Globally once banks operated under a striking rule of 3-6-3 which describes how bankers would give 3% interest on depositors’ accounts, lend the depositors money at 6% interest and then be playing golf at 3 pm. Now all of us know that sand timer has reversed and the same industry work under complex environment dealing with the present (daily work) and future (predictions) for efficient growth of their business. Who can be a helping hand to them? Can anyone save their time? Can anyone manage their future risk?
Fintech platform is taking a lead role everywhere. It has captured market like a network of mobile operating companies. Is the network of lending platforms reached to banking in predictive analytics?? Well, it’s not a surprise for anyone that Fintech network has reached here also.
Let’s forget about white collar professional getting adopted to cloud, mobile technologies and apps, wearable devices, intelligent/smart networks and systems, it’s not a big thing but a taxi driver also feels handicapped without them. Growth in data is a product of multiple technological developments which may be due to the adoption of Fintech technology. Then how are these Fintech players making use of such technological advancement? Whether they are able to use it or still a gap is there?
Some areas in finance where these players have captured the market and can help the bank with big data analytics are:
Extract data from the bank and thereafter used it for qualitative analysis like behavior, willingness, the ability of customer.
Customers are used to digital platform especially for financial services to gain a low cost advantage. An indication of the digital channel includes online direct investments plans, online savings/deposit account opening and automated advisory services.
Marketing, Customer Retention, and Loyalty Programs
Providing customized products to the customer with attractive rewards and discounts to retain them.
A solution or combination of device identification, biometrics, behavior analytics, etc is used for better risk management solutions in the fraud and authentication. Banks apart from storing data focus on building powerful algorithms that mine this data to provide actionable insights and lending platform serve the same purpose.
When one can extract the core out of data by combining various economic factors, trends, market movement, growth drivers then a perfect investment scenario can be created. With help of big data, lending companies can easily make out of it. The solution for market anomalies and preventive checks against them is also an easy check by lending
Upcoming opportunities in 2017
Large bank spends $ 1 billion a year to manage risk and another $ 1 billion for implementing compliance process. They need players for managing their regulations to avoid penalties and fines from last ten years.
No banking can work without Rules and Regulations. Next generation of innovation in Fintech demands better risk management for regulatory compliance procedures at low cost. Emerging technologies such as cognitive analytics, big data, machine learning and predictive analytics offer products to manage risk compliance.
We expect that
will emerge as a distinct new player in FinTech for boosting banking operation.