12 benefits of fintech AI chatbots: Don’t get left behind in the revolution of AI in finance
The impact of AI on the fintech industry
Artificial intelligence (AI) has transformed entire industries, changing how people work and play. Specifically, AI in finance spans various business functions, from customer service to fraud detection. Fintech AI enables banks and other financial institutions to detect fraud, automate processes, and cut costs, among other perks.
According to management consulting firm McKinsey, fintech AI could deliver up to $1 trillion in additional value for banks each year. Not only does it have the potential to drive efficiency and growth, but it can also uncover new opportunities.
For example, the UK's National Westminster Bank allows people to open accounts remotely by taking a selfie. The company uses AI-powered biometrics to match selfies to ID card photos. Goldman Sachs, Capital One, and Ally Financial leverage AI to streamline customer service and support operations.
AI in finance can also be a game-changer for fintech startups and small- to medium-sized businesses (SMBs). As an entrepreneur, you can use this technology to personalize the user experience, enable transparency and compliance, improve data security, and mitigate risk.
How to get started with AI in finance
Banks and financial institutions can use AI to drive innovation and streamline their operations.
For example, about 70% of financial services firms rely on machine learning, a form of AI, for credit risk modeling, cash flow forecasting, fraud detection, and other operations. Approximately 60% use Natural Language Processing (NLP), a component of AI, to improve underwriting, spot errors in documents, and search for specific records in datasets.
Other AI technologies, such as computer vision and deep learning, can streamline wealth management, decision-making, data security, and reporting.
However, you don't have to be a billion-dollar corporation to tap into the power of AI. SMBs can use this technology to make data-driven decisions, improve their products and services, and automate manual tasks. This allows them to compete on a level playing field with major banks and meet customer expectations.
The first step to getting started with fintech AI is understanding how it works. After that, you must assess your needs and determine which AI tools and technologies will work for your business.
Take generative AI, for example. This technology uses neural networks to analyze existing data and create new content based on it.
Financial institutions can leverage generative AI for:
Market analysis and forecasting
Financial simulations
Portfolio management
Fraud detection
Risk assessment
Credit scoring
Customer support
Wealth management
For instance, generative AI can simulate financial scenarios to assess risk. These insights allow users to analyze the likelihood of certain events, such as market crashes and surges.
AI-powered chatbots, on the other hand, can assist with customer onboarding and support. They can also monitor customers' accounts and detect fraudulent activities, such as money laundering, mitigating risk for both parties.
The tools required to implement these technologies range from basic to advanced.
For example, a fintech startup may use ChatGPT to analyze data, create reports, predict future trends, and so on. Large enterprises usually use more sophisticated tools or create AI software.
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How is AI in finance useful? Use cases of fintech AI
AI and digital transformation go hand in hand. Therefore, it's not surprising that digitally-driven companies were the first to embrace generative AI, machine learning, and similar technologies.
Today, financial institutions are deploying AI solutions in key business areas, including:
Automation
Fraud and risk management
Regulatory compliance
Business growth and development
Customer service
Product personalization
Now let's take a closer look at the main use cases for AI in finance.
Credit decisions
Most banks use AI to assess borrowers' ability to repay when applying for loans, mortgages, and credit cards. AI-based tools can process massive amounts of data in minutes, extracting relevant information and identifying patterns. These insights allow lenders to calculate credit scores, analyze credit risk, and determine whether to approve or decline loan applications.
Fintech AI can also reduce bias in credit scoring and ensure consistency in lending decisions. As a result, it allows for more accurate assessments. At the same time, it eliminates or reduces the need to manually collect information and review customer profiles.
Fraud detection
AI technologies can leverage Natural Language Understanding (NLU) to detect fraud in real-time.
For example, some chatbots monitor customers' accounts to identify suspicious activity and alert the bank about it. Others can monitor user transactions for patterns and anomalies, such as payments to accounts in high-risk countries.
Risk management
Machine learning algorithms can analyze market data, cash flow data, funding sources, liquidity metrics, and other factors to help banks mitigate risks. This subset of AI can automatically identify trends, correlations, and anomalies that may impact the bank's investment portfolio or trading activities.
