An NLP based tool that extracts insights and user intent from data to leverage banking solutions on where to invest, improve and innovate📊

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According to Epsilon research, 80% of customers are more likely to do business with you if you provide personalized service. Banking is no exception. Our product anticipates customer needs in a more concrete manner by using latest technology to attain a high level of insight that can be set up in a matter of days, delivered in near real time and without the need for a data scientist to maintain the model.

The sole aim is to unlock the hidden user sentiment or emotion which would exponentially impact the growth of the bank with respect to its competitiors and provide valuabe advice on which domains they should continue, improve, invest and innovate to maximize its user appeal.

The project aims to find insights of customer's perception, behavior, pains and thought from data scraped from various different social bookmarking sites like Twitter, Redddit etc. which provide a vast amount of user-generated annotations and reflect the interests of millions of people.

To realize the text mining of the social media data, we applied topic modeling algorithm with R and in the end got 20 different topics with around 200k twitters and Facebook comments. We also used sentiment analysis to compare different topics to see whether they are good indicators of these customers’ comments. In the end of the report, we suggested some recommendations for the financial agencies to better utilize social media to improve customers’ experience and loyalty.

The Solution is expected to peform well and give great results even over huge datasets as the underlying architecture remains same and only harwared requirements would increase which can beb taken care of by using Cloud storage for large dataset and implementing over

1. Bridge gap between banks and coustomer
2. Attract younger Generation
3. Time frame Analysis
4. Specifying which Regions to Target specifically
5. Recomentation / stpes to improve user review
6. Multilingual
7. Fast and efficient
8. Beautiful Dashboards ---> Easy to interpret & convey Results
9. Voice User Interface
10. Tracking coustomer emotion
11. Allows you to fix faults quickly

A positive customer experience increases 85% of the original growth , whereas a negative experience, may decrease 70 percent of expected growth. So tracking a user and its experience becomes important and getting this wrong can prove a costly exercise to any financial institution out there.

Rather than rely on assumption, how can a business know exactly what makes a service ideal for the users? The answer lies in the deep analysis of customer sentiment. Tracking simple metrics like NPS (Net Promoter Score) is pointless if customer feedback on how to increase that metric is not strategically used to make positive change, even if there is a direct link to revenue. In this article, we reveal that customer sentiment analysis is not just about assigning a positive/negative label. Plus we explain how to deepen this analysis and benefit practically from the results.