AI Use Cases in Banking

Discover how banks can effectively leverage generative AI to streamline operations and drive innovation

Generative AI in finance offers dynamic solutions for enhancing operations and driving progress. It holds significant promise in finance, offering functionalities including text summarisation, generation, data analysis and information retrieval.

<35%

front-office employees’ productivity growth

15%

call centre’s productivity growth

Main Use Cases of Generative AI in Banking

1. Financial document summarisation

2. FAQ chatbot for employees

3. Onboarding & general information

4. Financial planning & analysis

5. Forecasting and strategic planning with AI

6. Market research and gathering insights

7. Budget forecasting and expense analysis

8. Financial reporting automation and feedback gathering

9. Ensuring regulatory compliance with AI

10. Debt collection with generative AI voice bots

11. Fraud alerts and account security with AI voice bots

In financial services, creating reports is essential but can be very time-consuming. Many financial professionals face the challenge of manually summarising extensive documents from various sources, which is slow and overwhelming.

Using large language models (LLMs) can simplify this process. Integrating LLMs into your systems lets your teams quickly convert lengthy documents into clear, concise summaries. This speeds up report generation and frees up time for strategic planning and innovation.

Pro tip

It’s crucial to prioritise data protection by avoiding including sensitive personal or company information in third-party AI tools. For enhanced data security, consider acquiring enterprise-grade AI solutions that can be deployed on-premise to maintain control over sensitive data.

In financial services, employees often spend time answering repetitive questions. An AI-powered FAQ chatbot can address this by drawing information from various sources to handle common transactions, accounts, and billing inquiries.

With its broad range of AI chatbot use cases, this tool acts as a central resource for all departments. It speeds up information retrieval and cuts down the time spent searching for documents, ultimately saving time and money.

Pro tip

Deploying an AI chatbot integrated with organisational databases is a valuable investment in employee productivity.

Tovie Data Agent simplifies information retrieval. It functions like a personal assistant that understands natural language and instantly delivers responses with links to pertinent documents from the database.

Using generative AI in onboarding helps financial organisations simplify the process for new employees. The large amount of information during onboarding, ranging from company policies to report templates, can be overwhelming. AI can create interactive and personalised training modules, making learning easier for new team members.

GenAI acts as a one-stop resource, providing access to onboarding documents, training materials, and procedural guides. This centralises information, making it easy to find and understand, helping new hires quickly grasp their roles.

In this business use case, implementing generative AI in onboarding provides a clear and efficient path for new employees to integrate into their teams, boosting productivity and skill development.

Pro tip

Generative AI is helping prevent employee burnout by taking on repetitive tasks and reducing information overload. Want to learn more? Check out our free whitepaper on combating workplace burnout.

We've gathered insights from leading HR and People Management experts, combining their experiences with our AI knowledge to show how this technology can make a difference.

AI-powered tools can streamline your financial planning by removing processing bottlenecks. With AI algorithms, stakeholders can quickly analyse data from multiple sources to create efficient financial plans. This AI use case allows for rapid scenario modelling without manual data sorting, speeding up the analysis and providing a clear understanding of potential financial outcomes.

This solution isn't limited to finance. It also enhances scenario modelling across departments, promoting inclusivity in planning. Generative AI simplifies complex financial models, leading to better decision-making and reduced manual data processing.

Enhance your forecasting with AI tools that provide both short-term and long-term insights. Generative AI simplifies document analysis, integrating internal processes and market conditions for strategic planning. Users can get tailored forecasts by inputting specific documents and setting forecasting timelines.

One of the top AI use cases is its ability to efficiently transform operations in the finance, legal, and corporate development sectors. Experience the benefits of AI-driven forecasting to streamline operations and support strategic growth.

Unlock valuable market insights effortlessly with GenAI technology. From cost details to comparative analysis reports, AI excels at providing comprehensive pricing insights. 

In the banking sector, generative AI simplifies competitor analysis, enabling departments to identify trends and craft effective marketing strategies. By analysing competitor data and extracting insights from text-heavy documents, reports, and articles, AI helps understand market trends, competitor activities, and customer sentiments with precision.

Pro tip

Upload detailed information about your buyer personas, market segments, and product details to your generative AI tool. The more familiar the AI is with your company’s products and target audience, the better the results it will produce.

GenAI tools simplify budget forecasting and expense analysis. By analysing historical project data, AI predicts potential overruns and recommends adjustments based on past performance. 

Additionally, these tools categorise expenses and analyse cash flow patterns in project reports, aiding finance departments in predicting liquidity challenges and pinpointing areas for cost optimisation. Experience seamless budget management with GenAI for accurate financial planning and optimised project outcomes.

