Satin-ERP – Satin Creditcare Network Limited
Satin-ERP: Technology Transformation in Microfinance
Problem
- Identity fraud and delays in manual loan processing workflows.
- Limited visibility into field operations, resulting in inefficiency and compliance risks.
- Insecure or inconsistent identity verification at customer interaction points.
- Underutilized customer data, with no analytics-driven insights for decision-making.
- Heavy customer dependency on support staff for basic services, with no 24×7 access.
Solution
- Seamless biometric IRIS-based loan agreement signing integrated with UIDAI.
- Real-time geo-fencing and geo-tracking of field operations using GPS and mobile data.
- Facial recognition technology for secure, touchless client verification across attendance and financial workflows.
- A Machine Learning-driven customer insights engine for predictive analytics.
- A client-facing self-service mobile application enabling 24×7 digital access to core services.
Outcomes
- Reduced loan processing time by 60%.
- 95% improvement in operational visibility and field workforce tracking.
- 99% drop in identity fraud cases via biometric authentication.
- 20–25% increase in customer retention using personalized analytics.
- 60% app adoption, reducing support center loads and improving customer experience.
SKOCH Award Nominee
Category: Financial Services
Sub-Category: NBFC & MFI – Technology
Project: Satin-ERP
Start Date: 5-01-2017
Organisation: Satin Creditcare Network Limited
Respondent: Sunil Yadav
www.satincreditcare.com
Level: BFSI – 1
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Case Study
Next-Gen Digital Transformation for Secure Financial Services and Client Engagement
We have developed a robust in-house ERP system as part of our commitment to digital transformation in financial services. This advanced platform is designed to significantly enhance security, streamline operations, improve customer engagement, and support data-driven decision-making. By integrating state-of-the-art technologies such as biometric authentication, geo-tracking, facial recognition, machine learning, and self-service applications, our ERP revolutionizes key processes including loan processing, client verification, workforce management, and customer insights. This innovative system enables us to deliver faster, safer, and more personalized financial services to our clients.
Problems
Traditional loan processing was manual, time-consuming, and prone to fraud, especially in remote areas. Workforce management lacked real-time location visibility, leading to inefficiencies and compliance risks. Identity verification for attendance and transactions was vulnerable to impersonation and manual errors. Customer data remained underutilized, limiting personalization and predictive insights. Lastly, clients relied heavily on support teams due to lack of 24/7 self-service options, increasing operational costs and slowing service delivery.
Solutions
The project introduced:
- UIDAI IRIS-based seamless loan signing for secure, instant, paperless agreement execution.
- Geo-fencing and real-time geo-tracking to monitor and optimize field force operations.
- AI-powered facial recognition to authenticate users in attendance and transaction workflows securely and contactless.
- Advanced customer insights platform driven by machine learning to unlock predictive analytics and personalized engagement.
- Client self-service application providing round-the-clock access to services, reducing dependency on human support.
Each component was integrated into a scalable, secure digital platform compliant with national digital identity standards.Key Outcomes & Impact
- 80% reduction in loan processing time through secure, paperless IRIS-based digital signing, accelerating approvals and disbursements.
- 100% improvement in field workforce visibility via real-time geo-tracking, enhancing operational efficiency and compliance.
- 99% decrease in identity fraud incidents using AI-driven facial recognition and biometric authentication for secure client verification.
- 18% increase in customer retention enabled by advanced machine learning analytics delivering personalized and predictive insights.
- 20% adoption rate of the self-service application, reducing dependency on support teams and improving customer satisfaction through 24/7 service access.
For more information, please contact:
Sunil Yadav at Sunil.Yadav@satincreditcare.com
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