Artificial intelligence is a technology that can perform tasks that normally require human intelligence, such as understanding language, recognizing images, making decisions, and learning from data. AI has many applications in various fields, such as medicine, education, entertainment, and more. One of the fields that can benefit from AI is banking and financial services. In this article, we will explore how AI can help banks improve their customer experience, efficiency, and profitability, as well as the challenges and considerations for implementing AI into banking products and services.
AI Helps Banks Support Sustainability Transformation
AI models can work with a lot of data very fast. This makes them useful for other areas, like sustainability. Starting from 2023, banks in the European Union will have to tell which of their transactions are good for the environment.
They will follow the EU’s rules, which say which loans are green. For example, loans for making electricity from the sun or the wind are green. Loans for a medium-sized business to buy things or systems that will help it use less energy or produce less pollution are also green. To sort out the transactions, banks need new information from their business customers.
Apps of AI in Banking Examples
Customer Service and Customer Engagement
AI can make chatbots and helpers that can talk to customers anytime, help them with their questions, suggest things they might like, and make them happy. For example, Personetics is a company that uses AI to help customers and businesses with money matters.
Personetics is a company that uses AI to provide personalized guidance and insights for the financial customer journey. It helps banks understand their customers’ behavior, preferences, and needs by analyzing data from various sources, such as transactions, social media, and web browsing. It also helps banks offer tailored products and services, optimize pricing and marketing strategies, and increase customer loyalty. Capital One uses Personetics to provide personalized financial advice and offers to its customers.
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Personetics also helps banks create and manage custom content and engaging insights with a codeless management tool called Engagement Builder. This tool allows banks to define logic, customize UX, and configure calls to action for different customer segments and campaigns. It also helps banks distribute the insights across all banking channels, such as mobile, web, email, and voice.
Personetics claims its AI-powered technology can increase customer engagement by 35%, account and balance growth by 20%, and customer satisfaction by 90%. It also claims that it can reduce customer churn by 25% and call center costs by 15%. Personetics has raised $85 million in growth funding in January 2022 and plans to use the funds to expand its global presence and product offerings.
Fraud Detection and Risk Management
AI can help banks find and stop bad things like fake payments, dirty money, and hackers by looking at a lot of data, finding things that are not normal, and warning the banks. For example, Quantexa is a company that uses AI and connections between data to fight against crime with money.
Quantexa is a company that uses AI and network analytics to combat financial crime and fraud. It helps banks connect disparate data sources and form a 360-degree view of entities and their relationships. It also helps banks reduce false positives, focus on the most relevant threats, and address complex fraud typologies that simple rules cannot solve.
Quantexa also helps banks with a new solution called Syneo, which offers an all-in-one platform for monitoring and investigating financial crime and fraud. Syneo uses contextual monitoring to detect and manage the holistic financial crime and fraud risks within international trade, such as money laundering, sanctions evasion, and trade-based fraud. Syneo also automates time-intensive manual data gathering and analysis and supports investigations with visualization tools for exploration and decision-making.
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Quantexa claims its AI-powered technology can reduce case volumes by 60%, increase fraud savings by 20-30%, and reduce investigation time by 80%. It also claims it can improve customer experience and compliance by providing a single view of risk and reducing false positives by 75%. Quantexa raised $240 million in Series D funding in July 2021 and plans to use the funds to expand its global presence and product offerings.
Underwriting and Credit Scoring
AI can help banks decide if people can repay loans, make the loan process faster, and lower the chance of people not paying back loans using models that work with data, words, and images. For example, Zest AI is a company that uses AI to help lenders with loans.
Zest AI is a company that uses AI to provide better lending solutions for banks and credit unions. It helps banks assess the creditworthiness of borrowers, automate the loan approval process, and reduce the risk of default by using data-driven models, natural language processing, and computer vision.
Zest AI also helps banks build and manage their own AI models with a codeless management system called Zest Model Management System. This system allows banks to define logic, customize UX, and configure calls to action for different customer segments and campaigns. It also helps banks validate, document, and monitor their models for compliance and performance.
