Many SMBs grapple with finance workflow. Even with accounting and finance software they had in place, businesses still spend too much time generating invoices, consolidating accounts, preparing annual reports, and more. With ChatGPT, you can potentially save time, resources, and effort in getting your finances in order.
But first, you need to learn how to integrate ChatGPT into the finance software your business uses. ChatGPT is powered by generative AI models developed by OpenAI. It has evolved tremendously in recent months, unlocking possibilities for ChatGPT-powered financial analysis, summary generation, and other tasks.
According to Statista, generative AI in financial services will grow at a CAGR of 28.1%, potentially hitting $9.4 billion by 2032. This marks the benefits that genAI tools like ChatGPT promise and their widening use cases. The question is — how do you go about using ChatGPT for finance?
I’m Oleh Komenchuk – Machine Learning Engineer at Uptech. Together with our development team, I’ve helped companies like Presidio Investors integrate generative AI with their financial products. And I hope to do the same for you by sharing the steps required to integrate ChatGPT with your finance software.
Let’s start.
How to Integrate ChatGPT into Finance Software: 9 Key Steps
Though not extremely complicated, using chatGPT for finance is not straightforward either. We don’t recommend feeding the ChatGPT app directly with your financial data because of privacy concerns. Rather, follow these steps to integrate ChatGPT effectively and safely with your finance or accounting app.
Step 1: Define Objectives and Use Cases
ChatGPT, as a language model, is helpful in many applications. It can analyze data at scale, detect anomalies, converse naturally, and more. However, you must determine how you want to use ChatGPT for your finance software and build a workflow for the respective use case.
Ideally, integrate ChatGPT into tasks that your finance team spends the most time on. Let’s say you’re running a retail business and struggle with invoicing mistakes. In this case, you can integrate ChatGPT with your accounting software to streamline invoice creation and cross-check billing codes before sending them to customers.
So, ask these questions when you want to introduce ChatGPT capabilities in your finance software.
- Do you want better clarity on your financial standings?
- Are you spending too much time on repetitive tasks?
- Is financial management consuming too many resources your business can spare?
Once you’ve identified a clear and convincing purpose, proceed to the next step.
Step 2: Assemble the Development Team
It goes without saying that you need a development team to integrate ChatGPT with your finance software. Although you’re not training an entire generative AI model from scratch, you still need developers to implement machine learning functionality with OpenAI’s API.
Besides AI developers, your team should also include the following specialists.
- A project manager who coordinates the entire development process.
- UI/UX designer to optimize the customer journey and prevent disruption to user flow after the integration.
- Web or app developers for creating, revamping, or modifying user-facing apps and interfaces.
- Backend developers who build and manage backend services the financial software needs.
- QA engineers for testing the app for bugs, vulnerabilities, and other software issues.
SMBs can either hire an in-house team or engage a reliable outsourcing development partner. If you choose the first option, be prepared for the salary, perks, and other expenses your business must bear. Plus, you must personally oversee the integration effort. Alternatively, you can outsource AI integration services to Uptech. This way, you can focus on your core business activities while we build a ChatGPT-enabled fintech app for you.
Step 3: Prepare Your Development Environment
Before developers can work on the ChatGPT integration, they need tools and frameworks to work with. And that’s where your immediate task lies.
Set up development tools
Prepare the tools your developers need to integrate ChatGPT into your finance app. Like any other software development work, you’ll need tools like:
- Integrated Development Environment (IDE), which brings together the editor, compiler, libraries, and other software development framework into a unified workspace.
- Version control tools like GIT to support continuous integration and continuous development (CI/CD) practices and enable rollback.
- SDKs, such as OpenAI SDKs, and those that support finance and accounting functionalities you want to use in the app.
Acquire API access
Then, register for an OpenAI developer account to get the API key, which is unique to every account. Your developer will need the key to call the ChatGPT services from OpenAI’s SDK.
Step 4: Design the Integration
ChatGPT finance integration is more than making API calls at random parts of the app. Rather, you need to carefully plan how users interact with the AI engine and consider their privacy.
Define interaction flow
Much of the work involved in fitting ChatGPT capabilities seamlessly into the existing workflow. For example, if your finance analysts spend a lot of time browsing through past records to retrieve specific data, you’ll need to identify ways to automate with ChatGPT.
For example, your developer reroutes a query to track project costs and milestones through ChatGPT’s text generation service. Then, the AI model would analyze the underlying data and return a summary. After receiving the outcome, the finance app would map the figure into charts and tables for your finance analysts.
