With digitization dotting the length and breadth of daily life, a huge amount of data gets whipped up by the hour. Every credit card transaction, every message sent, every web page opened – it adds up to 2.5 quintillion bytes of data produced daily across the globe.
This is as big an opportunity as it is an overwhelming statistic – an opportunity for even temperately clever businesses to lap up and capitalize on. Of all, Banking industry is sitting on a large piece of the pie since it generates a colossal volume of data inhouse.
The long and short of Banking digitization
It would not be a stretch to say that banking has picked up the gauntlet of digital revolution and responded with mobile and internet banking. It literally is ‘banking on the go’ with smart interfaces offering a host of banking conveniences. Some of these banks have gone a step further towards digitizing their mid and back office operations to build efficiencies and deliver seamless customer experiences. This spawn a set of scenarios:
In their bid to go digital, front-end as well back-end, banks are throwing off data by the terabytes.
This data, available on tap without any auxiliary effort remains largely unused and underutilized.
Analytics – mining this data for authentic business insights leading to better decision making is still not a priority for a lot of banks.
Digitisation to grow numbers and cut costs without insighting is taking banks only so far. To run along further, they need something more.
Data, the Differentiator
While from 1980s to early 2000s, it was IT systems that transformed the ways bank operated, today, data wields transformative potential. While it still presents itself as an untapped opportunity, it can be a critical differentiator, the one that will set the forerunners apart from the pack.
Data and Analytics holds potential in the following key areas:
- Enhancing productivity – Detailed analytics can help identify lag in processes and improve efficiencies therein. It can help teams take analytics-backed decisions and respond to problem situations faster and more accurately.
- Better risk assessment and management – Data analytics can help identify potential risks associated with money lending processes in banks. Based on market trends emerging from analytics, banks can variate interest rates for different individuals across various regions. Fraud detection algorithms can help identify customers with poor credit scores and erratic spending patterns to help banks take more informed decisions regarding extending loans. It may also help track dubious transactions that may be fuelling anti-social activities.
- Help meet compliance and reporting requirements – Data presented in a certain way can help meet compliance, audit and regulatory reporting needs and address issues arising therein. With a super dynamic and ever-changing regulatory climate, banks and financial institutions need a robust backing to be able to meet all requirements on time and with precision, and data and analytics can play a decisive role in this.
- Delivering an omnichannel banking experience – With customers interacting with banks through multiple channels, a seamless and consistent experience at all points in the chain is crucial and data analytics can help drive this with efficacy.
- Detailed nuanced understanding of customers – Analytics can enable a detailed profiling of customers based on inputs received from their spending trends, investment patterns, motivation to invest and personal or financial backgrounds. This opens opportunities to personalize banking solutions, integrate customer acquisition and retention strategies and cross-sell & upsell. It can also be a crucial input for risk assessment, loan screening, mortgage evaluation etc.
Realising the Data Dream
Data and Analytics can prove to be quite the enabler for banks that are ready to reinvent themselves. But the data dream can be as elusive as it is promising. A piecemeal approach that moves from one project to the next under can yield results below encouraging. It is important that the business leaders envision what problems they want to solve with data and analytics and get involved every step of the way. A great analytics approach starts at asking the right questions to guide the discovery process, before data is dived into for the sake of it.
By Kiran Kumar, Co-Founder and Executive Director of Profinch Solutions