Banks will rethink banking from the ground up as part of Banking 4.0 since customers’ level of expectations has become the new disruptor in the conventional economy. This will have an impact on how banks connect with consumers as well as how they handle conventional bank products, procedures, and finance and risk operations.

To compete in the digital era, new technology and talent must be implemented. This generation of banks will serve as a platform for digital services including a broad variety of banking and nonbanking activities.

Banks will evolve from being safe havens for people’s assets to financial partners capable of making tailored suggestions based on their clients’ financial histories, experiences, and preferences, as well as clearinghouses for a variety of partner services.

The strategic priorities for the banking sectors include; 
  • Seamless Connectivity
  • Data-Driven Intelligence
  • Operational Effectiveness
  • Financial Insights and Risk Control

In this blog, we’ll look at the strategic importance and benefits obtained by the banking sector through the implementation of Data-Driven Intelligence,

Let’s start by understanding what is Data Driven Intelligence, and there we get our first question’s answer,

What does “Data-Driven Intelligence” mean?

The growth of technology has made customers witness the difference between standard and digitalized solutions, this realization built their expectations among the various customer serving industries. Individuals and businesses alike demand solutions that are tailored to their specific needs and help them stand out. This forced banks to drive their transition from restrictive product models to methods that integrate platforms and personalization to allow for scale customization.

Banks should begin their journey toward data-driven insight by using machine learning and AI to operational and experience data. Following that, they will be able to design, model, and anticipate numerous business scenarios and financial impacts by utilizing deep, real-time data analytics to understand consumer and market behavior connected to purpose.

To effect the necessary cultural transformation, performance incentives will migrate from individual product sales to aggregate customer satisfaction scores.

Impact of “Data-Driven Intelligence” in the Banking Sector:

Let’s look into two different scenarios, one following the traditional finance service network and the other following the next-gen practices of the digital era

Traditional Scenario Next-gen Scenario
Isolated systems across the bank. A full source data integrated ERP system to handle all your bank’s operations.
Banks rely on IT to deliver highly customized unique services. Create customized product offers and campaigns depending on how consumers act on the bank’s website, and produce offers outside of the bank’s website, in the cloud.
Manual analytics and risk management procedures Allow for real-time services and sales on the cloud.
User behavior intent is derived by manually executing procedures across different systems, standardizing data, and then analyzing results, resulting in stale forecasts. Automated deep, real-time risk evaluations for flight, churn, and abandonment.
Manual processes impede the adoption of new regulations. Improve the business line’s understanding of consumer profiles, preferences, and behavior.
Post-tragedy fraud analysis Detect fraud in real real-time using state predictions and financial loss.
Isolated offer management systems that do not provide a comprehensive 360-degree perspective of client behavior and possible intent, leading to wasted sales and revenue-generating possibilities. Leverage the SAP Cloud portfolio, which enables a bank to integrate many data sources from diverse systems (internal, third-party, social, and so on) into a 360-degree, real-time customer perspective.
Outcome-Driven Values of Data-Driven Intelligence:
  • Cloud provides the single source of legitimate information for client activity and intent
  • Real-time analytics for improved offer management and fraud prevention
  • Enhanced customer sales and proposal management
Benefits of having Data Driven Intelligence in the Banking Industry:
  • Centrally process applications and reply immediately
  • Based on accurate and full client information given by an automated application, make judgments.
  • Capability to exploit data integration opportunities – operational and analytical, structured and unstructured
  • Incorporating the digital experience of machine learning and predictive analytics
  • Efficient reporting with SAP HANA’s monitoring capabilities
To Conclude:

Every bank requires computer power to run complicated algorithms on enormous operational and experience data sets in order to offer fast, real-time analysis. Everyone in the bank must have the information they require at all times and from any location. This also applies to the rest of the environment. To guarantee that policies and procedures are followed, compliance officers must be able to monitor transaction histories in real-time.

Bankers must be able to view client history in order to assess credit risk and verify that client relationship management activities, such as resolving a bad customer experience, are completed. In a digital, multichannel environment, banks should be able to centrally handle applications from any source of access.