KGFS has been a forerunner by investing heavily in technology from the early days, supporting its well-laid-out mission and strategy.

  • Financial Well-Being and Rural Focus
  • Dense Geographic Expansion
  • Wealth Management Approach
  • Wide Range of Financial Products

With the foundation of the investments already made in Technology and Platforms, KGFS has embarked on a digital transformation journey into a Tech 2.0 stack. The emergence of digital platform sand the explosive growth of cloud, analytics, big data, and machine learning capabilitie shave enabled us to look at a suitable mix of branch, field, and digital channels for customer engagement. The KGFS2.0 Tech Stack builds on our Plan, Grow, Protect, and Diversify model and brings a strong middleware with a specific focus on risk, productivity, growth, and regulatory compliance.


On the user interface layer, there is a greater focus on customer, employee, and partner experiences. Besides driving the organization towards customer centricity, the KGFS Tech& Data Science Platform aims at improving operational efficiency, effectiveness, and market growth. The platform also creates new avenues for customer sourcing: inbound marketing via the WhatsApp Customer Self-Service App, data mining on customer transactions; data mining on CB reports (including earlier rejects); and retention management tools. WhatsApp engagement with customers, along with the digital agent network, provides the necessary impetus for customer stickiness and indirect network effects.

Key architecture principles guiding the technology solutions cover:

  • Full system is mobile enabled
  • Flexible Process and Workflow Management
  • Flexible Product definition
  • Multi-dimensional risk scoring engine
  • Configurable legal forms / contracts definition module
  • Psychometric test framework
  • Document Scanner
  • Deviations and Mitigants

Our key initiatives include:

  • Digital onboarding and originations occur through journey-driven customer-facing systems aligning CRM, LOS, and various other systems.
  • Implementation of a unified engagement platform to support omnichannel touch points covering all the channels – Branch, Direct, Digital Agent and Self Service.
  • Agile Transformation covering Enterprise Agile setup aligning processes that support Architecture, DevOps setup, tools, system reliability, scalability, and security.
  • Transition to a microservices-oriented architecture
  • Drive data-driven decisions with a strong data strategy, analytics, and insights.
Following are the front-office systems, which are the key enablers for the omnichannel strategy.
  • KGFS Assist is the customer management and wealth management system and app for the branch operations team.
  • KGFS Mitra aims at creating digital touch points around the branch network. Technology-savvy small shop owners will use this application near customer locations.
  • KGFS Direct is the CRM to stay in direct contact with customers and prospects for lead generation, overdue calling, agent onboarding, and activation.
  • MyKGFSWhatsApp aims to offer self-service capabilities for smartphone-savvy customers via WhatsApp and mobile applications.
A few of the key back-office systems are:
  • Perdix Loan Management System and Audit Management Software
  • HRMS
  • Compliance Tracker
  • Tally Accounting Solution

As part of the data strategy, a focused analytics team is formed to create a “trusted single version of the truth” through the consolidation of the data assets and to champion analytics maturity at the organization by integrating advanced prescriptive and cognitive modelling for decision support purposes. A clear and well-defined strategy is broken down into three essential pillars:

  • Data Visualization: To make data transparent, visible, and clearer to identify patterns, trends, and outliers in large data sets. Stories are told through dashboards and trend charts. The subsequent aim is to make the data more accessible to consumers and to explicitly present the behaviours of the data in a well-recognized manner.
  • Predictive Analytics: The main goal is to make predictions about future outcomes using historical data combined with statistical modelling, data mining techniques, and machine learning. Through this, we can create optimized solutions and drive better business decisions.
  • Future Technology: The main goal is to leverage the latest, innovative technology, such as Web3, chatbots, computer vision, etc., and combine the problems to be solved to come up with an efficient,state-of-the-art solution. The potential is enormous, and there is a huge opportunity in utilising it to solve our current problems.