Prioritize data handling
Often, merely introducing ChatGPT capabilities cannot automate all financial tasks. Rather, you’ll need to connect ChatGPT with your company’s accounting and finance database. To do this, it’s important to prioritize data security, privacy, and compliance. Otherwise, your business risks data breaches, information leakage, and costly penalties.
So, pay attention to how you design the data pipeline between your finance software and OpenAI’s language model. Employ security measures like encryption and secure coding to comply with data privacy acts like GDPR, PCI-DSS, and CCPA.
Step 5: Implement the Backend Integration
When you integrate ChatGPT with your finance system, you need to work on both the software’s backend and front end. Let’s start with what you should do with the backend part.
API integration
The backend, which is the part hidden from business users, is the heart of the entire software. It handles a range of critical tasks, including consolidating data requests, processing business logic, and exchanging data with third-party services.
To communicate with OpenAI’s language model, your backend application needs to support HTTP requests because that’s the data exchange protocol that ChatGPT’s API uses. So, perform a software audit on your existing finance system to see if it can handle HTTP requests. Otherwise, you might need to modify or revamp the backend application before proceeding.
Despite leveraging the API, developers still need to write codes, although minimal, particularly when modifying existing functions. To do that, they use Python, a common programming language for AI development.
Business logic
Being able to submit requests and process the responses from ChatGPT isn’t enough to successfully integrate it with your finance software. What’s equally important is making appropriate changes to your software’s business logic. Depending on the business, the scale of modification can vary greatly.
Let’s say you want to use ChatGPT to generate profit and loss reports from transaction records. Then, from the result, you want the software to automatically alert specific stakeholders if the result deviates from projections. To do that, developers create or modify the reporting business logic in the software.
When working with business logic, developers collaborate closely with finance professionals to standardize format, compliance, and other criteria. As with working on API integration, developers will write codes, test the business logic, and revise the modules accordingly.
Step 6: Integrate with the Frontend
Though not directly exchanging data with ChatGPT, you must pay equal attention to the software’s front end. Chances are, you’ll need to modify the software’s user interface or create a new one because of the added AI functionality. Then, developers will bridge both the frontend and backend parts of the financial system with the appropriate data exchange framework.
User interface design
Generative AI is complex, but the AI feature on your financial app shouldn’t be. And that’s where good UI/UX best practices come in. When revamping your app’s user interface, consider how the changes would affect interactions. For example, some features are best accessed via a chatbot, while others require a voice assistant or an AI tool.
From submitting requests to ChatGPT to viewing the results, the entire process should be guided by a seamless workflow. Choose layouts, colors, fonts, and other visual elements that not only reflect your brand values but also allow users to navigate through their tasks easily.
Often, creating a visually pleasing and user-friendly interface requires a blend of creative talents, conversational design principles, and programming skills. For example, developers use HTML and JavaScript to build a responsive chat interface, which UI/UX designers layer with a layout designed for aesthetics, accessibility, and usability.
Frontend-Backend Communication
With both the frontend and backend completed, the next step is to bring both parts together. When doing so, pay attention to data flow, authentication, and latency between both parts of the financial app.
Let’s say you’re integrating ChatGPT with an investment app to recommend investment strategies. To do that, the app needs to gather personal information the user fills out on the frontend and sends it to the backend services for further processing.
We can’t stress how important it is that the data exchange must take place on a secure, reliable, and low-latency channel. As such, we recommend using REST APIs or WebSockets to bridge the frontend and backend parts of the finance system.
- REST APIs are known for their speed. They reduce the compute resources the backend server needs to handle user requests.
- Web Sockets allow low-latency, two-way communication between server and client applications.
Step 7: Ensure Data Security and Compliance
Another area that deserves your attention is safeguarding the data the finance software collects, stores, and exchanges with ChatGPT. When you send data through ChatGPT with API, OpenAI stores them for 30 days. While OpenAI doesn’t use the data to train the model, it’s prudent to anonymize them to protect your user’s privacy.
Besides, we strongly suggest securing financial data, especially those containing sensitive information, at all interaction points. Use security measures like encryption, authentication, and authorization to control how data are represented, secured, and exchanged with various services.
At Uptech, we believe that data security is a collective responsibility of all stakeholders. Besides securing data with technologies, communicate your data policies and security best practices to app users. It strengthens their confidence in the ChatGPT integration that you want to introduce.
At the same time, ensure the data security measures you implement are sufficient to comply with data privacy regulations like:
- GDPR mandates businesses serving the EU market to empower users with control over how their data are managed, used, and stored.
