America Fintech Robo-advisor Market Growth and Performance


  • The fintech robo-advisor market in Latin America witnessed YoY growth of 34.6% and reached US$ 27.27 Billion in 2023.
  • The Latin America fintech robo-advisor industry is poised to experience a CAGR of 37.4% throughout the forecast period to amount to US$ 435.03 Billion by 2032.
  • In the region, the healthcare sector is projected to emerge as leading segment in the fintech robo-advisor market, with a healthy CAGR.
  • In comparison to other countries, fintech robo-advisor market in Brazil is expected to generate the highest revenue in 2023.

Latin America Fintech Robo-advisor Market Scope

Analysis Period

2019-2032

Actual Data

2019-2023

Base Year

2024

Estimated Year

2024

CAGR Period

2024-2032

 

Research Scope

Service Model

Pure Robo-advisor

Hybrid Robo-advisor

White-Label Platform

End Users

Individual Consumer

SME

Medium-sized Enterprise

Large Enterprise

Industry

IT and Telecom

Media and Entertainment

Energy and Power

Transportation and Logistics

Healthcare

BFSI

Retail

Manufacturing

Public Sector

Other

Transaction Types

Business-to-Consumer (B2C)

Business-to-Business (B2B)

Consumer-to-Consumer (C2C)

Consumer-to-Business (C2B)

Investor Type

Retail Investor

Institutional Investor

Small and Medium Enterprises (SMEs

Asset Class

Equitie

Fixed Incom

Cryptocurrencie

Real Estat

Platform Type

Web-Based Platform

Mobile Application

API Integration Platform

         

Latin America Fintech Robo-Advisor Industry: Regional Coverage

 

Countries

Latin America

Brazi

Per

Colombi

Chil

Rest of Latin Americ

*Research Methodology: This report is based on DataCube’s proprietary 3-stage forecasting model, combining primary research, secondary data triangulation, and expert validation. [Learn more]

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