Generative AI improves finance by automating the creation of textual reports and efficiently summarising key indicators and market trends. AI-powered FAQ bots are customised to individual needs and reports, answering follow-up questions quickly. 

By implementing this AI automation use case, the ELT and Sales teams can quickly access accurate information, saving time and enabling prompt responses. Share this bot in Microsoft Teams or other preferred channel for specialised report inquiries to enhance collaboration and efficiency in your organisations.

Pro tip

Use AI tools trained on your company’s product data. For instance, Tovie Data Agent can learn from your databases to swiftly and accurately prepare responses to customer reviews.

GenAI can ensure regulatory compliance by monitoring financial documents and transactions against laws and regulations. By flagging potential compliance issues, it aids finance departments in promptly resolving any issues that may arise. Through this practical generative AI b2b use case, experience the peace of mind that comes with streamlined compliance monitoring.

Debt collection can be made more efficient with generative AI voice bots. These bots automate both inbound and outbound calls, significantly easing the burden on human agents and cutting down wait times. 

They can send automated reminders for overdue payments, negotiate payment plans with debtors, and make follow-up calls to confirm receipt of payments. By understanding natural language, these AI bots offer human-like assistance and efficiently resolve customer queries.

Pro tip

Like any AI application, ensure robust data security protocols are in place to safeguard sensitive information.

AI-powered voice bots enhance fraud alerts and account security by making numerous outbound calls and taking calls outside business hours. They notify customers of suspicious account activity, provide steps to secure accounts, prevent fraud, and confirm recent transactions.

These bots interact like human agents, asking questions and calling back if clarification is needed while logging all data into a database.

Pro tip

Like any AI application, ensure robust data security protocols are in place to safeguard sensitive information.

1. Financial document summarisation

In financial services, creating reports is essential but can be very time-consuming. Many financial professionals face the challenge of manually summarising extensive documents from various sources, which is slow and overwhelming.

Using large language models (LLMs) can simplify this process. Integrating LLMs into your systems lets your teams quickly convert lengthy documents into clear, concise summaries. This speeds up report generation and frees up time for strategic planning and innovation.

Pro tip

It’s crucial to prioritise data protection by avoiding including sensitive personal or company information in third-party AI tools. For enhanced data security, consider acquiring enterprise-grade AI solutions that can be deployed on-premise to maintain control over sensitive data.

2. FAQ chatbot for employees

In financial services, employees often spend time answering repetitive questions. An AI-powered FAQ chatbot can address this by drawing information from various sources to handle common transactions, accounts, and billing inquiries.

With its broad range of AI chatbot use cases, this tool acts as a central resource for all departments. It speeds up information retrieval and cuts down the time spent searching for documents, ultimately saving time and money.

Pro tip

Deploying an AI chatbot integrated with organisational databases is a valuable investment in employee productivity.

Tovie Data Agent simplifies information retrieval. It functions like a personal assistant that understands natural language and instantly delivers responses with links to pertinent documents from the database.

3. Onboarding & general information

Using generative AI in onboarding helps financial organisations simplify the process for new employees. The large amount of information during onboarding, ranging from company policies to report templates, can be overwhelming. AI can create interactive and personalised training modules, making learning easier for new team members.

GenAI acts as a one-stop resource, providing access to onboarding documents, training materials, and procedural guides. This centralises information, making it easy to find and understand, helping new hires quickly grasp their roles.

In this business use case, implementing generative AI in onboarding provides a clear and efficient path for new employees to integrate into their teams, boosting productivity and skill development.

Pro tip

Generative AI is helping prevent employee burnout by taking on repetitive tasks and reducing information overload. Want to learn more? Check out our free whitepaper on combating workplace burnout.

We've gathered insights from leading HR and People Management experts, combining their experiences with our AI knowledge to show how this technology can make a difference.

4. Financial planning & analysis

AI-powered tools can streamline your financial planning by removing processing bottlenecks. With AI algorithms, stakeholders can quickly analyse data from multiple sources to create efficient financial plans. This AI use case allows for rapid scenario modelling without manual data sorting, speeding up the analysis and providing a clear understanding of potential financial outcomes.

This solution isn't limited to finance. It also enhances scenario modelling across departments, promoting inclusivity in planning. Generative AI simplifies complex financial models, leading to better decision-making and reduced manual data processing.

5. Forecasting and strategic planning with AI

Enhance your forecasting with AI tools that provide both short-term and long-term insights. Generative AI simplifies document analysis, integrating internal processes and market conditions for strategic planning. Users can get tailored forecasts by inputting specific documents and setting forecasting timelines.