Financial institutions also use ML to predict and plan for potential liquidity shortfalls. Moreover, this technology can detect operational risks related to internal processes, technology failures, or human errors, allowing banks to protect their systems and clients.
Customer service
Conversational AI chatbots can streamline customer service and enhance the user experience. These smart bots can answer common questions, find solutions, and assist users with account-related operations.
Capital One and other banks have developed their own chatbots to optimize the customer experience. The bots can provide users with detailed information about the bank's products and services, send real-time transaction alerts, and act as financial advisors.
For example, some AI chatbots help customers track their expenses, set savings goals, and apply for loans or credit cards. Others can handle customer complaints and direct them to human agents when necessary, driving operational efficiency.
Financial advisory services
AI models can assess customers' risk tolerance, financial goals, investment preferences, and other factors through questionnaires and data analysis. This information allows them to make personalized recommendations and optimize investment returns.
The latest AI apps use deep-learning technology to help customers manage their finances, stay on top of their bills, and cut unnecessary expenses. Some can even offer insurance or tax tips and alert users when they're close to exceeding their budget.
These recommendations are tailored to each client's financial situation, taking into account their income, debts, expenses, and other factors. Additionally, AI continuously monitors financial markets so it can provide real-time insights.
Personalized banking experiences
Nearly 80% of consumers expect personalized support from their banks. AI can help financial services firms personalize their offers and recommendations to meet customers' needs.
For instance, banks can leverage generative AI to deliver personalized financial content, including articles, guides, videos, and reports. Virtual assistants and other AI apps can alert users about upcoming bills, potential overdrafts, or low balances to help them organize their finances.
Pro tip: Check out Sendbird's new chatbot demo powered by ChatGPT to see generative AI in action. The bot generates personalized and intelligent responses, fostering customer loyalty and engagement.
Marketing teams can use this technology to customize their campaigns, upsell or cross-sell banking products and services, and make relevant offers based on customer preferences. These AI models can continuously learn from data, allowing for a high degree of personalization.
Internal operations
Another use of AI in finance and banking relates to internal operations, such as employee onboarding and compliance reporting. Chatbots and other AI-powered tools can assist financial advisors, marketing teams, and other employees, leading to higher efficiency across the board.
For example, some AI systems have built-in tools that can automate the approval process for internal documents and requests, reducing manual work. This aspect alone can free up employees' time and prevent human error.
Most banks also use AI to monitor their servers and ATMs so they can detect potential failures and minimize downtime. On a similar note, AI can identify and address cybersecurity incidents in real time, protecting financial data from threats.
ChatGPT and other AI apps can streamline cross-team collaboration, marketing, sales, and other internal processes. The result? Time and cost savings, increased productivity, and higher profits.
5 examples of fintech AI
Wells Fargo, J.P. Morgan Chase, Merrill Lynch, and other banks leverage fintech AI to prevent credit card fraud, detect cybersecurity threats, and automate routine tasks. The same goes for fintech companies, which use this technology to improve their products and services.
Now let's take a look at some real-world examples of AI in the financial services industry.
Capital One
Capital One’s data scientists developed a virtual assistant to help customers stay on top of their finances. Eno can generate virtual card numbers, chat live, answer questions, and assist users around the clock.
The bank also uses AI and machine learning to optimize KYC (Know Your Customer) operations, automate incident management, and fight money laundering. This allows it to secure customer data and discover potential issues before it's too late.
J.P. Morgan Chase
J.P. Morgan Chase has invested billions in data science, making it the first major bank to launch a virtual assistant for business clients. The bot can assist customers with their transactions and simplify complex operations, such as stock and securities trading.
However, the company has been using artificial intelligence for years to prevent fraud, analyze data, and streamline customer service. Its employees use an in-house platform that allows them to run and manage ML/AI applications at scale.
Simudyne
Simudyne's AI-powered platform enables financial institutions to simulate unlimited scenarios. Once the simulation is ready, companies can use it to run experiments and What are push notifications? the waters. After that, they analyze the results to see how different decisions or changes would impact their operations.
AI simulations allow users to What are push notifications? new ideas in a low-risk virtual environment. As a result, they can streamline risk management, unleash innovation, and reduce unnecessary expenses.
