Editorial Notes

[Editorial Notes] Artificial Intelligence in Banking sector

AI will not only empower banks by automating its knowledge workforce, but it will also make the whole process of automation intelligent enough to do away with cyber risks and competition from FinTech players.
By IASToppers
July 11, 2020

Contents:

  • Introduction
  • Need for AI in banks
  • Advantages of AI
  • AI-driven future

Artificial Intelligence in Banking sector

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Introduction:

The Indian Institute of Technology (IIT) Roorkee has announced the first-ever course in India on AI in the banking programme, in collaboration with WileyNXT. The four-month programme will focus on training IT professionals and graduates to implement Artificial Intelligence (AI) in the banking sector. The aim of the course is to make the learner understand the role of AI in banking and financial domains.

Need for AI in banks:

  • The global pandemic has seen a movement towards digital and virtual platforms and the banking sector is shifting towards contactless banking.
  • It will encompass the processes such as digital onboarding of customers enabled by video KYC (know-your-customer), contactless authentication and payments, virtual customer servicing, and immersive banking experience.
  • Artificial Intelligence will be highly used to develop interactive banking-customer experience.
  • The growing security and privacy concerns have reinforced the need for leveraging new-age skills to tackle emerging challenges.
  • As per the 2019 RBI annual report, losses due to banking frauds have risen by a whopping 73.8% despite the Government’s efforts to curb them.
  • With the adoption of real-time payments, there has also been rapid innovation in the digital fraud landscape.
  • Considering RBI’s zero-liability safety net in the event of cyber frauds, it is imperative banks adopt best-fit practices and technology to mitigate these risks and enable advanced and adaptive real-time monitoring of their payment networks.

Advantages of AI:

1. Enhanced customer experience:

  • Based on past interactions, AI develops a better understanding of customers and their behaviour.
  • This enables banks to customize financial products and services by adding personalized features and intuitive interactions to deliver meaningful customer engagement and build strong relationships with their customers.

2. Prediction of future outcomes and trends:

  • With its power to predict future scenarios by analyzing past behaviours, AI helps banks predict future outcomes and trends.
  • This helps banks to identify fraud, detect anti-money laundering pattern and make customer recommendations.
  • With its power of Machine Learning and Cognition, AI identifies hidden actions and can detect suspicious data patterns among humungous volumes of data to carry out fraud management.
  • AI studies past to predict the future behaviour of data points, which helps banks to successfully up-sell and cross-sell.

3. Cognitive process automation:

  • This feature enables automation of a variety of information-intensive, costly and error-prone banking services like claims management.
  • This secures Return on Investment (ROI), reduces costs and ensures accurate and quick processing of services at each step.
  • Cognitive process automation fundamentally automates a set of tasks that improvises upon their previous iterations through constant machine learning.

4. Realistic interactive interfaces:

  • Chatbots identify the context and emotions in the text chat and respond to it most appropriately.
  • These cognitive machines enable banks to save time, improve efficiency and help banks to save millions of dollars as a result of cumulative cost savings.

5. Effective decision-making:

  • Cognitive systems think and respond like human experts, provide optimal solutions based on available data in real-time.
  • These systems keep a repository of expert information in its database called knowledge database.
  • Bankers use these cognitive systems to make strategic decisions.

6. Robotic automation of processes:

  • AI reviews and transforms processes by applying Robotic Process Automation (RPA).
  • This enables automation of about 80% of repetitive work processes, allowing knowledge workers to dedicate their time in value-add operations that require a high level of human intervention.

AI-driven future:

  • In India, the reliance on legacy systems, lack of data science talent, and cost constraints have impeded seamless adoption of AI.
  • AI will not only empower banks by automating its knowledge workforce, but it will also make the whole process of automation intelligent enough to do away with cyber risks and competition from FinTech players.
  • AI keeps evolving and innovating with time without considerable manual intervention.
  • AI will enable banks to leverage human and machine capabilities optimally to drive operational and cost efficiencies, and deliver personalized services.
  • By adapting AI, the banking sector can reap these benefits.  
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