The Banking and Finance industry is the center of our economic system, offering financial services to individuals and businesses worldwide. However, this system faces many operational challenges, from data handling to reliable customer service and increasing decision-making and productivity.
Generative Artificial Intelligence (AI) is helping to reshape the future for many banking and finance companies, from risk assessments to fraud handling and financial planning for customers. Let’s take a dive and explore Generative AI in banking, examine the benefits, and highlight proven examples.
Exploring GenAI Use-Cases in Banking and Finance
1. Fraud Agent
Cybercrime Magazine predicts that by 2025, cybercrime and fraud will cost $10.5 trillion globally. Many global banks have dedicated fraud prevention teams to prevent fraud cases from increasing; however, due to cost and maintenance, sometimes fraud prevention departments aren’t as effective.
AI in banking and insurance can help with fraud detection, as banks can trace fraudsters’ locations, systems, and even devices. Gen AI can detect specific algorithms by analyzing data and keeping up with the latest fraud cases. An example of this is AI chatbots, as many banks use security questions to identify customers and ensure their data is protected.
Gen AI in banking and finance companies can help manage risk assessments and avoid financial disruptions for clients. Gen AI can work to identify possible financial risks and ensure that specific financial cases are resolved if any warning signs occur. Regarding credit scoring, banks can adopt Gen AI, which can study large amounts of data and provide information regarding a client’s claim.
2. Customer Interaction Search Agent
Customer satisfaction is the backbone of all companies, especially in finance and banking. A customer Interaction Search Agent focuses on improving customer services, interacting with customers, answering inquiries, and providing context on different finances.
AI chatbots and agents can support customers 24/7 by answering inquiries, providing updates, collecting information, and discussing transfers. Gen AI in banking is advancing, and many companies are adopting this idea. The Bank of America uses virtual AI assistants to support customers and answer specific inquiries.
3. Regional Market Intelligence Analyst
Business and company leaders want to know financial performances, market trends, and customer preferences. Gen AI tools can look into financial performances amongst companies and produce data to show predictions for the company’s future assets.
Gen AI works with banking and finance to help with data analysis and financial documentation, reducing risks and helping customers.
Gen AI will be able to identify specific patterns regarding data, which will help financial companies discuss future business outcomes. By incorporating Gen AI in banking and finance, many companies worldwide can make reliable financial decisions based on the data provided.
4. Marketing Content Generator
Marketing materials such as websites, blogs, email marketing, and social media ensure that companies reflect their different services. Targeted marketing and content for businesses will help increase revenue and attract new customers.
Gen AI in banking and finance will begin to improve the marketing process, as Gen AI solutions will provide tailored marketing posts, content, and campaigns to reach different target audiences. AI can also produce specific marketing materials and track customer rates toward the company.
5. Financial Data Analyst
Banks and financial companies must examine data and collect the correct financial documents to support customers. Companies can use Gen AI to investigate essential data and summarize relevant documents to reduce time and increase company productivity. This is efficient as customer inquiries will be sorted, and increased productivity will be contained throughout the company.
Companies with advanced technologies like LangChain and Hugging Face offer reliable Gen AI materials. However, there is still room for improvement. Given the fast growth in technologies and financial companies, responses to clients and resolving possible fraud cases are essential.
Lyzr offers a Gen AI agent framework, to help you build AI systems that meet your company requirements. With Lyzr’s SDK package, customers can personalize their AI Agents to ensure they fit their financial criteria with features such as analysis agents, knowledge bots, and responsive 24/7 chatbots to help with customer inquiries. Check out our latest demo.
Examples of Companies Using Gen AI in Banking
Generative AI has been shown to help revolutionize the banking and finance industry through chatbots and learning machines. A survey conducted by American Bankers for 2024 found that 75% of finance workers believe AI in banking and finance will change how companies run.
This is due to the progressive advancement of chatbots and machines working in different parts of companies, such as customer service, data, fraud investigations, and content. Furthermore, an Accenture report predicted that by 2028, banking companies’ productivity will increase by 30%. Here are some examples of Generative AI use cases within the banking and finance industry:
Enova: The Use of Chatbots
Enova is a world-leading international financial company based in the United States and is currently using the advancements of Gen AI in banking and finance. The company uses AI and chatbot learning machines to provide credit assessments and financial data. With this, the company wants to ensure it can help small businesses and consumers solve real-life financial problems with the help of AI.
SoFi: Virtual Assistants
Online banking companies like SoFi, an American online finance and banking company, also use Gen AI. The company helps many small businesses and clients with credit scores, student loans, savings accounts, and business loans. SoFi is using AI to support customers regarding online inquiries and offering a 24/7 virtual assistant. This would automatically improve the company’s online presence and ensure all customer problems are solved when needed.
