Fintech Evolution With Big Data

Financial services has gone beyond the traditional banking services, which was limited deposit of funds, withdrawals, loans and services were available for a limited time. With the advent of electronic transactions, the branch level services were advanced to services accessible anytime such as ATM, online internet transactions, telephonic transactions, etc.

With improvements in digital technologies, banking & financial services sector has undergone a huge change. Retail banking and fintech companies entering the foray has challenged the traditional banking process.

Gone are the days when customers were to stand in long queues for deposition / withdrawal of money or run from pillar to post for getting a loan sanction. With rise in number of MSMEs in the market & regulatory changes, customers these days, expect instant and personalized services without any delays.

Are the financial companies equipped to handle this kind of competition & expectations from the customers?

With more companies going the digital way, smaller companies also need to embrace this change in order to live up to the peer competition & customer expectations. Organizations must be able to speed up transaction processing formalities like faster credit scoring, risk analysis, quicker and personalized product recommendations, etc.

Facts & Predictions

Rise in e-commerce & number of smart phone users has given rise to digital transactions in the last 5-10 years and is expected to increase manifold by 2020.

  • By 2020, global digital transactions market is expected to reach revenue of 8 Trillion USD from the present 600 billion USD market, with more than 3 billion smart phone users.
  • With more people opting for digital transactions, POS sale is set to generate revenue of $98 billion by 2020.
  • With growth of online retailing and hence the online transactions, flipside of the coin is the rise in online transaction fraud cases. This is expected to hit $25 billion with amount spent on online fraud prevention expected to touch over $9billion in the next 3-4 years.

* source: Mckinsey & Juniper reports -2016

Need for Analytics

Digital transactions have created an exponential rise in the amount of data generated. Getting ‘Right insights from Right data’ is the biggest challenge faced by most financial services companies. Data analytics has opened up huge opportunities for organizations around the world in terms of understanding their customers and identifying the key to marketing their products successfully.

Customers are spoilt for choices with options to access multiple applications on the fly. But, with that comes higher expectation of getting uninterrupted and single view of their transactions & services irrespective of the devices used.

A simple scenario:

Let’s look at this example where multiple stake holders are involved in a single go.

A person swipes his card at the POS at a mall. He withdraws cash from ATM & then pays for his taxi back home through his e-wallet. He opts to pay his utility bill through mobile banking and later a fund transfer through Net banking.  In this case, there are about five different transactions happening from a single customer and ideally, all of these data gets stored into their respective silos.

It becomes prerogative to any company to ensure that customers get seamless crossdevice view and interface to all their data. The power of big data & analytics enables organizations to source the data from multiple touchpoints & provide insights on its customers.

Omnichannel View

Big data technology with underlying Hadoop architecture has enabled gathering data from multiple silos to a common data store for analysis. Analytics products with Artificial intelligence do a quick and thorough analysis irrespective of the data size to provide recommendations to its customers based on all touchpoints. Customers can also get a single view of all their transactions over any device.

Targeted marketing with data driven insights

Organizations generally spend a huge amount on marketing to acquire new customers or offer their existing customers with other products. But, it gets difficult measuring ROI on marketing campaigns – most effective & least effective campaigns, marketing medium leading to highest marketing, etc.

Analytics can help bring a 360 degree understanding of customers for more targeted campaigns with better results and higher ROI. Customized offers with dynamic pricing model can help gain a better customer base.

Fraud detection

Rise in digital transactions can lead to higher chances of fraud. Fraudulent transactions involve credit / debit cards, payments, bloated up income levels for loan approvals, identity theft, etc. Analytics help detect fraudulent transactions by being able to co-relate information from different sources such as card transactions, web behavior, location data, social media & historical data. Pattern & anomaly detection with power of dynamic & predictive analytics can detect any suspicious activities much before they actually occur.

In a shell, Big data & Analytical tools steer companies in Banking & Financial services take data driven decisions to grow their businesses by increasing their customer base, taking pre-emptive decisions to reduce risks and providing faster services to its customers, while adhering to changing regulations. With multiple applications available in the market, organizations need to choose an analytical tool offering best insights in shortest time span most economically.