ABN Amro Bank
The Netherlands’ ABN Amro Bank uses a conversational AI chatbot to assist customers. Anna can handle client inquiries, initiate conversations, send notifications, and answer questions related to the bank's products and services.
The company also leverages blockchain technology and generative AI to improve its operations. AI, in particular, allows it to automate customer relationship management, fraud detection, credit decisions, and other manual processes.
Zest AI
Founded in 2009, Zest AI uses artificial intelligence and machine learning to power lending decisions. Its services appeal to banks, credit unions, private lenders, and other companies in the financial sector.
Traditional credit underwriting takes into account a customer's income, payment behavior, credit history, and related factors. Therefore, it's often biased and flawed. For example, just because someone has no credit history doesn't mean they can't repay a loan.
Zest pulls data from alternative sources, such as a customer's employment history and childcare payments, to help lenders make fair decisions. Its ability to analyze thousands of data points and turn them into actionable insights wouldn't be possible without AI.
12 benefits of financial or fintech AI
By now, you should better understand how AI in finance can benefit fintech companies and their clients. Not only does this technology streamline tedious tasks, but it can also drive business value and growth.
For example, Sendbird's new generative AI knowledge bot can assist your customers around the clock. Powered by ChatGPT, it can carry out natural conversations just like a human agent and answer questions on various business topics.
Fintech AI systems can also generate code, delegate tasks, and make custom recommendations. Plus, they integrate flawlessly with existing processes, such as customer relationship management software, and have a wide range of applications.
With that in mind, here are 12 key benefits of fintech AI:
Turn unstructured data into business intelligence
Generate financial statements and statutory reports in a smaller amount of time
Predict and address security events before they escalate
Reduce labor costs and boost operational efficiency
Enable 24/7 customer interactions
Make unbiased underwriting decisions
Detect and prevent financial fraud
Offer personalized financial advice and solutions
Automate KYC procedures and other compliance tasks
Improve transaction security
Reduce operational costs
Enhance customer satisfaction
In a survey conducted by The Economist, 46% of banks agreed that AI could help them achieve their business goals "to a great extent."
Nearly 60% said they use this technology heavily to prevent fraud, and 54% leverage its potential to optimize their IT operations. Others reported using AI to streamline digital marketing, credit scoring, risk assessments, and other processes.
But that's not all.
AI models can also pave the path to smarter investment initiatives for both financial services firms and their clients.
These systems are able to process large amounts of financial data in minutes, allowing investors to capitalize on opportunities as they arise. At the same time, AI can mitigate investment risk and help improve portfolio performance.
Getting started with fintech AI chatbots
Some AI systems are difficult to set up and manage, but that's not the case with Sendbird’s ChatGPT-powered chatbots. Sendbird, an in-app communications API company, offers a proven way for developers to integrate chat into their apps in a matter of hours.
Before starting a proof-of-concept (POC), you can build your own AI knowledge chatbot demo with no code. Sendbrid’s AI chatbot demo allows you to feed information to your SmartAssistant. Submit your email and the URL you’d like the bot to scrape, and ask the chatbot any questions related to the content on that page. Check out this tutorial for more information!
Once these steps are completed, you’ll experience the power of generative AI prompted by your content. The Sendbird SmartAssistant demo aims to demonstrate the value of conversational AI in relation to specific financial topics, such as credit scoring, budgeting, or wealth management.
SmartAssistant also includes additional features for control and data retrieval, such as:
Pre-scripted answers
Third-party system data retrieval (aka function calling)
Ready to give it a try? Here’s how to quickly start a POC:
Download our sample code for our JS website chatbot widget or iOS and Android chatbot channel integrations
Check out our step-by-step tutorials for detailed instructions
Start a free trial and create a SmartAssistant from the Sendbird dashboard with no code
Contact us to share your needs and requirements with our product managers and engineers, or visit our community site
With Sendbird’s new generative AI chatbots, the future of fintech AI is within your reach. Embrace this technology to optimize your products and services, automate tedious tasks, and personalize the banking experience across all devices and channels.
Happy fintech AI chatbot building! ⭐️
