Big Data for Banking

As the era of electronic banking shapes the industry in ways never before seen, banks have to decide how they will utilize the sheer volume of data that is streaming into organizations. Data is now being created, manipulated and transmitted from computers, tablets and mobile phone which has taken banking out of the physical branches and given customers the ability to express themselves on platforms outside the organization.

More Data Equals Better Insights

The nature of incoming data has evolved to extend beyond the traditional operational data that is part and parcel of everyday business from the days before the information age. With data streaming from a diversity of sources, banks have to make sense of information from social media, call center emails, website logs, mobile devices and other data sources. Collectively this information known as big data provides key insights into customer behavior and market opportunities.

Big data analysis can be utilized for improving customer relations, providing insights for customer retention, increasing product cross-selling and identifying potential areas for market growth. However, the incoming stream of data is semi-structured or unstructured and cannot be immediately placed side-by-side with operational data. Big data tools overcome this challenge.

Big data solutions can now make sense of this diversity of data to derive business value that not only meets growth targets, but also ensures that banks do not lose market share. At a time when aggressive competition in a depressed market has created an environment where every bank is looking for that edge, the answer may well lie within the organization’s ever expanding data stores.

Sales and Customer Service

Big data helps banks understand the behavior and needs of their clients at a deeper level. It can assist with greater product penetration and cross-selling through targeted campaigns thereby lowering marketing costs. Deeper analysis means a more appealing value proposition to individual customers with products that are relevant to risk profile.

Beyond sales, revenue can be boosted through improving customer relationship services and call center efficiency. Not only does it improve customer retention but can reduce operational expenses. Big data helps banks identify problems and implement solutions before customer experience is adversely affected.

Fraud Detection and Risk Management

A constant challenge facing the banking industry is the fight against financial crimes. Be it fraud or a security breach, the information age has given new tools to unscrupulous customers and criminals alike. The key is real time fraud detection integrated with big data capabilities to identify fraudsters and their ever changing techniques without the heavy cost of conventional fraud screening and monitoring.

Better credit risk management means lower default rates and a better counterparty risk profile for banks. In order to achieve this, banks need to look beyond the traditional approach to credit risk management. Reckless lending is no longer about approving credit for customers who are obviously high risk. Big data can help banks identify patterns of behavior that may be indicative of potential defaulters and minimize exposure to bad debt.