Is AI/ML Transforming the Banking Industry

Listen on the go!

Artificial Intelligence (AI) is quite powerful and is constantly evolving and currently knows no bounds. It is focused on outperforming its limits using the power of Machine Learning (ML).

AI is empowering computers to do things that human beings are unable to do efficiently and effectively and machine learning is aiding the computers to do so by breaking the rules of traditional programming.

We are aware that AI/ML has been driving an era of automation that holds important benefits for global industries like increased productivity, and time to market as companies have started relying on technologies to optimize their internal business operations.

AI/ML also boosts creativity and innovation by automating tasks so that employees only focus on the essential part and can also handle and analyze enormous data in an unbiased manner.

In recent times AI and ML have brought exceptional changes in the banking industry as both challenger and traditional banks are growing their focus on helping consumers save money. As customers increasingly look to save money and become more fiscally responsible, many banks have reacted by providing a variety of services.

According to MicKinsey, Ai technologies could potentially deliver up to $1 trillion
of additional value each year for global banking.

Traditionally, banks have been providing services for basic budgeting apps or digital tools, but with the inclusion of AI, banks are now able to deploy to help segment different payments.

With AI, they can now provide suggestions to customers based on payment history, offer a source of advice, and a resource for answering common customer queries via chatbots.

Artificial intelligence in banking is used to establish meaningful conversations with customers by solving real problems and managing finances.

AI to support customer interactions

Customers and banks are not realizing their full saving potential because banks are generally still learning to understand their customer’s needs. Banks that are still running on legacy systems may struggle to complete complex transactions beyond money transfers and deposits in the future.

AI will allow banks to focus on their customers by leveraging the data that they own to gain essential insights. This will in turn allow banks to personalize and enhance the customer journey, making it as frictionless as possible by manipulating the data to offer real-time recommendations.

In more than 25 use cases, AI technologies can help the banking industry increase revenues by providing customers (and employees) with more individualized services, and reducing costs through increased automation.

AI can help banks reduce error rates, better resource utilization, and uncover new and untapped business opportunities thanks to an improved capacity for processing and drawing insights from massive amounts of data.

Even elderly customers, who may not be as tech-savvy will be able to process their banking transactions quickly and easily via a smooth online experience. AI can be used to create a smarter and more personalized user experience.

For instance, it can be used to track data such as a customer’s spending and purchase history over some time to help the bank send relevant information regarding budgeting and saving. By offering customers an individualized service, the bank can increase customer satisfaction and retention, creating mutual value for the customer and the bank.

Successful AI applications in banking need to put to good use huge volumes of data collected via ATMs, web channels, digital wallets, point-of-sale activity, or mobile devices, regardless of how it was collected.

A tailored approach

In order to provide a sustainable high level of customer engagement, banks need to gain full visibility of a customer’s history to understand their personal banking habits and needs.

Banks, therefore require an integrated enterprise system that consolidates customer data from all sources, from apps and APIs to third parties, which can then use AI to provide real-time recommendations to increase loyalty, retention, and value. This combination of AI and omnichannel decision-making making can add value to the overall customer experience.

Real-time transaction analysis is crucial not just for fraud detection but also enables banks to collate data and track transactions at low latency. This would enable banks to know their customers better and would also give them the dataset required to apply AI and deep learning to provide personalized, value-added products to customers as it learns about spending habits over time.

With all this information, banks can now deliver curated financial services and advice better than ever before with the help of AI-based decision-making. By tapping into customer profiles and preferences, banks can package products and services together based on personalized needs.

There are many products that are integrated with banks to help customers choose the best mortgage loan-providing bank. This could enable the banks to develop more products affiliated with greater customer loyalty and lifetime value for customers.

Whereas customers can benefit from the convenience of working with a trusted organization that understands their personal requirements. As the adoption of AI-based decision-making tools grows, relationship managers will be able to more accurately and consistently assist a customer with the best products and services for managing personal finances.

Banks will be able to model and implement process optimization across all of their physical, web, digital, and mobile channels using AI, allowing them to better serve consumers and create a better customer experience.

Using conversational AI chatbots to help customers

AI-driven virtual assistants or chatbots are able to respond to customers’ simple banking needs. From identifying funds in a customer’s cash flow that can be automatically moved to a savings account, and alerting customers to any unusual activity in their accounts, to providing personalized financial management insights and advice.

This can ultimately help banks expedite workflow, reduce the volume of customer calls coming into the call center, and improve customer service.

Chatbots have progressed to the point where they can mimic human intellect. As a result, they can provide an emotionally engaging experience for customers who are making life-changing decisions.

Using AI  in  ATMs 

Banking customers depend on ATMs but like any mechanical device, they can break down. Artificial Intelligence can help to create an individual ATM’s personality and determine when it needs maintenance. Here’s how.

The ATM is considered a stalwart of the banking experience as it is always there, always on, and always ready to dispense cash. Like any electromechanical device, an ATM can break down, go dark, and maybe even fail permanently.

As ATMs in the field get older, maintenance becomes more important. Rich Johnston, head of service technology and innovation at Diebold Nixdorf, once said in an interview that financial institutions (FIs) need to manage the technical data about individual machines to see where attention must be paid.

Being proactive about maintenance and upkeep by banks can save headaches and costs down the line — and advanced technologies such as machine learning and artificial intelligence can play an important role in that proactivity, addressing pain points in new ways.

Financial institutions need to leverage advanced technologies to determine the technical information about ATMs, and the stressors they encounter in terms of weather or usage difference(s) based on ATM location.

Not only may data from ATMs assist the financial institution in customizing ATMs to provide increased services to customers, but it could also assist the financial institution in customizing ATMs to provide enhanced services to consumers.

As we have been seeing that reliance on branch visits and tellers is diminishing the reliance on ATMs is going up and the FI is ever more reliant on the machine to keep banking relationships sticky and loyal.

Moving towards mobile

There’s been a continued blending of mobile technologies and mobile interactivity with the physical cash world. Moving towards a mobile ATM would eliminate the need to swipe or insert a card with biometrics as an added layer of security.

The risks of skimming could be greatly decreased if there is a relationship between a mobile device and the physical piece of hardware that is supplying the money.

What we’re talking about here is “driving availability, uptime, and an experience to ensure that whenever a consumer goes up to a machine, it’s up, live, and running”.

Conclusion

After integrating AI into the workplace, the banking industry has seen enormous changes. The bank will save money by using AI to reduce costs. Banking organizations will become more powerful if they update their digital workflow with the customers in mind first and increase their adoption of AI platforms.

In addition to empowering banks by automating their knowledge workers, AI will make the entire automation process smart enough to eliminate cybersecurity issues and competition from FinTech competitors. AI, which is essential to the bank’s operations and processes, keeps innovating over time without a lot of manual work.

Speak with our AI specialists if you’re seeking AI development services for your banking organization. To know how we can assist you in developing and implementing a long-term AI in banking strategy, take a look at our AI/ML services.

Author

  • Cigniti Technologies

    Cigniti is the world’s leading AI & IP-led Digital Assurance and Digital Engineering services company with offices in India, the USA, Canada, the UK, the UAE, Australia, South Africa, the Czech Republic, and Singapore. We help companies accelerate their digital transformation journey across various stages of digital adoption and help them achieve market leadership.

Leave a Reply

Your email address will not be published.