For any economy to thrive in the global marketplace, despite the fiscal vicissitudes, a robust and active banking sector is imperative. For a country like India, which has a flurry of private, foreign, regional, rural, and urban banks, each apportioned into the private sector, foreign back, and cooperative domains, analytics have become the go-to tool. Post the financial meltdown and the current splurge in banking activities, you know that no cookie-cutter approach can work for financial institutions around the globe to increase their corporate market share. You need a continuous transitional journey, changing the account-centric format to a customer-centric one.
The world of Data
That journey is possible only through poignant analysis of persistently generating huge assortment of structured and unstructured data from various sources, which include customer touch points such as branch, call centers, ATM, online, LoT sensors, social media and financial feeds like news and regulatory events.
The data world: Text documents, CRM Systems, Social media, machine data, geo-location data and sensor data make the gamut of data. The objective is to unify the data. Unstructured data entails paucity of contextualization, proper resources and time burden. With Analytics tools like MECBOT, the first ever integrated and unified data mass to augment, scale, manage and analyze engine, you can now conjoin the data from heterogeneous sources, enrich it, deliver the insights properly and perform consistent analytics. You get free-flowing, vertical search with secure and reliable access control.
Enhancing cognitive functions: The fulcrum of analytics is to fix the leaking faucet of Indian banking. Banks face enormous customer leakages, which is worsening each day. Customer retention is the need of the hour to envisage banking work for retaining the maximum clients. The process is to secure customer loyalty towards the brand. When you know that customers have penchant for offers and choices, analytics will create dynamic business ontologies. Resultantly, it can discover the linkages automatically, seamlessly connecting you to enhanced data pool. It performs text and statistical analytics. The synthetic data acts as a scalable engine.
Smarter and smoother banking: Analytics integrates the customers’ spending patterns, channel usage, consumer behavior, bank interaction, and Debit/Credit card transactions. It assimilates the information from a diverse database, which includes customer service, premium mode or payment behavior, portfolio details or product info, and app and device data, which is the device customers use for mobile banking. The fundamentals are traversal of the customer on mobile or website, and his/her personal data.
Segmenting the customer: Analytics intelligently clusters the customers on the basis of the above parameters. Clustering is based on the user’s transaction history, comprising their frequency of card transactions and their respective amounts. A prismatic view of customer behavior provides personalized insights like loyalty analysis and individualized marketing strategies, preventing anomalies or churn.
Analytics propel you to launch products that specifically target the credit behavior and investment appetite of a customer. It identifies the critical and dynamic touch points in the customer’s patterns or lifecycle, per say. When you perceive the risks associated with different segments of customers, you can scale the efficiency of third-party loyalty programs in loop with analytics-powered customer loyalty for the Indian banks.
Fraud detection: You can facilitate the prevention and detection of irregularities and fraud by analyzing and marking transactional data on a primetime basis against a cluster of conventional patterns. With analytics, you can establish conjunction between multiple source data to determine and decode fraud. There are modern machine-centric algorithms to learn and chase customer devices and behaviors, enabling smooth and early identification of banking fraud.
The road ahead
Using prescriptive and sophisticated analytics and enhance customer’ experience in business and consumer banking sectors, invariably boosting the competitiveness and profitability of banks. There’s an increasing need for regularity adherence, streamlined services, personalized up-sell and cross-sell directives and initiatives, fraud detection, contextual layering, and omnichannel banking experience. These are the requisites to ensure sustainable growth for banks. Advanced data analytics essays a clinical role in ensuring that banking employees and technical staffers execute these strategies well. In a nutshell, the potential benefit of the concerned business analytics for financial institutions lies in nurturing data reservoirs from multiple sources for a cohesive 360-degree assessment of a customer. You need them to smartly use the tools and retain customers, whilst increasing your business profitability or ROI.