The significance of Big Data has grown to an extent that overlooking it is no more affordable in the banking industry. The digital transformation in banking has become a way of life with modern customers demanding convenient ways of banking and the incompetency of legacy systems to meet up with these new expectations.
However, with Big Data Analytics, the times to come will bring an immense change in how banking services are provided by the financial institutions. Some of the futuristic organisations have already been leveraging this technology and are winning over competitors by expanding the business scope.
To cope up with the increasing compliance, risks and new product demands, banks have been exploiting technology in banking. While traditional banking still prevails, its limitations are keeping the modern-day customers away. For this reason, the digital-first approach in banking is taking a front seat.
Have a look at these interesting statistics across a developing country like India.
Source: Economic Times (Survey by Avaya)
FinTech culture is popularising for their abilities to drive a disruptive force in the finance and banking industry. A Global Fintech report of 2017 states that as high as 82% of companies are expected to increase partnership with FinTechs in the next 3 to 5 years to benefit from their fast-moving digital and mobile capabilities.
The Future Scope of Data Analytics in Banking
The immediate challenge
With banking data growing in leap and bounds every day, handling its volume is becoming all the more challenging. Both structured and unstructured data creeps into the legacy systems at a huge pace, and managing it is the biggest complication for banks and financial institutions.
Banks are responsible to sort this data so that it can be useful in product innovation, business expansion and lots more. This means this data needs to be analysed using smart tools in order to make it productive.
The opportunity lying ahead
The challenges associated with data can be addressed using a unified platform to store, manage and analyse all banking data with speed and accuracy. This will enable banks to enhance their time-to-market strategies and support need-specific banking product developments. This will also help banks to have a 360-degree view of customers in line with their sentiments and market trends.
The new data analytics platforms store high volumes of structured and unstructured data and simultaneously analyses it to make it more reliable. With more and more banking data, the need for technologies in data science like predictive analytics, artificial intelligence and machine learning will continue to rise.
This article just lists the very basics of the real challenges faced by banks in terms of big data. However, with data analytics and business intelligence solutions, they can meet any type of challenges head-on. To learn more about how Data analytics and business intelligence solutions work in banks, talk to us.