The author of this article is Praveen Paulose, MD & CEO of Celusion Technologies.
Use of technology in Indian financial space has transformed over the past decade and is currently a leading force in the global phenomena. This has led to the innovation in the field of banking, finance and insurance. Driving this transformative mission is the integration of state-of-the-art technology in the financial industry.
The fintech sector in India today makes use of tools such as Artificial Intelligence, Machine Learning, Blockchain, and data analytics – all culminating to create unique solutions helping elevate customer experience (CX). This tech-driven approach has not only improved service delivery but has also created new ways of accessing effective solutions. The landscape is characterized by a growing digital space which echoes the aspirations of a population that is becoming more and more technology-oriented.
Technological improvements simplify processes through the automation of common activities for minimizing errors and increasing speeds. Business Rule Engines coupled with Machine Learning gives the opportunity for automated decision-making, thereby enhancing operational efficiency. These systems are then capable of handling large amounts of information in real-time, thereby providing timely and reliable reactions to changing market preferences or trends. The BFSI sector has witnessed major shifts in consumer expectations.
Modern consumers no longer look for simple fiscal services, but individualized and convenient ones with a guarantee of high level security. To take care of these demands, technological advancements offer innovative solutions in the form of new products and services. Likewise, Machine Learning can process customer data to offer customized tips or credit assessment.
Business Rule Engines also simplify the provision of such customized services by converting intricate business rules into simple operational processes, thereby guaranteeing compliance and uniformity in service delivery.
Introduction to Business Rule Engines
Business rule Engines are specialized systems that are created for the purpose of executing business roles with maximum efficiency. These include several processes, of which the most common are logical statements during business policies, regulations, and operational constraints within an organization.
They help provide the organization with a structured framework to facilitate decision-making and automation to ensure the best possible compliance and efficiency throughout. BRE engines facilitate quicker data inputs by allowing businesses to codify complex rules into structured formats.
This codification is a key step in simplifying the decision making process. The result of this is much faster responses towards changing market dynamics and regulatory requirements. The agility offered by BREs is unparalleled. These engines empower organizations to swiftly adapt to changing market dynamics or regulatory shifts.
As rules are encoded within the BREs, any alterations or updates can be efficiently implemented across the system, ensuring compliance and operational alignment with the latest requirements. This agility enables BFSI entities to respond promptly to regulatory changes or market demands without undergoing extensive overhauls in their systems.
By employing BREs, businesses ensure consistent application of rules across diverse operational channels. This consistency is fundamental in maintaining compliance and adherence to industry standards. The automated enforcement of rules through BREs guarantees that all transactions and processes adhere to predefined guidelines, reducing errors and ensuring operational efficiency. BREs facilitate real-time decision support by swiftly analyzing incoming data against predefined rules.
Whether it’s assessing risk levels, detecting fraudulent activities, or determining eligibility criteria, these engines swiftly process incoming data, providing instantaneous decision support for critical business operations.
In essence, the facilitation of quicker data inputs by BREs is not merely about expediting processes; it’s about instilling a structured, efficient, and responsive framework within the BFSI sector. These engines serve as a linchpin for ensuring adherence to regulations, enhancing operational agility, and delivering consistent and efficient services to consumers.
How can Machine Learning elevate the performance of Business Rule Engines?
The combination of Machine Learning and Business Rule Engines (BREs) creates a powerful synergy. One notable merit of incorporating ML into BREs is empowering predictive analysis. BREs have been able to predict outcomes using ML algorithms that can spot patterns from huge sets of data.
For instance, ML algorithms can analyze past transactional data to predict fraudulent activities and take preventative measures in risk assessment. This kind of predictiveness in rule-based systems gives more decision making abilities to respond in advance either to emerging risks or opportunities.
Additionally, Dynamic Rule Adjustments in Real-Time helps change dynamic rules via linking them with Multilayer Learning Systems (ML). ML algorithms always learn and adapt to changing data patterns. Since BREs dynamically adjust their rules in accordance to the most recent knowledge extracted from a continuous stream of data, rule-based systems are able to make fast optimal decision procedures that react to the varying characteristics of the market, consumers’ behavior, or regulations.
BREs are made more accurate and flexible by advanced ML-driven algorithms. These algorithms have the ability to decipher intricate patterns into data that traditional rule-based methods can’t do. With ML abilities, BREs can improve on how they make decisions.
regulations, enhancing operational agility, and delivering consistent and efficient services to consumers.
Future trends in Business Rule Engines
The future of business rule engines in fintech looks bright. This evolution includes incorporating sophisticated analysis capabilities, natural language processing, and decentralized decision-making skills.
BRE will be more capable of responding to a dynamic environment, able to adapt quickly, and equipped to address complex situations in real-time. Business Rule Engines will enable more personalized customer experiences, compliance with regulations, and further automation of financial procedures accurately.
Machine Learning and Business Rule Engines provide the cornerstone for operational excellence in the dynamic BFSI environment. These technologies should be in harmony to improve decision making, enhance agility and promote flexibility, which are necessary for an efficient and customer-oriented financial system.
The development of Business Rule Engines in the fintech sphere will pave the way for unmatched productivity and creativity in the years to come.
About the Author
Praveen Paulose became a first generation entrepreneur when he started Celusion Technologies. The idea was based on the premise that they could build great software but today their software is changing the way people look at finance. Celusion Technologies has been a bootstrapped company that has always been careful with the money and they have been profitable from the word Go. They follow a flexible business model ranging from cloud based software as a service to licence based fees for on site deployment.
Praveen is passionate about technology and spends most of the day either programming or reading about the next big thing in technology and how that can be applied to their offerings. He loves solving complicated business challenges using technology.
His business mantra is summed up in three words, “Possible is Everything.” Today, Praveeen is a sought after business leader in the fintech sector in India that is on an explosive growth path.
