The incredible data proliferation and the ever-increasing technological complications are continuing to radically change the way industries particularly the banking and financial sector, function and compete. During the last few years, around 90% of the global data has been generated because 2.5 quintillion bytes of solid data were created per day. Referred commonly as big data, we understand that this speedy growth and storage comes up with major opportunities for collection, analysis, and processing of both unstructured and structured data.
Big data technology is today, an integral part of the banking and financial services industry and is all set to drive innovation in the years to come. Today, the tech-savvy financial companies are leveraging big data for:
- Generating new revenue streams via data-driven offers like personalized recommendations.
- Becoming far more proficient for competing with cutting-edge Fintech organizations that use state-of-the-art technology for providing customers with advanced financial and banking services.
- Providing much-improved services to consumers like fortified security.
In the current data-oriented business environment data insights and data analytics play a pivotal role and are utilized in almost all decision-making processes that involve the future of the organization. This is particularly, true in case of the finance industry. According to financial experts, the most intriguing trend would be financial companies and banks are able to completely leverage the power of Big Data while adhering strictly to security standards and compliance requirements.
As per https://www.techfunnel.com, several organizations in the financial sector are already taking proactive measures for making the most of the Big Data they are holding and effectively enhancing their overall services.
The big data application in the banking and financial sector would be opening up numerous avenues and opportunities for boosting the efficacy and productivity of financial services. To fully utilize big data, finance companies are focusing their attention on taking three major steps as discussed below.
Define Clearly a Specific Data Stratagem & Align Effectively with Business Objectives
Even though several organizations strive relentlessly to be data-driven, some of them do not succeed in their mission. The reason why most of these companies are literally struggling to manage big data is simply because they are more into short-term results. They fail to manage big data strategically instead; they are focusing on one-off projects.
Financial companies must necessarily use data for accomplishing not only singular objectives but also for achieving broader business objectives and goals. Businesses could create a comprehensive stratagem spanning across all the departments within the organization including their business partners for fullest utilization of data.
Choose a Scalable, Flexible, and Secure Data Platform
Irrespective of the type of platform an organization is using, it is necessary to choose a scalable, flexible, and secure data platform. Experts feel that scalable and flexible data platforms would be facilitating organizations in collecting and storing the amount of data required while data processing in real-time. Security implies factors such as role-based access that would help in ensuring that invaluable information does not go to the wrong people and this would further ensure that companies are able to constantly monitor data usage on specifically a granular level.
Begin with a Single Business Issue & Go on Expanding on It
Some American multinational financial companies started leveraging effectively the power and versatility of big data, firstly, to boost and enhance fraud detection. When they were successful in their mission, they got involved in some other data-driven endeavors. Companies have been using big data to solve a specific business issue and once they could solve the crisis, they went on expanding on that particular solution to addressing other business problems. It is clearly evident that Big Data is an integral part of the current financial services industry and ultimately the success of all these financial organizations would be evaluated according to their efficiency in harnessing the power and versatility of big data in a brilliant way. Let us explore some other aspects where experts believe that big data analytics could certainly add value to.
Enhance Financial Methods
Financial institutions like banks, trading concerns, and lending institutions are known to generate a huge amount of data on a daily basis. They must depend on data handling applications and programs. These financial institutions are generally known to have several diverse business models since they provide a plethora of services. All data trends and data should be considered for creating actionable strategies and competent working models.
Much-Improved Data Processing & Better Storage
Banks and financial institutions have collected a massive amount of data. With a boost in data usage and rapid digitalization in practically every decision-making facet, the database created by these companies is bound to go on increasing exponentially. As such, big data would be using algorithms and codes for processing continuously humongous volumes of data and for managing the shared servers or data clouds.
Machine Learning Reaps More Returns
Financial organizations and banks interact every day with customers. This information seems to be important for coming up with seamless customer experience and also, for obtaining valuable insights. Most of these organizations have already integrated machine learning and artificial intelligence for facilitating services and enhancing fraud detection measures. Fraud detection is certainly an important field where big data has proved to be immensely beneficial.
Effective Credit Scoring
One major responsibility of lending institutions such as https://www.libertylending.com/ is to effectively calculate an accurate credit score, taking into account all the parameters and data to the extent possible. We know that credit scoring is a hugely sensitive activity that could be impacting business credibility and the overall corporate reputation and image. As such, financial institutions use an effective combination of big data analytics and business intelligence software for accurately calculating the credit score.
Blockchain technology is gaining momentum and is currently pretty much in vogue thanks to the cybersecurity threats, data compliance, and GDPR measures. This seems to be having a fantastic application in terms of big data because a blockchain network stores data in ledgers that are distributed, as well as, saved on the participating bank’s servers. As the information seems to be distributed among different banking platforms, blockchain networks are practically impregnable against hacking. Experts point out that the bigger the network; the blockchain would be more secure.
Effective Customer Segmentation
Banks have switched over from a business-centric model to purely a customer-centric model in 2019. For facilitating such a switchover, it is essential for banks to effectively perform customer segmentation for coming up with much-improved and more effective financial or banking solutions to their esteemed customers. We understand that big data plays a pivotal role in aiding the banks in such a process by segmenting consumers effectively on the very basis of real-time and historical data hence, hastening and easing the process.
Boost in Customer Acquisition
Big data would be considering both real-time and historical data for segmenting customers. When the proper segmentation is over, you could profile the specific type of customers most probably would be requiring your services. You would thereafter, simply require creating your marketing stratagems aimed towards acquiring more customers.
Today financial organizations are utilizing big data for easily running their marketing programs. This would be effectively generating more leads and also, conversions. Companies could create a massive customer base and assist in generating effective customer loyalty programs and customer retention. The financial industry seems to be gradually changing itself and becoming a Fintech industry. We understand that big data analytics is acting as the catalyst to speed up the transformation. Today an increasing number of financial organizations are depending on big data analytics for carrying out a perfect visual representation of crucial data for bolstering growth and expansion.