Challenges faced by Companies in FSI Sector

The industry continues to face multiple challenges from declining revenue, demanding customers, burgeoning operational costs and increased regulatory pressure. There is a tremendous opportunity to leverage Analytics in this sector courtesy of the explosive data growth owing to digitization. The Big Data phenomenon has thrust the once-technology shy banks to the forefront of this data revolution. The industry now has no choice but to acknowledge, acquire and adapt to this situation to not only survive but thrive.

A summary list of some of the major challenges that this industry is shown below:

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How Analytics can help with these challenges?

Analytics has countless applications in resolving some of the most pressing of this industry’s problems. It is brilliantly poised to take the center stage as the volume of data generated by embedded systems multiplies into a huge corpus of structured and unstructured data. Combining statistical learning models, machine learning algorithms and data mining techniques, it can sift through the voluminous data coming from multiple channels like Internet of Things (IoT), Social Media, Wearable Technology, traditional relational data warehouses to provide actionable insights.

A few practical applications of Analytics into this domain are listed below:

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Why should I Choose Innodatatics?

Innodatatics is strongly differentiated by its highly qualified individuals that have several decades of domain knowledge between its members. Our team members have the unique blend of passion, the enthusiasm of a startup company, excellent educational background from premier institutes and prior experience of working in the biggest of consulting brands. Having already provided solutions to a diversity of the common (and not so common) problems faced by the industry positions us very strongly to excel in this industry.

Our R&D team continues to innovate partnering with its alma maters in resolving problems

Case Study 1 :   How to identify fraudulent and illegal transactions due to Insider trading
Case Study 2 :   How to reduce manual processing of loans by increasing the automatic loan approvals & rejections
Case Study 2 :   How to reduce manual processing of loans by increasing the automatic loan approvals & rejections
Case Study 3 :   How to predict on whether a person will default on the loan & if yes, then after how many loan installments
Case Study 4 :   How to automate to reduce manual effort in processing bank applications
Case Study 4 :   How to automate to reduce manual effort in processing bank applications
Case Study 5 :   Learn on how to predict the deposits churn & reduce the risk of losing customers