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Pacing ahead to conquer the next-gen technology & drive business growth

How is Cognitive Analytics transforming Banking?

Kamalika Roy | MAR 13, 2020

Traditional banking has been at the forefront of disruption with new specialized entrants and innovative business models blurring the line between business and technology. The traditional approach of creating value through business growth, operational efficiency, introducing new markets and product offerings is no longer likely to yield long term shareholder value.



The ability of bank to manifest opportunities in the disruptive environment by re-inventing business models & leveraging external cross-functional partnerships will carve a sustainable path for success. But what’s the starting point? How can banks achieve this?


To answer this, let’s have a close look at a technology term that is doing massive rounds around the globe — Cognitive Analytics !


Cognitive analytics can be defined as a novel approach to information discovery and decision-making. It is inspired by the way the human brain processes information, draws conclusions, and translates experiences into learning.


In layman terms — cognitive analytics mimics the human brain in terms of drawing inferences & conclusions from a given set/ myriad of data..

Let’s have a closer look at the building blocks of cognitive analytics & understand the technologies better by referencing day-to-day examples


  • Natural Language Processing — Ontology-Based information extraction and Speech recognition. One of many examples of this to get you started can be- Gmail’s email classification which classifies the mails under 3 buckets — Primary, Social, Promotion based on the email content. Moving to speech, Apple’s Siri & Amazon’s Alexa recognize patterns in speech, infer meaning & provide a meaningful response.

  • Natural Language Generation — Transforms structured data into plain text. eg) Gmail’s smart compose which offers suggestions on what you should type next in a mail.

  • Computer Vision — Image recognition. Take the example of Amazon Go ( The physical retail arm in US), where shoppers need not wait in any queue to make payments. All they have to do is switch on their app before entering the store and the network of cameras installed in the store ensures that the right folks are billed for the right stuff which they pick up.

  • Machine learningNeural Networks, Deep learning — Systems “learn” to perform tasks by considering examples without being programmed with task-specific rules. The example which we can all resonate with would be ‘Google Translate’. It analyzes millions of documents that are already translated & considers general vocabulary rules as the base to run its own translation functionality.

The combination of these technologies unlock the power of unstructured data (industry reports, financial news,etc) using deep text and/or image/ video understanding to fuel innovations.

Now let’s see how these technologies can transform the banking value chain

Customer Engagement

Banks are vying for customer mindshare & stickiness. Here the aim is to achieve enhanced customer acquisition & retention through personalization.

Banks are focusing on designing interactive computing systems that use artificial intelligence to collect information and build models encompassing a high degree of understanding, influence & natural flow of communication. Cognitive technologies have the power to automate knowledge creation, empower businesses with deeply personalized answers & customer intelligence and discover new revenue streams by deep insights on customer needs.


Market Adoption

  • Secure transactions using voice recognition via banking apps

  • Deploying Web assistant — A leading bank achieved an average of 30k conversations/month & first-contact resolution of 78% in the first 3 months. It has the ability to handle over 350 different customer questions & answers.

Automation

Banks must prioritize the automation of repetitive natural language-rich decision making processes.

Intelligent automation powered by OCR & machine learning can be useful in back/middle office operations involving high volume rule-based tasks. For instance, NLP is used to develop semantic rules to process information and leverage OCR scan of account opening forms, KYC documents such as PAN card, etc


Market Adoption

  • Leading banks are developing natural language generation solutions that can automate investment/earning reports into a voice narrative

  • Banks are investing in voice processing, compliance and surveillance technology to monitor & prevent trading malpractice. The solutions monitor and understand communications across voice and electronic communication channels.

Strategy Insights

This involves detecting key patterns & relationships from a gazillion data sources in real-time to deliver actionable insights

Banks must create a winning differentiator in products & services by leveraging the power of deep complex patterns & relationships from a vast number of data sources. It aids in providing a personalized accurate product match to the consumer.

Cognitve analytics can create value in almost every banking function eg. Real-time insights on loan, treasury, investment portfolios. Banks can shape their portfolio strategy accordingly as well.


Market Adoption

  • Banks are developing solutions to provide personalized wealth management advice to top clients by modeling millions of individuals’ behavioral patterns. This involves leveraging cloud-based technology platforms that can process huge amounts of data along with understanding and learning from each interaction at an unprecedented speed.

  • A leading global bank developed a solution with an ability to process 65 million question combinations in an instant by scanning more than 90,000 actions involving economic reports, drug patent approvals, monetary policy updates, political events and their impact on financial assets.

Indian Banking Leaders must realize that Machine Learning, Natural Language Processing & AI are no longer in the experimental phase but qualify as potential disruptors to create a strong competitive advantage in the market. It’s pertinent to ride on this bandwagon NOW to aim for sustainable growth in the near future!


NSEIT is a leading technology partner for BFSI players in India, US & Middle East. Check out https://nseit.com/dataanalytic to understand how NSEIT is empowering the leading financial institutions to generate value from advanced analytics solutions.


Additionally, NSEIT is a leading partner of Antworks which provides a single integrated intelligent automation platform. Reach out at https://nseit.com/contact-us#dropamessage to know more on how NSEIT & Antworks can empower your enterprise for the next phase of growth.

Kamalika Roy Barman

Asst. Manager - Strategy

Kamalika is a part of the strategy team at NSEIT - working with senior leadership on identifying and growing the technology practices disrupting the Banking, Financial services and Insurance space. Armed with an MBA from the prestigious Indian School of Business (ISB), she's skilled at analyzing competitive behavior & market trends in the BFSI segment.

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