How Artificial Intelligence Makes a Difference for Banking Institutions and Customers

Just about everybody is already hooked on to technology, from businesses to homes, everyone is looking to automate processes so they can make work and life easier. In fact, technology is slowly banishing the traditional way of doing things and rapidly taking over. In order for businesses to realize the maximum profit, it is important that transformation strategies be put in place to take advantage of technology.

Fortunately, technology is doing great in just about any sector you can think about – at least for the purposes of easing growth. The banking sector is regarded as one to benefit the most out of deploying Artificial Intelligence (AI) systems. In fact, the industry is likely going to realize savings of more than $1 trillion by 2030.

Listening to bank executives in the last few years, this is certainly an exciting period for financial institutions as they start considering using AI-based solutions to solve traditional banking problems. One common use of AI in the financial industry is the calculation of home values and interest rates. Through intelligent software, banks can quickly sift through past pricing charts and come up with a model that correctly predicts the financial future in consideration of plenty of factors.

Some of the factors analyzed include the demand for certain products, price fluctuations of diverse investment tools, and the geographical location of financial decision-making customers. Others include the investor preferences in terms of post-trade allocation, identifying trade patterns likely to shape prices and price volatility on the open exchange, and the relative cost of services and goods in diverse markets.

In addition, AI is also helping in cutting down repetitive tasks. Below are a few other areas AI technology is likely to benefit banking institutions and their customers.

Customized Customer Service and Chatbots

Many financial institutions wrongly believe that increased automation will lead to reduced loyalty – something attributed to the lack of personal contact. Conversely, AI usage does not really translate to less personal services. In fact, AI in banks helps increase efficiency, improve customer satisfaction, as well as maintain loyalty in numerous ways.

For instance, some banks have an AI tool that offers financial guidance to their customers via text and voice messages. Such a service is accessible at any time of the day and can carry out simple daily transactions. Such intelligent systems allow customers to gain access from wherever they are, without the added cost of hiring more customer service staff for the bank.

The software can also track transactional details and other sources of data to help an institution understand their customer preferences and behavior for better interaction experiences. Today, banks understand the importance of increasing and accelerating customer interaction. This is why many of them are willing to launch their own mobile banking apps.

The apps are mainly used for helping make customer contact easier, while bringing in new customers, in particular millennials. Such AI-based solutions show that banks are on the lookout for new, creative means of personalizing the customer experience and understanding customer behavior.

Process Automation

One of the main driving forces behind the automation in financial institutions is process automation where AI products can perform complex automation. For example, some tools are capable of extracting data from documents in lesser time than it takes a human. Without automation, reviewing 12,000 documents would take up to 360,000 man-hours, but AI takes only a few seconds.

Other solutions are capable of recognizing and extracting critical data from lease agreements, loan applications, receipts, and W-4 forms, saving employees and customers thousands of hours. These tools also help reduce time spent on recording or reading customer information. Instead, time is better utilized taking on revenue-generating jobs.

Helps in Money-Laundering and Fraud Prevention

One of the biggest challenges for financial organizations is the detection and prevention of money laundering and fraud. AI has the capacity to help banking institutions achieve more efficiency in the course of identifying such cases. For fast identification of fraud cases, AI developers have tools and systems that compress and sift through data in seconds that would otherwise have taken hours in the past.

Bigger organizations are more likely to update traditional systems considering the increased number of fintech firms adopting AI. For example, Bankingly – Banking Software already implements big data and machine learning to stop criminal activities as well as monitoring potential threats to institutions and their customers.

Streamline Compliance Tasks

AI tools play a critical role in regulatory and compliance in the financial industry. In order for banking institutions and their customers to gain value, AI needs to be a major component to creating a secure digital backbone. In addition, the data collected for the purposes of analysis should be anonymous.

General Data Protection Regulation (GDPR) and similar laws involve firms been open with how they make use of records collected from their customers. AI tools help streamline this critical process by wiping personal identifying information from the data stored; at the same time, automating the reporting process.

From the customer’s endpoint, the most significant change is likely going to be the types of increased account protections implemented. The extrapolative investigative technology used for mining data storerooms for the creation of actionable monetary decisions will also take note of irregularities.

In other words, as AI mines data, it gets better at identifying issues and alerting users in case something is askew with their financial records. Your banking customers stand to gain the most benefits from using AI technology, just as you are as a financial institution.

Conclusion

In the past, AI was mainly associated with video gaming, but the banking sector is fast realizing that this technology can accomplish more. For decades, banks have been collecting information from their customer, without an effective way of analyzing it until now.

In addition, IoT set up at standard teller stations are helping banks recognize behavioral patterns of their depositing and withdrawing customers. With the implementation of AI solutions, the data collected can help reduce cash crunch risks due to massive demands for withdrawal demands at a single bank branch.