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Last Updated : Apr 09, 2019 03:46 PM IST | Source:

Artificial intelligence all set to change the BFSI landscape

The banking industry is using AI to reimagine products, processes, strategies and the overall customer experience.

Moneycontrol Contributor @moneycontrolcom

Usha Prasad

Businesses across verticals are moving from digitisation to cognification of everything. Having said that, banks and financial institutions have recognised the potentials of Artificial Intelligence (AI) to redefine their processes, products and services.

With customer experience becoming vital to ensure good business, banks have been adopting AI solutions to further enhance their services what with virtual assistants and chatbots handling different customer queries.


Elevating Security and Customer Experience

The banking industry is using AI to reimagine products, processes, strategies and the overall customer experience. On the security front, AI is touted as a big game changer.

"Cutting edge AI research and development is transforming the sector through an automated, integrated, collaborated approach to cyber defence and helping facilitate better information sharing between security components within and across organizations,” says Venkat Krishnapur, Vice-President of Engineering and Managing Director, McAfee India.

"In the current scenario, four new threat samples are submitted to our systems every second, which is around 250 samples every minute or 15,000 samples every hour, equivalent to approximately 3,60,000 NEW samples daily! AI is helping analyse large data sets using algorithmic pattern recognition capabilities in high-volume and complex environments, significantly improving the identification and conviction of threats,” he added.

One of the first forms and perhaps the most predominant form of AI implementation in banking is in customer care.

Tushar Garimalla, Chief Growth Officer, Capital Float, slightly differs in his view. “AI isn't commonly used in banks or in the BFSI sector. However, chatbots are widely used by banking websites to engage with potential customers.”

He highlights that chatbots are currently very primitive and must evolve from a responsiveness perspective. “This means that chatbots should be able to expand their scope of responses, which is possible as more data is gathered from users. Additionally, chatbots aren’t vernacularly equipped. This could be another area of improvement going forward.”

According to Accenture Banking Technology Vision 2018 report, 83% of Indian bankers believe that AI will work alongside humans in the next two years — a higher than the global average of 79%.

The report also states that 93% bankers in India said they increasingly use data to drive critical and automated decision-making.

“In theory anything that requires ‘less than a minute for a human to think’ can be implemented using AI ,” says Abhiram Modak, Chief Principal Consultant, BFSI verticals, Persistent Systems.

”Back office is the usual suspect for implementing AI due to its repetitive nature of work. However, a lot of Front Office functions like Loan Eligibility advice, Wealth Advice are also likely to be taken over by AI to some extent” he adds

Better use cases

“BFSI sector is transforming by deploying AI’s innate ability to understand the world as humans do while retaining the advantages over humans on volume, speed, accuracy and lack of bias,” says Jaya Vaidhyanathan, President, Bahwan CyberTek.

As she puts it, AI is commonly used in banks for the following –

1. Prevention of frauds and Anti-money laundering

Most banks globally are moving from rule-based systems to AI systems for a more intelligent identification of AML issues – geo-tagged data, large sums of withdrawal from a client that typically draws out small sums etc. are pattern matched for flagging.

2. Algorithmic trading

Real-time data from various financial markets are analyzed to come up with the mood or sentiment of the global markets and therefore, a more accurate prediction of the relative trading prices in these markets. AI can also support in intelligent decision making free of bias based on the models.

3. Risk Management

Date related to latest transactions, market trends, commodity prices etc., are used to come with unbiased risk profiling that helps indecision making on loan processes.

No doubt, AI is shaping the future of the banking and financial services sector through the entire value chain.

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First Published on Apr 8, 2019 07:48 pm
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