Zest AI claims that its AI-powered technology can increase approval rates by 20-30%, reduce charge-offs by 30-40%, and automate credit decisions by fivefold. It also claims it can improve customer experience and fairness by providing a single view of risk and reducing false positives by 75%. Zest AI has raised $85 million in growth funding in January 2022 and plans to use the funds to expand its global presence and product offerings.
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Predictive Analytics and Personalization
AI can help banks know what customers want, like, and need by looking at data from different places, such as payments, social media, and websites. This can help banks give customers what they need, have better prices and ads, and keep customers happy. For example, Capital One uses AI to give customers helpful tips and deals on money matters.
Capital One is a bank that uses AI to provide personalized financial advice and offers to its customers. It uses data from various sources, such as transactions, social media, and web browsing, to understand customer behavior, preferences, and needs. It also uses natural language processing and machine learning to generate tailored content and engaging insights for customer segments and campaigns.
Capital One also uses a chatbot called Eno, which is the first natural language SMS chatbot from a U.S. bank. Eno can interact with customers 24/7, answer their queries, provide personalized recommendations, and enhance their experience. For example, Eno can help customers pay their bills, check their balances, track their spending, and get fraud alerts.
Capital One claims that its AI-powered technology can increase customer engagement, account and balance growth, and customer satisfaction. It also claims that it can reduce customer churn and call center costs. Capital One has a history of AI innovation and was the first U.S. bank in the cloud.
Robo-advice and Wealth Management
AI can help banks give customers tips and help on how to invest and manage their money, especially those who do not have enough money or access to banks. AI can also help banks make better decisions on how to use their money and trade. For example, Wealthfront is a company that uses AI to help customers with money management.
Wealthfront is a company that uses AI to provide automated investment advice and portfolio management to its customers, especially those who are underserved or unbanked. Wealthfront requires a minimum investment of $500 and charges an annual fee of 0.25% of assets under management.
Wealthfront uses data from various sources, such as transactions, social media, and web browsing, to understand customer behavior, preferences, and needs. It also uses natural language processing and machine learning to generate tailored content and engaging insights for different customer segments and campaigns. For example, Wealthfront uses a tool called Engagement Builder to create and manage custom content and insights with a codeless management system.
Wealthfront also helps customers optimize their own asset allocation and trading strategies. It offers various services, including automated investing, retirement planning, tax-loss harvesting, and a portfolio line of credit. It also helps customers diversify their portfolios and provides efficient tax optimization strategies.
Wealthfront claims that its AI-powered technology can increase customer engagement, account and balance growth, and customer satisfaction. It also claims that it can reduce customer churn and call center costs. Wealthfront has a history of AI innovation and was the first U.S. bank in the cloud
Challenges And Considerations For Banks
AI technology can make the customer experience in banking better, but it can also have some problems. One of the main problems is keeping customer data safe and private. Banks should make sure that their chat system is safe and that no one can see or use customer data without permission.
Another problem is teaching an AI model to understand the words and terms used in banking. Banks should give good training data and connect the model with their other systems to make sure that it can give correct and suitable answers to user questions.
And one more problem is getting customers to use the chat system. Banks should make sure that customers know about the chat system and how it can help them, and that they are happy using it. This will require them to think about how to design their product better and teach customers how to use the chat system easily.
Being able to work with words and customer data means AI could be a great way to provide a more personal, fast, and easy user experience in banking and financial services.
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Artificial intelligence is a technology that can help banks improve their customer experience, efficiency, and profitability. AI can help banks with various tasks, such as loan approval, fraud detection, customer service, personalization, wealth management, and more. AI can also help banks face the challenges of the digital age, such as increasing competition, changing customer expectations, and stricter regulations. However, AI also poses some challenges for banks, such as ensuring data security and privacy, training AI models to understand banking language and terms, and encouraging customer adoption of AI-powered chat interfaces. Therefore, banks need to carefully implement AI into their products and services and leverage its potential to provide a more personalized, convenient, and satisfying user experience in banking and financial services.
