The latest tech jargon – ‘Big Data’ and associated technologies have been penetrating the business world at a rapid pace. The explosion of huge data volumes growing at an exponential speed has potential to bring business value for a wide range of industries. Considering, the speed at which data is budding up, it is predicted that by the year 2020, 1.7 megabytes of new information will be created every second for every human being on the planet.
Health care, hotels, manufacturing, management to financial firms are consuming potential of data and analytics and emerging technologies to drive game-changing business results. And taking into account, the rising number of frauds and risks associated with customer’s data; many financial firms have started to take the leverage of big data which is enabling them to serve multiple purposes. The proliferation of data has opened up new business opportunities for financial firms. This pool of data emerging every day, every minute is enabling not just financial firms but also, other small to mid-sized enterprises to enhance their customer service level and add potential to their overall business functioning.
Simplified Fraud Management
Nowadays, as almost every business is striving to make their online presence; businesses are becoming more prone to cybercrimes. Recently, Juniper Research predicted that increasing digitization of enterprise data and consumers’ lives will elevate the cost of data breaches to $2.1 trillion globally by 2019, rising to almost four times the estimated data breach costs in 2015.
In light of growing cybersecurity concerns, financial companies, SMBs, and other companies need to identify, restrain and handle fraud risks and financial crimes across all of their verticals. Any potential risk and fraud need to be managed strategically, considering the customer-centric nature and complex framework of financial institutions’ comprising several facets such as managing investments, risk management, credit card lenders.
Thankfully, big data technologies have simplified the task of mitigating fraud and financial risks. By taking the leverage of machine learning, big data tools, and analytics, financial firms can earn a comprehensive view of customers, recognize patterns hidden in data, assemble the similar data, and differentiate false from the right activity. There are various analytical tools increasingly becoming common among businesses to manage risk and dilute customer service churn.
Customers’ Data Segmentation and Sentiment Analysis
Big data tools have brought a radical change in the customers’ journey. Banking and financial firms can group customers into sections based on customers’ preferences, behavioural patterns, demographic information, daily transactional data, interaction data received from several customer touch points such as merchant records, call centers, home value data.
Further, these data sets can be analyzed to channelize banking products and services, plan services, sales, marketing campaigns distinctly for each group of customers. This helps to improve the efficiency of marketing campaigns and serve specifically each customer’s demand conveniently.
Customers’ communicate with your brands via a variety of channels such as social media, digital ads, mobile apps. Using big data analytics marketers can analyze the complete customer’s data across various channels at the same time. Brand promoters can gain valuable insights on customers’ response to banking products and services via product review sites, social media and ensure customer satisfaction. Also, such analysis helps to respond timely to emerging problems effectively.
Robust Risk Management Strategies
Businesses need a fresh approach and robust technologies for retrieval and analysis of data exploding in a huge variety and at a great velocity from plethora of sources comprising business apps, social media, archives, sensor data, emails, and documents. Data emerging in immense volume has created huge possibilities for its analysis in real-time.
Financial firms can take the leverage of big data tools and technologies to confront avalanche of risks comprising operational risks, credit risks, compliance risks, market or liquidity risks that can put a significant impact on business profitability. By incorporating the revolutionary potential of big data, risk managers can offer more comprehensive risk coverage, exponentially enhance the system response times, ensure regulatory compliance in time and accurately and produce immense cost savings.
Big data tools and technologies, when incorporated in combination with complex event processing (CEP) and high-performance computing (HPC), can enable the enterprise to manage the huge amount of data and unlock actionable insights for financial risk management. It offers possibilities for advanced statistical analysis and instantly identifies the hidden networks between transactions and accounts and unlocks fishy transactional patterns.
Better Wealth Management
In this digital age, financial firms are increasingly embracing the real-time payment modes which have led to getting a better view of customers spending habits. Payments processed in real-time have enabled a smooth shift from cash-based economy to digitized-payment space by surpassing the procedure of administering centralized clearing and settlement operations.
By linking big data analytics with transactional data financial institutions can enhance their ability to make pricing decisions that helps institutions to bring in and keep deposits by linking analytical tools with customer insights. Data-driven decisions help to derive “what if” situations, for instance, the effect on banks bottom line if some percentage of its loans defaulted.
By using the potential of big data financial institutions can enhance profitability, simplify the process of wealth management and provides customers secured individualized experience.
The proliferation of data is opening up seamless possibilities to get 360-degree view of customers and create smarter enterprises. Big data technology integration with data emerging in all forms and sizes allows users to make more productive and informed business decisions. And data-driven decisions drive better business strategies.
Author Bio:
Shraddha Tewari, the skilled and accomplished editor, is formally associated with AceCloudHosting that offers services related to QuickBooks Cloud. In a nutshell, she can be best described as an elusive reader and technology evangelist. Her strong interest in cloud technology and software developments enables her associations to streamline business processes. She can be followed @tewarishraddha1
