The Finance industry is evolving and AI is playing a prominent role in it. In this particular blog, you will get to know the top 8 use cases of how generative AI in Finance can be used to elevate your fintech business.
Let’s dive in and check the content of this post:
What Is Generative AI? What Are The Benefits Of Generative AI In Finance?
Generative AI is a part of Artificial intelligence that creates content such as text, images, videos, and audio based on a command. Unlike traditional AI, generative AI analyzes data and then gives output based on it.
Any leading finance app development company will suggest you integrate generative AI functionalities into your app, and here are 3 major benefits on why you should do that.
- Through generative AI you can provide automated customer support through chat. With the help of a Chatbot, you can easily and quickly provide support to your customers based on previous conversations.
- Generative AI can also be used to suggest customers with personal finances and investment options that will enhance their portfolios.
- Finance apps should be compliance-friendly, and thus with the help of Generative AI, you can carry out document generation or risk modeling assessment.
8 Usescases Of Generative AI In Fintech
Here are the best 8 use cases of using Generative AI in fintech:
- Personalized Financial Services
Generative AI in stock trading can be used to generate tailored investment plans, loan offers, or saving strategies based on the user’s portfolio. This can be done via notifications or through a virtual chatbot.
Generative AI can also understand your user’s spending trends and create a monthly spending budget for them so that they can invest and spend their income accordingly.
- Fraud Detection And Prevention
Through generative AI in fintech, developers can create synthetic fraudulent patterns which helps in improve the training of detection algorithms, making them more robust against new fraud tactics.
It can detect unusual transaction behaviors in milliseconds, sending alerts and blocking suspicious activities which reduces the risk of cybercrime on your platform.
- Streamlined Regulatory Compliances
A Fintech app needs to be compliant and with generative AI it’s much easier for you to create accurate, regulation-compliant reports for audits or filings reducing human errors. Moreover, AI helps generate and update complex legal documents like KYC/AML (Know Your Customer/Anti-Money Laundering) policies.
- Enhanced Risk Assessments
Generative AI can track the creditworthiness of users by analyzing their social data, credit scores, and behavioral patterns before they make a loan-related transaction on your platform. Furthermore, it can be used to forecast financial risks with high accuracy, enabling better decision-making for loans, investments, and insurance.
- Scale Up Customer Engagement
You can use generative AI to create educational content for your knowledge base. The content can be of any type, that is video, text, and even audio format content. Also, AI-driven systems allow customers to engage naturally through text or voice, improving satisfaction and retention rates.
- Account Automation
With the help of automation and data insertion through generative AI you get accurate accounting reports such as the collection of data, overviewing and correcting data, and more. This reduces the risk of wrong data entry or any other human error and also reduces manual efforts.
- Analyzing Customer Satisfaction
Generative AI in financing has better capabilities sending customers automated emails, sms, and WhatsApp messages to get more reviews on your platform. To get good trustworthiness on your platform it’s necessary to have more reviews and thus using Generative AI to gather those reviews is important too.
- Prediction In The Stock Market
Robo-advisory platforms use Generative AI to predict out-of-stock based on market trends and future predictions. This helps traders predict which stock to buy and which to sell in the future, which helps in profit maximization and gives them complete satisfaction.
Top 3 Fintech Companies Using Generative AI
Streetbeat
From the perspective of a Mobile app development company, this platform uses generative AI to provide users with AI-powered investment insights and market analyses. Users can interact with an AI advisor to customize investment strategies, democratizing access to advanced financial tools
Sardine
Leveraging generative AI for fraud prevention, Sardine excels in transaction monitoring, anti-money laundering (AML) compliance, and identity verification. Its comprehensive approach ensures secure and seamless user onboarding processes
ZestAI
This platform applies generative AI to lending processes, particularly credit underwriting, to improve accuracy and fairness. It helps financial institutions make informed lending decisions.
HighRadius
By integrating generative AI into financial operations, HighRadius automates payment processing and improves cash flow management for businesses, showcasing its capability to enhance operational efficiency.
Cost Of Integrating Generative AI In Fintech
Here is a tabular representation of the cost of integrating generative AI in fintech.
| Cost Component | Description | Estimated Cost Range |
| Initial Development and Setup | Includes acquiring or developing generative AI models, setting up data pipelines, and cloud infrastructure. | $50,000 – $200,000+ |
| AI Model Licensing | Cost of licensing pre-trained models like OpenAI’s GPT or custom models. | $20,000 – $100,000/year |
| Cloud Computing Costs | Cloud services for training, deploying, and maintaining generative AI models (AWS, Azure, etc.). | $10,000 – $50,000/year |
| Integration with Fintech Systems | Customization to integrate AI into core banking, lending, or payment systems. | $30,000 – $150,000+ |
| Regulatory Compliance | Cost for ensuring AI adherence to financial regulations like GDPR, AML, etc. | $10,000 – $30,000 |
| Data Preparation | Cleaning and curating financial datasets for model training and testing. | $10,000 – $50,000 |
| Security and Privacy Measures | Implementing robust security measures to safeguard sensitive financial data. | $20,000 – $100,000 |
| Training and Upskilling | Training staff to operate and maintain AI systems, including prompt engineering. | $5,000 – $20,000 |
| Maintenance and Updates | Ongoing model updates, retraining, and infrastructure scaling. | $15,000 – $50,000/year |
| Total Estimated Cost | Aggregate cost depends on the scale and complexity of the implementation. | $170,000 – $750,000+ |
Conclusion
Now, in the end, we hope that through this post you were able to gain knowledge of how you can use generative AI in fintech. We have mentioned all the important use cases and benefits that will help you determine if your fintech platform really requires Generative AI.
However, we suggest you integrate generative AI into your software as it reduces manual efforts and the risk that comes with it. If you are looking for a company that can help you integrate or develop an AI fintech app then you must check out Appic Softwares.
They have 10+ years of mobile app development and 3+ years of AI development experience which ensures that you have the best of the product.
With three years of experience in celebrity blogging, I share insightful content on the world’s most famous personalities through my personal blog, FameRevUp.