RPA-powered systems are enabling game-changing strategies for sustainability in volatile markets
In this day and age, banking digital infrastructure is at new heights. Right from sanctioning loans to predicting money laundering, it’s all possible digitally. What’s more? These processes generate data that enhance marketing decisions.
A management information system (MIS) carries out data processing in real-time. Financial Entities can now monitor borrowers’ assets and generate insights for monthly as well as periodical decision-making. Automated analysis helps with quick lending and corrective actions against defaulters.
Its comprehensive approach to reporting offers varied insights for business decisions. These systems intensively automate all aspects of reporting to a Bank’s management as well as enhance scope for automation of regulatory reports.
Capabilities of Management Information Systems for Banks?
The solution compiles data from multiple lending systems that are also required for regulatory submissions. It generally uses a centralized data repository (CDR) and automatically transforms data for Automated Data Flow (ADF) format, prescribed by RBI.
It hosts a robust analytics system for Asset Classification as prescribed in RBI guidelines. However, for easy access of data to c-suite executives and stakeholders these asset classification reports are also generated on a monthly basis. These reports offer users the capability to draw meaningful insights regarding assets.
To ensure smooth flow of high-quality data in a timely manner, it is essential that –
● Uniform data reporting standards are developed internally
● Data flow is automated from the source systems of banks to their MIS server
● Data is automatically submitted to regulators without any manual intervention
Trends for MIS Systems Simplifying Insight Generation
Automation for Data Collection
Automated Data Collection extracts data from analog sources using AI/ML-powered solutions. Automation reduces all tedious, mundane work from backend processes without human intervention. Algorithms for fully-automated data collection frees your workforce for decision-centered job roles.
The volumes of data grow non-stop, which is great news for businesses. However, it gets more complicated and expensive as new data accumulates. Automated data-collection processes increase productivity and cut costs, all while enhancing data delivery.
Automation of Information Analysis
Automated information analysis also known as intelligent decisioning, can assist in important decisions on behalf of enterprise stakeholders and create useful feedback mechanisms. One example here, the MIS analytics system constantly runs a study and generates data visualizations.
An employee's time is more valuable, especially when it comes to data analysis. By automating tasks that don’t involve a high degree of human ingenuity or imagination, employees can focus on uncovering new insights to guide data-driven decisions.
Cloud Implementation for Streamlined Data Flow
Cloud implementation has grown considerably as a Software as a Service (SaaS) solution. It breaks down data silos, improves connectivity and visibility, and ultimately helps automate business processes by easing data-access. It is a response to the dire need to unify information components in Banks.
Easy accessibility to data stored in a cloud improves operational efficiency, increases flexibility and scalability, and offers a competitive edge with real-time data for automated collection and analysis.