Page 50 - Banking Finance October 2025
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                 officers and actual default outcomes to identify 2. Real-Time Analytics
                 discrepancies and areas for improvement.        Technologies like Apache Kafka  and Apache Spark
                 Model Updates: Regularly retrain models with    facilitate the handling of continuous data streams from
                 new  data  to  adapt  to  changing  customer    various  sources, allowing for timely and relevant
                 behaviours and market conditions.               analytics.
                                                              3. Visualization and Reporting Tools
                 Anomaly Detection: Implement systems to detect
                 and address unusual patterns or sudden shifts in  Advanced visualization tools like Tableau, Power BI, and
                 data that may affect model performance.         Qlik provide dynamic and user-friendly interfaces for
                                                                 data exploration and reporting, enabling banks to
         Emerging Trends in Data Analytics                       derive insights quickly.
                                                              4. Edge Analytics
         Several  emerging  trends  are  poised  to  reshape  data
         analytics in the banking sector such as                 Analysing data at the edge of the network, closer to
                                                                 data sources, reduces latency and bandwidth usage,
         1. Artificial  Intelligence  (AI)  and  Machine
                                                                 enabling faster and more efficient analytics.
             Learning (ML)
                 Advanced Predictive Models: The integration of  Conclusion
                 AI  and  ML  allows  for  the  development  of
                 sophisticated models that can uncover complex  Data analytics stands as a significant force in the banking
                                                              sector, offering unparalleled opportunities to enhance
                 patterns and improve predictive accuracy.
                                                              decision-making, mitigate risks, and drive operational
                 Natural Language Processing (NLP): NLP enables  excellence. By systematically addressing challenges and
                 the analysis of unstructured data such as customer  adhering to best practices, banks can harness the full
                 feedback, social media interactions, and call centre  potential of data analytics, fostering a data-driven culture
                 transcripts to gain deeper insights into customer  that propels the institution toward sustained success and
                 sentiments and preferences.                  innovation.

                     Dass meets Bhutani to discuss CoopKumbh 2025 preparations

           Preparations for CoopKumbh 2025 are gaining momentum as Joint Secretary of the Ministry of Cooperation, Abhishek
           Dass, met with NCUI Chief Executive Sudhir Bhutani to deliberate on the upcoming mega cooperative event. The
           high-level meeting aimed to ensure seamless coordination between the government and cooperative institutions for
           the event scheduled in Prayagraj next year. CoopKumbh 2025 is envisioned as a large-scale convergence of coopera-
           tives from across India, aligning with the broader vision of promoting the “Sahakar se Samriddhi” (Prosperity through
           Cooperation) initiative.
           The discussions included planning for exhibitions, stakeholder participation, thematic pavilions, and showcasing inno-
           vative models in the cooperative sector. Dass emphasised the importance of grassroots-level participation and called
           for active involvement from state cooperative federations, PACS, and SHGs. Bhutani assured NCUI’s full support in
           mobilising cooperatives and curating knowledge-sharing platforms. CoopKumbh is expected to highlight the role of
           cooperatives in India’s socio-economic growth.

                     RBI penalises five cooperative banks for regulatory violations

           The Reserve Bank of India (RBI) has imposed monetary penalties on five cooperative banks for non-compliance with
           various regulatory norms, reaffirming its strict stance on governance and risk management in the cooperative bank-
           ing sector. The penalised banks include The Banaskantha District Central Cooperative Bank Ltd (Palanpur), The
           Himachal Pradesh State Cooperative Bank Ltd (Shimla), and three others. The violations ranged from irregularities
           in KYC norms, non-compliance with exposure limits, improper asset classification, and lapses in internal control sys-
           tems. RBI clarified that the penalties are administrative in nature and are not intended to question the validity of
           any transactions or agreements entered into by the banks with their customers.


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