Fueling the Future of Fintech With Data Science and AI

Data is much vaunted as the new oil. However, every profit-driven enterprise out there sits on copious of big data as they clock years through the two primary enterprise processes - Core & Support processes. And most of these fintech companies have these processes running daily.

Since there is a lot of novelty involved, and some of the processes are bleeding edge in relation to agile business operations, it goes without saying that AI is part of this agility.

Here we discuss how data science and machine learning would strongly boost sales and all allied processes for a fintech organisation.

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Table of Contents:
- Analysis of Customer Payment and Transactions
- Credit Risk Evaluation
- Revenue and Debt Collection
- Customer Journey Attribution
- Fraud Detection and Prevention
- Portfolio Optimization and Asset Management
- Corporate Compliance & Service Quality
- AI in Fintech: Possible Applications
Summary:

For financial companies across the globe enhancing efficiency and productivity while improving customer experience has become a top priority. As data becomes the new fuel, AI allows financial organizations to improve business decision-making by crunching huge, varied, and complex data sets. In this ebook, we will have a look at how data science and AI is helping FinTechs enhance efficiency and productivity with possible applications of AI.
Key Highlights:
- 15000 data points per user (from different sources) are being captured, allowing organisations access data in scale.
- 98% accuracy in some of the ML algorithms are allowing AI tools to prevent suspect transactions, loan application fraud, money laundering attempts, account thefts and more.
- AI heps fintechs deploy personalized experiences that are tailored to their user's unique demographics, geography, needs, and wants
- 75-90% of healthcare & banking queries are projected to be handle by Chatbots by 2022