- CCPA is a data privacy act that applies to businesses serving Californian residents. Like GDPR, it allows users to know how their data are used and grants them the right to delete the stored data.
- PCI-DSS regulates how companies secure and process credit card payment data. It details security practices, technologies, and standards that businesses must apply to protect card information.
Step 8: Test the Integration
Before you deploy the finance ChatGPT integration in your software, test it thoroughly. Better still, make continuous testing a part of your development process. This prevents costly reworks when bugs are discovered after your developers have finished integrating several services.
There are various tests you can perform, but here are the most critical ones.
Unit testing
Unit tests are designed to measure the consistency and accuracy of individual software functions. It uncovers bugs and allows developers to remediate them before those functions are integrated with other modules.
Integration testing
Integration testing ensures that the software is stable and can exchange data reliably with third-party services. In this case, QA engineers ensure that OpenAI’s ChatGPT returns the expected responses to the requests the financial software sends.
User acceptance testing (UAT)
UAT is the final lap before your ChatGPT-powered software is considered fit for release. It involves enrolling users to try out the newly implemented and existing features. Then, the QA team collects the test results and feedback to ensure the software is helpful, accurate, and consistent.
Step 9: Deploy and Monitor
After the software has passed the various test cases, prepare for deployment. Prepare all stakeholders for the upgrade by providing ample notice. Inform them of the impending changes and provide training if necessary.
Then, release the software and put your technical support team on standby. Be prepared to respond to any incidents, such as bug reports and app support. Make appropriate changes to the software and release.
As ChatGPT is an integral part of your finance software, you’ll need to keep updated on upcoming changes from OpenAI. For example, if a new model rolls out, you might need to assess and replace the current model your software uses.
10 Ways to Use ChatGPT in Finance
ChatGPT has grown leaps and bounds from the day it was introduced to the public. With GPT-4o powering the chatbot, ChatGPT’s possible use cases for finance have greatly expanded.
1. Customer Support and Engagement
ChatGPT is a large language model, which means it can converse naturally like humans. You can use ChatGPT to augment your customer support team so they can channel their effort to solve more complex issues. As for customers, they don’t need to spend precious time waiting just to get a simple question answered.
For example, Bank of America launched Erica, an AI chatbot that helps customers access banking information, make payments, suggest financing options, and more through casual conversations.
2. Fraud Detection and Prevention
Banks and financing institutions seek ways to block suspicious transactions and alert their customers immediately. ChatGPT can be helpful in this because it can analyze massive transaction data at scale and in real-time. The chatbot can also work cohesively with other machine learning models to alert users of fraudulent attempts.
Capital One provides a glimpse of such a possibility with Eno, its AI-powered chatbot. Eno can alert users if suspicious transactions are detected in their accounts and help them resolve such issues.
3. Personalized Financial Advice
As financing institutions pivot their customer engagement strategy towards personalized offerings, they seek a reliable method to do so. Again, ChatGPT can be an ideal mechanism to enable personalized services, including providing financial advice. It can analyze customers’ profiles, uncover hidden patterns, and provide tailored recommendations.
A perfect example of this is Cleo, a personal financial app that uses conversational AI to analyze user’s financial standings and offer ways to strengthen them.
4. Wealth Management
ChatGPT is equally helpful for helping investors understand and manage their portfolios. Investors can also use conventional AI to track portfolio performance and derive market insights. The AI chatbot can analyze volumes of investment data, extract key information, and summarize it for users.
Tired Banker, an AI-powered fintech app we built, uses GPT-4 to summarize earning reports of S&P 500 companies for finance users.
5. Risk Management
Bankers, finance managers, and insurers alike make many financial decisions in a short period. Oversights, which occasionally occur, might put the organization at risk. For example, an insurer might set a policy at a value that proves disadvantageous in the long run.
ChatGPT can help them make better-informed decisions by uncovering, analyzing, and comparing risk factors at scale. Rather than replacing human managers, it assists them by laying out every possible option and its possible implications.
6. Regulatory Compliance
ChatGPT, being a powerful language model, can help finance teams comply with accounting, audit, and other business regulations. When integrated with finance software, the AI model can analyze finance documents, including invoices, receipts, contracts, and other textual assets. From there, the model compares its findings with audit guidelines and informs stakeholders if it finds any anomalies.
7. Market Analysis and Predictions
Investors want to assemble a portfolio that maximizes their return. To do that, they need to analyze volumes of data and detect complex trends. Both are challenging for humans. Conversely, ChatGPT can augment investors with its ability to make reasonably accurate predictions based on various factors.
