How ChatGPT works in the Banking Industry: A Case Study

Priya Bawa

She has started her career as a Content Writer and writes on blogs related to career.

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You've probably heard other bankers mention ChatGPT. This Intelligence-powered digital assistant, known officially as "generative AI," has taken the banking and societal worlds by storm. In three months, it has grown into the key tool for many bankers, assisting banks in being more efficient across the board. Our Spark innovation working group has been experimenting with the technology for several months, and this post describes how we utilise it to increase our productivity by 20%. Boost your Skills by learning: Digital Marketing
Table of Content:
1) What Is GPT Chat?
2) ChatGPT's Future in Banking
3) ChatGPT Case Studies in the Banking Sector
4) How Much Does ChatGPT Cost for a Bank?

What Is GPT Chat?

OpenAI's Chat GPT is a sophisticated language model. It generates human-like replies to user questions and inputs using powerful machine-learning techniques.

Source: Safalta

Chat GPT is a language model that can perform a variety of language-related tasks. Language translation, question responding, and content production are a few examples. It was trained on a massive amount of textual material. As a result, Chat Open AI can respond to numerous inquiries in an accurate and contextually appropriate manner. Chat GPT is used in a variety of applications including chatbots, virtual assistants, and content production tools.
ChatGPT's Future in Banking:
As the financial services sector increasingly depends on AI, ChatGPT has the potential to transform the business. AI in financial services can deliver personalized financial advice and help because of its capacity to analyze massive volumes of data. It may assist banks and financial organizations in better serving their customers. According to some estimates, by 2025, AI will have a market value of more than $20 billion in the banking industry alone. Chatbots and virtual assistants driven by AI and Machine Learning technologies, such as ChatGPT, will play an important part in this expansion. They will provide an improved user experience for clients while lowering expenses for banking institutions.
ChatGPT Case Studies in the Banking Sector:
1) Asset Management:
ChatGPT can help banks provide personalized wealth management services to their consumers by analyzing customer data and making tailored investment recommendations based on their unique financial objectives and risk tolerance.
2) Financial Preparation:
A lot of customers rely on banks to provide services related to financial planning, which is another fantastic opportunity for ChatGPT. The concept may be used by banks to deliver personalized financial planning services such as budgeting, managing debts, and retirement planning.
3) AML and KYC:
Banks must use Know Your Customer (KYC) and Anti-Money Laundering (AML) systems to reduce financial crime risks and maintain compliance with regulations. By analyzing vast volumes of client data, including personal information and transaction history, and spotting possible compliance concerns, ChatGPT can aid banks in automating these operations. It may also authenticate a customer's identification, compare them to sanction lists, and flag questionable transactions. This decreases the possibility of mistakes and enhances the precision of compliance checks.
4) Management of Risk:
ChatGPT can assist banks in discovering and managing potential problems by assessing massive amounts of data and recognizing potential risk indicators. ChatGPT may also be used by banks to monitor transaction activity, flag questionable transactions, and detect possible fraud. The model may also predict possible economic and political risks that may affect the bank's operations by analyzing market data and news. Banks can continuously learn from previous risks and enhance risk management procedures with ChatGPT's machine learning capabilities.
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How Much Does ChatGPT Cost for a Bank?
To get began, bankers should utilize the trial edition for personal use before upgrading to one of the commercial subscriptions, which are now $42 per month. The professional version is always accessible and significantly quicker. There are a range of professional models available for bank usage that are quicker and more sophisticated than the freemium version and are meant to be exploited via an API and implemented inside a product.

Because pricing is dependent on usage, banking applications built on ChatGPT are extremely economical for any size bank. Pricing is based on 1,000 "token" increments, with each token representing a certain quantity of data. In the case of text, for example, 1,000 tokens equal 750 words. Bankers can sign up for a "Playground," which is a sandbox for the creation of applications. Bankers can use this page to get a calculator that will show the cost of the app's installation. To put this in context, developing an app that automatically pleasantly responds to every comment submitted on Google AND Yelp would cost the typical bank roughly $900 per year.
The Chat GPT from OpenAI is a complex language model. It uses strong machine-learning algorithms to produce human-like responses to user inquiries and inputs. Chat GPT is a language model that can handle a range of linguistic problems. Some examples include language translation, question answering, and content creation. It was honed using a vast amount of textual data. As a consequence, Chat Open AI can accurately and contextually answer to a wide range of enquiries. Chat GPT is used in a wide range of applications like as chatbots, virtual assistants, and content creation tools.

Read More: Human-AI Collaboration in Content Creation

What are the applications of ChatGPT in the banking industry?

You may use ChatGPT to create a question-and-answer system for financial data. You may ask it questions such, "What was the total revenue last quarter?" or "What is the trend in operating expenses?" and it will respond with answers based on the data it has been trained on, offering rapid and precise insights.

What impact does ChatGPT have on the banking industry?

Because of its artificial intelligence, complex language model, and big database, ChatGPT can help a variety of enterprises, including banking. Customer assistance, fraud detection, risk management, customization, and marketing are just a few of the ways ChatGPT may aid the banking and financial sector.

What is an example of a banking chatbot?

Consider Bank of America's hybrid chatbot Erica, which speaks to over 1.5 million banking clients every day, or Capital One, which allows consumers to access their bank accounts via the intelligent chatbot Alexa.

What is ChatGPT's future in finance?

ChatGPT's future in finance looks bright, with potential future developments including the incorporation of more advanced machine learning algorithms, the use of natural language processing (NLP) to automate customer service interactions, compliance and regulatory reporting automation, and integration with other technologies.

Can ChatGPT be used to evaluate credit risk?

ChatGPT excels in data analysis, analysing financial ratios, detecting patterns, and identifying possible credit problems with ease. Financial experts can save time and assure more accurate evaluations by automating this procedure.

What role does ChatGPT play in risk management?

ChatGPT may be used by risk managers as a virtual assistant to aid with scenario analysis, forecasting, and identifying new hazards. The automated features of ChatGPT can help improve operational performance by allowing risk management professionals to focus on more strategic and valuable duties.

What are the three most frequent financial tools?

Horizontal analysis, vertical analysis, and ratios analysis are the three primary instruments for financial statement analysis.

Who designed ChatGPT?

OpenAI, OpenAI, an AI research company, developed ChatGPT. It began as a nonprofit organisation in 2015 but transitioned to a for-profit entity in 2019. Sam Altman, who also co-founded the firm, is its CEO. ChatGPT was offered as a free "research preview" by OpenAI in November 2022.

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