Artificial Intelligence in Banking 2020: Examples & Challenges

Introduction

Millennials and their changing preferences have led to a wide-scale disruption of daily processes in many industries and a simultaneous growth of many more in other sectors. Much like hand soaps and cereals, the use of a physical bank location has declined. Physical bank locations may soon be a thing of the past, as per a report from Business Insider.

With the customer preferences that are changing, the industries are adopting newer methods to match the pace of changing demands. Banking is digitizing as the word spreads. There is evident incorporation of operational process flows with artificial intelligence, robotics, and other machine assistance.

Technology and the fourth industrial revolution have penetrated its way into many sectors. This technology is now reconstructing social skills and the workforce. Not only limiting the existence of a changing workforce, but the use of artificial intelligence is very evident in the banking sector. Artificial intelligence applications are not just modernising the banking sector but the entire world as we know of. Read more about the top artificial intelligence applications.

Why Use AI

Technology is the face of this generation. To all the problems this generation has- there is a rising demand for answers. And, the solutions are sought after at the tip of their fingers. The other side of the screen might be a computer solving queries or a human employed as a relationship manager.

Big data is the industry standard today, and every sector is working on grasping all that it could from the repositories of unstructured data. Big data applications in banking are already transforming the industry. Here comes artificial intelligence. Not only utilizing the benefits of AI in extracting and structuring the data in hand, finance, and banking sectors are stepping in to use this data to improve customer relations.

Banking and AI

Artificial intelligence is being used in the banking industry to scale new heights in customer relationship management.

This sector is implementing this from the ground level with a principal aim of climbing heights in customer-centric approaches. A significant part of the banking industry concerning its customers is customer relationship management, which includes communicating with them.

Banking saw a shift in preferences for visiting the locations with the introduction of ATMs. These machines allow cash deposit and withdrawal directly communicating with input points on the device, thus, not requiring human assistance at all. It was a revolution that led to the growth and demand for artificial intelligence.

Digitization and Cyberthreats

Banking is evolving in terms of digitization. Net banking, mobile banking, real-time money transfers, and similar services have changed the face of the sector from the last decades. With this digitization, there is an increase in the cyberthreat that comes along.

These services again need to be secured from cybercriminal activities to ensure trust and safe transactions amongst users. With the availability of the right support, banks face difficulties in terms of the right workforce to drive the industry needs in the right direction.

When sectors like banking, telecom, and information technology come together, the world witness’s plethora of valuable user- information on the world wide web. Every report of any user is as vulnerable as it is secured. Cybercrimes lead to disruption in the practices, and hence there have been strict regulations from government bodies to improve the banking industry’s adequacy to retain this massive data it has.

Application Areas

Artificial Intelligence is working to personalize human experiences with machines. Robots replacing the front-office staff in the banking sector are aimed to provide a 24*7 uninterrupted, diligent, and undeterred expertise to the customer in front.

Banking today is witnessing a collaboration between humans and machines. This collaboration again is opening doors to customized opportunities for better service encounters and delivery.

Benefits

Restructuring reasons for the description, the following are the benefits in use:

  •         Improved service responses
  •         Reduction in human error
  •         Personalized options in the making
  •         Strengthening customer base by increasing satisfaction and trust
  •         Reducing time to travel locations

Banks are capturing the artificial intelligence by administering it into daily operational workflow by including changes in the values, employment and information patterns. Some of the application areas of artificial intelligence in the banking industry are listed as follows:

1. Refining Consumer Participation

Artificial intelligence helps understand the customers better. The data gathered from the customer’s choices and preferences enable AI to lead machines to decode the next decisions and thus create a personalized container of information for each customer.

This, in turn, is helpful for the banks to customize the buyer experiences as per their choices, in turn improving satisfaction and loyalty towards the institute.

Interactive Voice Response System (IVRS) are examples of such AI-led systems that include voice assistance to customers. It guides the customers by understanding their queries in the right direction by routing calls to the correct department as well as assisting them with the transaction and other banking-related issues in real-time.

