The Bots In Banking, Dubai 2016 held by InfrasoftTech ushered in a new wave of ideas in the Banking & Fintech landscape. Held on the 15th & 16th of November at Hotel W in The Al Habtoor City, Dubai; Banking and Fintech executives in the Middle East, Africa and South East Asia gained first hand insights from renowned thought leaders in the region.

While the discussions circled around tackling common challenges, taking advantage of opportunities & carving the future; the discussion that caught everyone’s attention was – How to leverage Digital solutions in your existing Banking processes and structures?

Have a look at the key takeaways (Excerpts from the presentation by Rajesh Mirjankar, CEO and MD of Infrasofttech)

“We see The Big Shift in Banking and Financial Services, What is the Big Shift all about?” quotes Mr. Mirjankar. To which he added it is the way banks will optimize the strategy of banking. The transformation of traditional banking to Core Banking Solutions, digitized transactions, mobile and internet banking is The Big Shift in the industry.

Reason behind Why The Big Shift? The total world population is 7.4 billion, out of which:

• Internet users are growing at 14% yoy

• Social Media users growing at 21% yoy

• Unique Mobile users growing at 28% yoy

• Active Mobile usage growing at 37% yoy

Source:Trendforce, Feb, 2016

The data above represents an increasing demand for mobility on the globe. It also speaks that as you grow up the ladder in your business strategy or technology adoption in the strategy, you will realize that if it is not on mobile it will not exist. Use of technology is adopted by this generation at a very early stage and hence the demand for technology adoption has taken up the most space in our strategies today.


The presentation commenced with discussion on a widely used term Big Data. An impromptu question that comes to our mind is ‘What is Big Data and if it is really Big?’ The response would be; Big data is any form of data available from any platform or channel. It isn’t needed to be big but offers very wide scope in terms of consumer insights.

From raw data very small and simple consumer insights can be inferred by looking at 4 V’s of Big data:

• Volume of data – The amount of data

• Variety of data – Number of data included

• Veracity of data – Accuracy of the facts and figures

• Velocity of data – The speed of data processing

Types of Data to be leveraged

• Unstructured Data – Take an example of particular campaign with specific # being viral on social media. The response you receive in terms of data will be unstructured data. Another example could be of PR campaign being effective on various media channels and website.

• Semi structured Data – Semi-structured data lies somewhere between the structured and unstructured. It is not organized in a complex manner that makes sophisticated access and analysis possible; however, it may have information associated with it, such as metadata tagging that allows elements contained to be addressed.

• Structured Data – Structured data will have data from the core banking system, CRM system or from any other enterprise management platform which gives reports and data in uniform and structured format.

Usage of Big data in Fintech

• Cognitive Analysis – To process extremely massive sets of data paving the way to discover key trends and findings as well as the identification of connections between consumer needs and available financial services.

• Machine Learning – For financial planning as well as development of trading strategies and hedge funds.

• Improved Consumer Insights – Consumer insights could be drawn from analysis of data gathered from various channels approached by consumers on the web.

• Customer Experience & Engagement – Combining processes with mobile, speech and touch technologies supports the implementation of user friendly interface designed to deliver seamless customer experience on mobile, Web, and other platforms.

Usage of Big data in Banking

• Product Analysis – While developing or introducing any new product, which are those features you would want include to stay up right with the market and target audience needs.

• Product Lifecycle Analysis – Product lifecycle includes various stages, at which stage is the product most profitable? Or at which stage product is performing on high scale. Such analysis could be performed using Big data technology.

• Profitability Analysis – Analysis of profitability in terms of which branch of the bank is most profitable. A particular bank branch has maximum number of footfalls on which day of the week. Take an example of demonetization in India; we can presume that maximum banks will be high on profitability scale due to large number of deposits in short period.

• Personalized Services – Personalized services could be given to clients by identifying precise details of the clients’ history and engagement with the bank.

• Process Improvement – If any process improvements are to be done with respect to employees needs or customer needs, even those could be addressed through analyzing Big data.

• Performance Analytics – Analysis of bank performance, product performance, employees’ performance could also be executed.

• Risk Analysis – We could generate various reports on fraud risk analysis, fraud detection, AML reporting etc could also be realized.

BOTS in Banking

Further the discussion went on to a trending fad in the banking industry which is BOTS. The discussion also included how do they function and what is their importance in Banking industry?

What are BOTS and how do they function?

Have you used Siri on your Apple Iphone? Yes, it is nothing but a type of BOT typically known as Chatbot in your phone which has specific technology to understand what you question and responds to it with specific result.

Machine Learning is essential for the way BOTS function. For example customers coming to banks with various queries, with the help of Big data analysis you can bifurcate those queries into frequently asked questions and implement them in a BOT which then could be used for easier conversation with the customer.

Importance of BOTS in Banking industry?

Bots offer the ability to not only extend the conversation but also to know the history of a particular customer according to the conversation. A BOT could be used to emulate certain basic tasks a bank executive would perform, which could be giving advice, directing someone to a nearby ATM, telling them their balance, showing their mini statements, helping them make payments etc.


Taking a lead further in the discussion was Digital 2.0 as digital innovation in the near future. It explored what it will majorly comprise of:

• Analytics including Big data analytics and Sentiment analytics driving the industry.

• Social media integration of banks with their existing as well as prospective clients.

• Augmented reality explained by giving an example of Pokémon Go which took help of location services and created virtual Pokémon for everyone to hunt.

• Gesture based technology would involve speech and touch based technology for seamless interaction across all platforms.

• Internet Of Things (IOT) integration across processes and systems involved in the Banking and Fintech industry.

• Digital partnerships and alliances for actively developing digital capabilities and not to lose network with dozens or more organizations in the industry.

• Gamification through loyalty programs, earning bonuses and credit points, increasing customer engagement and improving financial literacy will be one of the best as well as cost effective usages of digital channel.

• Omni channel experience is a multichannel approach to sales that seeks to provide the customer with a seamless browsing as well as shopping experience whether the customer is online from a desktop, mobile device, telephone or in a brick and mortar structure.

The presentation with the panel discussion concluded on a remarkable statement, “Technology has taken further lead and we are now capable of building a product around it.”

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