One of the top AI use cases is its ability to efficiently transform operations in the finance, legal, and corporate development sectors. Experience the benefits of AI-driven forecasting to streamline operations and support strategic growth.

6. Market research and gathering insights

Unlock valuable market insights effortlessly with GenAI technology. From cost details to comparative analysis reports, AI excels at providing comprehensive pricing insights. 

In the banking sector, generative AI simplifies competitor analysis, enabling departments to identify trends and craft effective marketing strategies. By analysing competitor data and extracting insights from text-heavy documents, reports, and articles, AI helps understand market trends, competitor activities, and customer sentiments with precision.

Pro tip

Upload detailed information about your buyer personas, market segments, and product details to your generative AI tool. The more familiar the AI is with your company’s products and target audience, the better the results it will produce.

7. Budget forecasting and expense analysis

GenAI tools simplify budget forecasting and expense analysis. By analysing historical project data, AI predicts potential overruns and recommends adjustments based on past performance. 

Additionally, these tools categorise expenses and analyse cash flow patterns in project reports, aiding finance departments in predicting liquidity challenges and pinpointing areas for cost optimisation. Experience seamless budget management with GenAI for accurate financial planning and optimised project outcomes.

8. Financial reporting automation and feedback gathering

Generative AI improves finance by automating the creation of textual reports and efficiently summarising key indicators and market trends. AI-powered FAQ bots are customised to individual needs and reports, answering follow-up questions quickly. 

By implementing this AI automation use case, the ELT and Sales teams can quickly access accurate information, saving time and enabling prompt responses. Share this bot in Microsoft Teams or other preferred channel for specialised report inquiries to enhance collaboration and efficiency in your organisations.

Pro tip

Use AI tools trained on your company’s product data. For instance, Tovie Data Agent can learn from your databases to swiftly and accurately prepare responses to customer reviews.

9. Ensuring regulatory compliance with AI

GenAI can ensure regulatory compliance by monitoring financial documents and transactions against laws and regulations. By flagging potential compliance issues, it aids finance departments in promptly resolving any issues that may arise. Through this practical generative AI b2b use case, experience the peace of mind that comes with streamlined compliance monitoring.

10. Debt collection with generative AI voice bots

Debt collection can be made more efficient with generative AI voice bots. These bots automate both inbound and outbound calls, significantly easing the burden on human agents and cutting down wait times. 

They can send automated reminders for overdue payments, negotiate payment plans with debtors, and make follow-up calls to confirm receipt of payments. By understanding natural language, these AI bots offer human-like assistance and efficiently resolve customer queries.

Pro tip

Like any AI application, ensure robust data security protocols are in place to safeguard sensitive information.

11. Fraud alerts and account security with AI voice bots

AI-powered voice bots enhance fraud alerts and account security by making numerous outbound calls and taking calls outside business hours. They notify customers of suspicious account activity, provide steps to secure accounts, prevent fraud, and confirm recent transactions.

These bots interact like human agents, asking questions and calling back if clarification is needed while logging all data into a database.

Pro tip

Like any AI application, ensure robust data security protocols are in place to safeguard sensitive information.

Key steps to adopt AI securely

One of the primary concerns when utilising generative AI in business is the security and privacy of sensitive information, especially in industries with strict regulatory requirements. Companies may face legal and financial risks, data misuse, lack of data consistency, and regulatory non-compliance.

1. Data security and privacy

Deploying GenAI on-premises guarantees proper safeguarding of sensitive data and maintains control over the database’s access levels. By deploying AI models on-premises in your private cloud, you can leverage their powerful capabilities while maintaining complete control over how your data is handled, stored, and managed.

2. Tackling hallucinations

AI answers are only as good as the data they are exposed to. Hallucinations in AI models occur when input data is poorly processed. If documents are chunked or pre-processed inadequately, or if the context is fragmented across different chunks, the AI model can become confused and produce incorrect answers.

To prevent this, documents must be pre-processed correctly to ensure all necessary context is included. While it would be ideal to simply upload PDFs or CSVs, additional pre-processing is often required, especially for tabular or graph-based data. This may involve semi-manual or manual processing to achieve better results.

Tovie AI offers services to assist clients with data pre-processing, enhancing the accuracy of AI-generated answers. Contact our team to learn more.

How to define your AI use case?

Generative AI consulting with Tovie

Harness the power of generative AI to outperform competitors and fast-track innovation. Our experts will collaborate with you to map the best AI use cases for your company and determine where the disruptive technology can bring the most value.

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AI is growing fast, and it can be tricky to know how to use it safely at work. Our free whitepaper, "How to Use Generative AI for Your Data," provides practical tips and creative ideas for getting started.

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