2. Wealth Supervision

These customized plans for customers not only benefit the banks by increasing their customer-base but also helps the user to manage their wealth in hand with personalized inputs and advice on risk and investment plans. Involving AI-led customer service to meet the front office standards is a challenge with the diverse language set in countries like India.

3. Examining Data to Enhance Defence

AI has the power to foretell future trends by interpreting data from the past. This property, when associated with machine learning, will help produce data-driven predictions to counter cases of capital laundering and identifying fraud.

4. Upgrading Security

Unusual data pattern recognizing property of AI-led machines helps banks tighten security and recommend changes by identifying loopholes in existing processes. Deceptive emails and log reports, patterns in breach of process flows can be tracked by artificial intelligence to provide better security in the existing methods.

5. Interfacing Emotions

AI-led machines use technology that identifies the emotions of the customers based on the text they use to input requirements. Based on this, the devices respond, suiting the tonality and fabrication of the words used by the customer. Natural language processing helps this happens. Read more about the applications of natural language processing.

This not only a realistic experience but also helps banks save massive costs on human resources and large chunks of time.

Chatbots are examples of AI in banking that are replacing the front-desk scenes at the banks. These AI-led machines provide next level digitized and customized interactive experiences to the customers. Learn more about creating a chatbot using Python.

6. Utilizing Knowledge Database

AI-led systems in the banking sector is a massive treasury of data. It has all the details there is for every user on board. This database provides for more meticulous decision making based on improving strategic and business plan models. The AI-led repository is equivalent to a human expert on cognitive thinking.

Face-detection and real-time cameras in ATMs and other such interventions is helping banks heighten measures into security and providing a clear and crisp insight into user’s behaviour patterns and techniques in operation.

7. Controlling Risks

The vast data bank available from AI-powered systems allows the banks to manage risk by analysing their plans, studying failures from previous strategies, and eliminating human errors.

AI is expanding into the roots of banking security processes to encrypt each step with codes that authenticate transactions, provide understanding to the companies on anti-fraud and anti-money-laundering activities. Regulatory checks like Know Your Customers (KYCs) help heightens security measures.

8. Expanding Through Front-office

By offering to be personalized financial guides to customers and strengthening security against fraudulent activities, artificial intelligence is paving its path, strengthening not only in the front-office operation (customer interactions) but into the middle-office(security) and back-end development (underwriting banking service applications) as well.

Challenges Faced

1. Many banks face the challenge of an unwillingness to improve or adapt to new methods. Standardized with set practices in conventional ways, some locations in tier two and three cities across the country face this challenge. These units also lack the level of commitment required to upskill their labour force and human resources skills.

2. With the lack of supporting data to implement operational changes, the banking sector is facing a disconnect between the need and response from customers. The banks adapt to a switch that fails to comply with the actual requirement of the masses.

3. Banks with upscaling use of artificial intelligence need to keep up with the regulatory standards of government. The increasing services like net-banking and online transactions come under the ambit of privacy regulation policies as well, which necessitates compliance from the bank’s end.

4. There is also an evident lack of training witnessed in the existing workforce associating with the advanced tools and applications of the use of AI in banking. With the increasing use of artificial intelligence, there is an apparent demand for a skilled workforce. Proficient and experienced engineers in streams like data science and machine learning are needed to provide credibility to the data in hand.

Conclusion

The digital revolution is changing the functionality of every other business operating today. Just like all distinct industries that are focusing on leveraging the revolution to increase profits, banking is on the territories as well. The applications and examples present a clear picture of what is in store from the benefit’s point of the use of artificial intelligence in banking.

Their focus on scaling new heights in customer relationship improvement through digitization is rising on the progress scale. Although with challenges like cyber threats from cybercrimes, conventional banking methods, lack of training, etc., the world of banking is picturing technology-faced services into the ground level banking operations.

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Kechit Goyal

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PG DIPLOMA IN MACHINE LEARNING AND ARTIFICIAL INTELLIGENCE
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