Already, such possibilities have turned into reality in the investment industry. Recently, Bridgewater launched a $2 billion fund that is primarily managed by machine learning.
8. Loan Origination and Credit Scoring
Before a lending institution can approve a loan application, they need to conduct background checks, assess risks, and assign the applicant a credit score. Conventionally, the process takes days or weeks, which can be significantly reduced by ChatGPT. With the AI chatbot, bankers can automate credit scoring by integrating the model with the loan processing workflow. Rather than weeks, they can process a loan in minutes.
Zest AI is a great example. It offers AI-powered credit scoring to lenders so they can make fair, inclusive, and accurate decisions while minimizing risks.
9. Automating Routine Financial Tasks
As a business owner, you might have spent a lot of resources on data entry, issuing invoices, consolidating receipts, reminding customers of payments, and more. With ChatGPT, many of these mundane tasks can be automated. When integrated with accounting software and optical recognition technologies, ChatGPT can process financial data from various sources, categorize them, and automate alerts for respective parties.
10. Enhancing Virtual Assistants
Most SMB financial apps are already built-in with virtual assistants to streamline mundane tasks and retrieve information from the company’s knowledge base. However, conventional virtual assistants are limited in many ways. They lack the natural language understanding capabilities that generative models possess.
On this note, ChatGPT can make virtual assistants smarter by improving the latter’s cognitive capabilities. With ChatGPT, virtual assistants can interpret user requests accurately and provide accurate results.
How ChatGPT Integration in Finance Software Can Positively Affect Your Business
SMBs, in their strive for growth and operational efficiency, have strong motivations to integrate ChatGPT with their finance software. With an AI-powered financial solution, they stand to gain from many fronts.
Improved customer support and engagement
Customers no longer need to wait as they’re put through to human support personnel. With ChatGPT, you have 24/7 frontline support that can answer common questions and escalate queries to human agents when required.
Coupled with personalized interaction, customers will feel engaged and valued throughout their entire interaction with your business. As ChatGPT becomes more eloquent through every update, the chatbot becomes more capable of evaluating users’ sentiments and adjusting their style and tone of response.
Enhanced fraud detection and transaction security
Finance ChatGPT allows your business to be more vigilant against fraudulent attempts. Once integrated with your finance software, ChatGPT can be a reliable watchdog against anomalous transactions and other suspicious activities. While some scam attempts can escape human surveillance, it’s harder to bypass an AI model’s robust and broad monitoring.
As ChatGPT detects a possible fraud, it immediately alerts all stakeholders. And if you connect the model to other safeguard measures, there will be no room for the perpetrator to act. For example, the suspicious transaction will be instantly flagged and halted to prevent users from losing their money.
Personalized financial advice and wealth management
As we’ve pointed out, ChatGPT can play a versatile advisory role when integrated with financial solutions. When introduced as a chatbot, it offers advice, recommendations, and solutions based on individual preference. For example, ChatGPT can analyze customers’ spending patterns and recommend a suitable financial plan.
Besides personalizing customer experience, ChatGPT can also assist investors in managing their portfolios more effectively. As a generative AI model, ChatGPT excels in spotting trends amidst volumes of market data and predicting possible investment outcomes. Investors could then use the results to support their choices when growing their portfolios.
Increased efficiency through automation of routine tasks
Finance teams are no longer bogged down by mundane processes when you introduce generative AI capabilities into the software they use. ChatGPT can streamline bookkeeping, invoicing, reporting, and other related tasks by relieving finance personnel from repetitive work. This results in fewer human errors and allows finance teams to work on more strategic tasks.
Another benefit that SMBs enjoy is ChatGPT’s capability to monitor compliance efforts. Instead of manually keeping up with regulation changes, you can enable automated monitoring with ChatGPT to ensure your business continuously remains in compliance with financial and data privacy acts.
Things To Consider While Integrating ChatGPT with Finance Software
Undoubtedly, SMBs will benefit from ChatGPT finance integration. However, the problem is that the required AI implementation isn’t without challenges. If you decide to integrate ChatGPT with your finance software, be wary of these hurdles.
Ethical concerns
ChatGPT or other generative models aren’t perfect. They might occasionally produce inaccurate or biased results. For example, an AI credit scoring system may reject certain applicants based on demographics because of presumptions made during training. Thus, you can’t replace all decision-making with AI.
Solution:
To help ChatGPT provide more accurate responses, you need to fine-tune the model via OpenAI’s API. This way, ChatGPT will be more consistent in processing complex requests and handling edge cases. If you’re not sure how to address ethical concerns, our team of AI developers is ready to help.
