AI is currently being actively integrated into the fintech industry, which helps to optimize and develop new strategies and solutions for increasing productivity, reducing errors, and making optimal decisions. Let’s dive into the concrete use cases of AI in Fintech and see the practical examples.
Complex AI Tools
To realize such strategic goals like expansion or disruption, organizations have to use a higher level of technologies like Machine Learning or AI that provide better decision solutions as well as identify better market opportunities.
AI improves credit scoring and portfolio management by providing lenders and investors with deeper insights into risk based on bigger and more complex datasets. McKinsey estimates that AI can automate as much as 70% of business tasks, augmenting risk assessment and contributing trillions of dollars in value to the global economy.
AI-Powered Fraud Detection
Today, it has become standard for financial institutions to utilize someone like an AI to help prevent money laundering and other criminal activities. These institutions minimize risks by using analytics and machine learning algorithms as part of their operations.
RPA, Data Visualization, and NLP for automation
Within the large-scale business transformation efforts, businesses are arming their finance workforce with digital toolboxes containing elements of RPA, data visualization, and the NLP. This enables employees to automate basic level tasks such as reporting of finance to more complicated ones such as analyzing financial outcomes.
Real-Time AI-Powered Insights
Using AI, business owners get real-time data that means the information that they use is always delivered at the right time. It involves formulating and implementing decisions more rapidly and effectively to the dynamic business environment.
Accounts Payable and Receivable
In the area of accounts receivable, AI can predict when a customer is likely to pay his invoices thereby allowing organizations to direct its collection efforts to accounts that are likely to turn bad. This proactive approach favorably impacts cash flow and requires less time for collection compared to chasing after clients and customers.
By using AI, customers can get a tailored financial recommendation considering their spending habits. Drawing on the analysis of behavioral patterns, AI contributes to improving the financial decision-making of clients.
AI-Powered Chatbots & Customer Support
The use of AI-driven chat and customer service assists in the handling of basic questions, and channeling the qualified cases to human operators. These chatbots can handle up to 70% of such inquiries to solve them and equally reduce the amount of work and increase customer satisfaction.
Automated Trading Systems
It is evident that algorithmic trading is set to benefit from the advances of AI. Trading by algorithms has the ability to analyze millions of data inputs within seconds, which results in improved results in financial markets.
These AI features benefit CFOs and financial institutions while furthering organizations’ strategic initiatives. Have burning questions regarding AI in FinTech? Reach out to S-PRO for the answers you need.
