5 Use Case of AI in Banking

Use Cases of ai in banking

With the rise of next-gen technology, fluctuating business needs, and ever evolving customer demands, the IT sector is always moving and always changing. What were once tropes of the Sci-fi genre are today’s reality. From AI and ML to IoT, the world is quickly becoming more and more technology dependent. Most major industries nowadays employ one such technology to elevate their business processes and improve their revenues. Looking at these adoptions, some stick out more than the rest; some feel like a match made in heaven. And one such union is of AI and Banking.  

Recent years have seen a rapid increase in disruptive technologies like AI and ML in the leading sectors of the global market. Specifically, the finance and banking industry has seen a steep rise in the use of AI applications and custom software solutions to enhance their baking operations. 

Whether we talk about Robo advising, portfolio management, facial and voice-recognition solutions, or even personal finance assistants, AI use cases in banking have always been a trending aspect. But, what does the future hold for AI in banking? 

As per many media debates, artificial intelligence has today become a game-changer for the finance and banking industry. From examining millions of data points to predicting future patterns and creating conversation platforms for customers, AI is helping banks change how they operate. And in this blog, we will talk about some of the key use cases of AI in banking.  

Top 5 Use Case of AI in Banking

1. Cost Reduction in Banking Operations

2. AI in Risk Management

3. Credit Scoring

4. Custom Chatbots

5. AI-Powered Fraud Detection Solution

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1. Cost Reduction in Banking Operations

The biggest use case of AI in banking is for cost reduction. We all know that banks heavily rely on capital optimization to earn greater profitability. So, AI algorithms can be used in banks to handle large quantities of data and increase the efficiency of complex mathematical calculations.  

Apart from that, machine learning solutions could also be deployed in the banks to find the best combination of the initial margin for different traders based on their previous transactions. Today, many banks are even using AI-based custom banking solutions for back-testing to understand different market models that lead to better decision-making capabilities.

2. AI in Risk Management

Artificial intelligence has made a profound impact in leading finance and banking agencies’ risk management departments in the past few years. Robust technologies like big data and machine learning, and AI-powered solutions, are today being used by most big banks to strengthen their risk management strategies.  

Apart from portfolio management, custom AI assistants are being deployed to make more effective and informed trading decisions. Furthermore, many banks are also leveraging AI applications to detect new trends and profitable trades that are difficult for humans to detect easily.  

All in all, AI in risk management, has been a great asset for banks, helping them make safer investment choices, thus significantly reducing losses and boosting revenues. 

AI based Risk Management

3. Credit Scoring

Another popular use case of AI in banking is credit scoring. Today, with the use of custom AI solutions, banks can significantly optimize front-office functions like credit scoring and insurance based on AI algorithms’ critical data. With AI-powered credit scoring tools, the banks can speed up their lending processes and simultaneously reduce the lending process’s risks.  

Historically, the banks used the user’s payment record for issuing the credit score. However, today, with the increased usage of AI in banking, most of the leading banks look for additional data like social media groups, mobile phone activities, and much more to get more accurate information on credit score.  

Leveraging all such robust AI applications helps the banks and finance agencies enable faster and cheaper credit scoring and provide quality and profitable loans to many audiences.   

4. Custom Chatbots

A chatbot is not a new term in the banking sector; instead, it has gained much momentum since its inception. Today, many of the leading banking and finance agencies are investing in chatbot development services to build customer facing chatbots for their organizations. 

With the use of machine learning and advanced NLP(Natural Language Processing), Chatbots can imitate human behavior to a great extent. In fact, they can easily understand the actual meaning of the messages and can offer the best solutions to customer inquiries.  

However, that’s not all! 

Today, with more AI and ML advancements, many leading banks are using chatbots that, when connected with any payment system, could analyze the accounts of the users and help them save money. For instance, if a user is looking to invest in a financial plan, your bank would offer them the most suitable investment plan with sophisticated ML algorithms and AI applications.

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5. AI-Powered Fraud Detection Solution

Lastly, we have fraud detection systems that are a key aspect of the banking and finance sector. As per a report, almost 1% of the global financial flows are either seized or frozen. Moreover, around 5% of the global GDP is from money laundering! That’s a huge amount when seen in actual currency. So, to stop such fraudulent acts, AI in banking came into existence! 

Many of the leading banks and even government agencies today are actively using custom fraud detection systems to locate and flag suspicious transactions and eliminate fraudulent transactions and claims. With smart ML algorithms, you can enable any system to learn what is actual fraud, and thus with time, the system becomes smarter and smarter.  

A popular example of this AI use case in banking is Mastercard, which introduced Decision Intelligence as one of its top security techniques. The system uses ML algorithms to analyze the user’s shopping patterns and detect any possible fraud or theft from the account.

Ai based fraud detection s

Final Takeaway!

In today’s digital era, change is the only constant. Whether we talk about the core banking operations, customer needs, or even the banks’ security, robust technologies like AI, they are today needed to cater to every need of your banking agency. In this blog, we have already mentioned the top 5 use cases of AI in banking that are all set to revolutionize the banking and finance sector. But it’s impossible to predict what amazing new vistas the future holds. 

Hence, we always recommend you stay updated and follow the trend to make the best use of technology to outperform your competitor and make your brand a hit in the finance market. Got more questions? Whether you want to know more or would like to start your digital transformation journey, we are always here to help you!  

We offer top-notch AI development services to banking and financial businesses big and small. Matellio have years of experience providing cost-effective and scalable services to banks around the globe. We house a team of seasoned experts who can help you take your AI-based custom banking solution to new heights. Reach out us today to discuss your next big idea. Also, get a free expert consultation after filling our form. 

Till then, Happy Reading! 

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