Technical challenges
With API, integrating ChatGPT with finance software is much simpler. Still, for businesses without generative AI and software development capabilities, the task can prove overwhelming. From technical documentation to app testing, you’ll need to manage various aspects of development. Plus, AI implementation requires special skills like machine learning and data analysis, which not all developers are equipped with.
Solution:
You’ll need to hire a team of AI developers, UI/UX designers, backend developers, and other software specialists. Alternatively, you can engage Uptech to integrate ChatGPT with your software. This way, you don’t have to commit to long-term expenses and can focus on your core business.
Data privacy and security risks
By connecting your finance software to ChatGPT, you’re exposing customer and financial data to greater security risks. While OpenAI takes appropriate measures to safeguard your company’s data, there are risks of exposure at many other data collection and exchange points. Such risks, if not addressed, can lead to data theft that negatively affects customer’s trust.
Solution:
Before integrating ChatGPT with your finance software, conduct a security audit and determine mitigative measures. At Uptech, we employ data protection measures like encryption to ensure the data collected, stored, and processed are secured. We’re committed to eliminating security gaps that cause data risks.
Evolving AI technologies and compliance
Even as we write this, AI technologies are evolving rapidly. As ChatGPT replaces its underlying GPT model with a newer version, SMBs are pressured to do the same. Still, you must evaluate the technological changes, as well as alignment with compliance requirements, before updating your finance software. Most business owners, however, struggled to keep pace with the tasks involved.
Solution:
Be diligent in staying updated with the latest developments in generative AI, specifically ChatGPT. At the same time, constantly monitor regulatory guidelines and adapt your software implementation accordingly. Uptech’s experience in the AI and fintech space can help you remain competitive amidst fast-evolving technologies.
Conclusion
ChatGPT, with its natural language understanding, text generation, pattern analysis, and other abilities, can change how SMBs manage their finance processes. From automating data entry to personalizing portfolio recommendations, we anticipate broader applications of conversational chatbots in the finance space.
Despite the promises that ChatGPT finance integration offers, SMBs must familiarize themselves with AI integration, including the risks and challenges involved. We’ve explained the steps involved in integrating your finance solution into OpenAI’s generative AI model. And we’ve also addressed concerns that often trouble business owners.
ChatGPT, like many other technologies, will transform how SMBs operate. But it falls upon you to leverage it for your business. That, we believe, is the only way to remain competitive in the market. And we can help you with that.
Talk to our team about integrating ChatGPT with your finance systems.
FAQ
What is ChatGPT, and how does it work in the finance industry?
ChatGPT is OpenAI’s conversational chatbot. It’s powered by the GPT large language model and can innovate financing workflows in different ways. For example, you can use ChatGPT for 24/7 customer support, automate invoicing, risk management, credit scoring, and more.
What are the key benefits of integrating ChatGPT into finance software?
As a large language model, ChatGPT can converse naturally like humans and it’s also adept at analyzing volumes of data. When integrated with your finance software, you can improve customer engagement and offer personalized recommendations. Also, ChatGPT can help with other tasks that consume excessive time and effort, such as fraud detection, loan approval, and market prediction.
How do I start integrating ChatGPT into my finance software?
You need to set up the development environment, which involves signing up for OpenAI’s developer account. To integrate ChatGPT with your software, use the API key provided. It allows you to access generative AI functions, such as text generation and data analysis, which ChatGPT offers. You’ll also need to modify the finance software, including the front end and back end, so it can send requests and process the responses from ChatGPT.
Is ChatGPT secure enough to handle sensitive financial information?
ChatGPT encrypts data that your finance software sends via API., which is not enough. You’ll still need to take proactive measures to protect sensitive financial data. For example, encrypting data from the moment they’re collected, anonymizing sensitive information before sending them and enforcing a human safeguard to prevent unintended exposure.
Can ChatGPT do financial modeling?
ChatGPT is not designed for financial modeling. That said, you can use ChatGPT to assist in such efforts. For example, ChatGPT can help you structure a financial model, plan various scenarios, generate possible outcomes, and interpret modeling results.
How much does it to integrate ChatGPT into finance software?
The cost of ChatGPT integration depends on the use case, modification, UI/UX, customization, and other development tasks involved. For a basic integration and a simple use case like a financial chatbot, the cost starts at $50,000. However, SMBs might pay $150,000 or more if they require complex integrations like fraud detection, risk management, or market predictions. Check our article for a more detailed AI app development cost or contact our team for a free project estimate.