Aspire Systems Case Studies Overcoming Data Challenges in the FinTech Industry

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	Overcoming Data Challenges in the FinTech Industry Aspire Systems

Overcoming Data Challenges in the FinTech Industry

Aspire Systems

Technology Category	Analytics & Modeling - Machine Learning Infrastructure as a Service (IaaS) - Hybrid Cloud
Applicable Industries	Education Retail
Use Cases	Facial Recognition Leasing Finance Automation
Services	Data Science Services Training
Challenge	Data remains a key challenge for FinTechs and their partnering traditional financial institutions. Among FinTechs globally, 81 percent have reported data to be their biggest technical challenge. These data issues include leveraging data for AI-ML, connecting to customer applications and data systems, security, and deployment in multiple clouds. Read More
About Customer	FinTechs are businesses that use technology to enhance and automate financial processes, services, and products. Examples of FinTechs include organizations and enterprises such as Venmo, Stripe, PayPal, and Challenger banks. They rely on data to drive innovation, improve user experience, and secure partnerships with incumbent banks. Read More
Customer Name	FinTech Read More
Solution	The solutions to overcome the data challenges faced by FinTechs include implementing smart data fabrics to bridge data silos and leverage data for AI, investing in cloud deployment solutions, and using one-shot learning models for AI. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Machine Learning

Infrastructure as a Service (IaaS) - Hybrid Cloud

Applicable Industries

Education

Retail

Use Cases

Facial Recognition

Leasing Finance Automation

Services

Data Science Services

Training

Challenge

Data remains a key challenge for FinTechs and their partnering traditional financial institutions. Among FinTechs globally, 81 percent have reported data to be their biggest technical challenge. These data issues include leveraging data for AI-ML, connecting to customer applications and data systems, security, and deployment in multiple clouds.

About Customer

FinTechs are businesses that use technology to enhance and automate financial processes, services, and products. Examples of FinTechs include organizations and enterprises such as Venmo, Stripe, PayPal, and Challenger banks. They rely on data to drive innovation, improve user experience, and secure partnerships with incumbent banks.

Customer Name

FinTech

Solution

The solutions to overcome the data challenges faced by FinTechs include implementing smart data fabrics to bridge data silos and leverage data for AI, investing in cloud deployment solutions, and using one-shot learning models for AI.

Impact #1	[Data Management ⦁ smart data fabrics there is a need for fintechs to take a look at their current data management strategy to bridge the data silos and integrate them with the help of a new architectural approach called data fabric.

Impact #1

[Data Management
⦁ smart data fabrics

there is a need for fintechs to take a look at their current data management strategy to bridge the data silos and integrate them with the help of a new architectural approach called data fabric.

Benefit #1	44 percent of FinTechs are considering implementing smart data fabrics, 54 percent are planning to invest in cloud deployment solutions, and 51 percent are considering using one-shot learning models for AI. These solutions will enable FinTechs to bridge data silos, leverage data for AI, overcome deployment challenges, and learn from smaller datasets.

Benefit #1

44 percent of FinTechs are considering implementing smart data fabrics, 54 percent are planning to invest in cloud deployment solutions, and 51 percent are considering using one-shot learning models for AI. These solutions will enable FinTechs to bridge data silos, leverage data for AI, overcome deployment challenges, and learn from smaller datasets.

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Overview

Overcoming Data Challenges in the FinTech Industry

Operational Impact

Quantitative Benefit