Morgan Stanley: Analysis of Data and Finances
Morgan Stanley is a world-leading bank and finance company based in New York City. The company uses AI chatbots to support financial advisors. The AI chatbots conduct intense research, analyze data, and offer financial insights to help clients and financial advisors.
PKO Bank Polski: Underwriting Approvals and CRM Systems
PKO Bank Polski is known for being one of the largest banks in Poland. It has implemented AI tools to improve customer service and online banking procedures. The band also uses Gen AI to improve underwriting approvals, CRM systems, analysis of necessary documentation, and risk assessments. This shows how Gen AI in banking and finance is progressively changing to increase workplace functionality and customer satisfaction.
| An Interesting Statistic about GenAIStatistics published by the Statista Research Department reflected how the banking sector will be significantly impacted with the support of Generative AI. The possible added value to banking companies will increase between 200 and 340 billion U.S. dollars. This shows how the Gen AI in the banking sector will significantly increase profit by 9-15%. |
SaaS vs AI Agents in Banking & Finance
GenAI presents a reliable tool within banking and financial services, as companies can increase productivity, gather information faster, analyze data, and even ensure customers are satisfied with services.
By providing customers with services like 24/7 accessible chatbots to address and resolve queries, help with banking related issues and streamline financial transactions, customers worldwide can have a better experience. AI in banking and finance is rapidly progressing, and there are several options available – either in the form of SaaS tools, custom GenAI solutions and pre-built AI agents. But which one should you choose?
Let’s break it down.
SaaS Integrations:
The fastest way for banking and finance institutions to deploy GenAI tools is by integrating with a SaaS platform. This ready-to-use format makes it easy to set up and begin functions soon after purchase. However there are certain limitations too.
Pros:
- Easy to integrate and set-up
- Easily available
- Does not require coding or AI expertise
Cons:
- Data is not secure
- Hosted on an external platform
- Dependency on vendor can cause issues with functionality, latency, response time etc
Custom AI Solutions:
The next option for an enterprise is to build GenAI solutions internally, or deploy with a framework like Langchain. This ensures privacy and security, however requires a large amount of resources as well.
Pros:
- Complete data privacy
- Locally deployable code
- Manual customization is possible
Cons:
- Requires weeks or months to deploy
- Need dedicated AI/ML team
- Limitations with agent integrations
Privately Integrated AI Agents:
The third alternative, and perhaps the most lucrative, is opting for pre-built SDKs like Lyzr to deploy private AI agents for enterprise. Organizations like Lyzr develop these SDKs (software development kits) which can be thought of as a ready-to-cook meal. All the components are coded and included in the framework, and it only needs a few lines of code to integrate into the backend systems.
Let’s take a look at the benefits of building AI Agents with Lyzr:
Choosing Lyzr to Build Private & Secure AI Agents
Lyzr offers the options for enterprises to build custom AI agents to increase customer satisfaction and meet all business objectives. When you integrate Lyzr SDKs to build private AI agents, you have access to several benefits:
- Reliable Privacy and Security
Lyzr offers a chance to expand your business while supporting high-tech privacy and security when using our personalized chatbots. As many banking and finance companies need the correct privacy protection in place, Lyzr SDK works to solve any data privacy and protection concerns.
- Multi-Agent Workflow Automation
Lyzr allows its customers to have a wide range of AI agents to complete tasks or take on the role of an entire job without any human interaction. This involves SDR automation, project updates, and meeting summarization.
- 24/7 Support
Lyzr personalized AI agents offer 24/7 support to ensure all inquiries are answered and projects are completed for your business.
- Personalized Private AI Agents
Each AI agent produced will be personalized for your business and its needs. Whenever you need support on projects, topics, research, or customer inquiries, Lyzr can help.
Lyzr will work to provide tailored bots for many banking and finance companies to ensure fraud is reduced, data analysis increases, and marketing campaigns are produced. Lyzr’s Agent SDK ensures companies’ privacy and data are protected.
It has proven to empower many global financial companies by increasing customer interaction through AI bots. Get ready to embark on a journey with Lyzr, as Gen AI will revolutionize your company and ensure all business requirements are met.
A New World with GenAI – What’s in Store?
The future of AI in banking and finance offers advancing potential. The industry is continuously increasing and ensuring they can embrace different technology advancements, as Gen AI is something financial services are moving towards.
All in all, GenAI is quickly becoming popular across different industries and functions. Soon, we may not remember a time when tasks weren’t automated with the help of AI.
Our team has curated a list of over 100 GenAI use-cases across industries, from automobile to banking and more. Click below to download!
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