Top 5 Data Analytics Use Cases for Banking

 Banks and other financial services companies generate a lot of data daily. Applying analytics and data science in functional areas such as sales, marketring, finance, risk, compliance, fraudand NPA monitoring, can help ensure operational excellence and allow management to make critical decisions where timing is crucial. Partnering with the right data analytics companies enables banks to advance, accelerate, and automate their data-driven decisions. Here are some examples of how data analytics can be good for banking.

 

1. Streamline and modernize the data and analytics landscape

 

Financial services companies are plagued often with challenges caused by interconnected issues in their data and analytics landscape, worsened by a lack of in-house expertise. This results in compromised data quality, scalability, user experience, and trustworthiness.

 

See how InfoCepts provided a data and analytics solution that improved data quality, transformed data governance, and revamped delivery excellence in a fintech company.

 

The team studied the present state and laid out a path to improve data quality, enhance delivery excellence, transform data governance, and ultimately enable a jump in user trust and adoption. A series of well-designed and collaborative sessions helped define the future state. It also established a step-by-step implementation plan in sync with the client’s short-term and long-term business objectives. TCO and ROI analyses guided the formation of a consensus between the finance and IT departments.

 

2. Optimize cost and increase adoption

 

Data analytics companies offer managed services that can help mature and modernize a bank’s data and analytics ecosystem and harness the power of D&A for better decision-making. They can help overcome challenges like automation debt, overworked stakeholders, surprise downtime, and lack of cross-skilled resources.

 

See how InfoCepts assisted a global bank in reducing 80% of tickets each month and maintaining 100% SLA compliance for all its data analytics applications. This allowed corporate and IT leaders to create a slew of data-driven innovations to boost analytics adoption throughout the company while boosting operational efficiency and the overall quality of customer experience.

 

3. Boost analytics adoption with a conversational and intuitive app

 

A conversational business intelligence app can help banks ‘converse’ with data and obtain insights on the fly. With voice-enabled capabilities and a Google-like natural language search interface, it can reduce the cycle time between insight and question by over 40 percent.

 

Learn about this InfoCepts solution where they helped a conversational BI application for a global bank. It uses MicroStrategy NLP features, a knowledge graph, and custom libraries to create a text and voice-based search interface for data and insights.

 

The solution received the MicroStrategy Partner Award for its significant impact on the end-user experience. The natural language search experience that is both simple and intuitive altered how users access and interact with now-decentralized data. It also lowered IT dependence on data and insights preparation by more than 40 percent. Within a few months, the active user base grew by around 4 times, driven by higher portal visits, self-service data searches, and overall feedback.

 

4. Scale analytics tools for innovation and better service levels

 

A cross-functional and data-savvy team can augment a bank’s capabilities to create and scale insight delivery services. See how InfoCepts did it - Their team produced fast PoCs and analytics tools to help firms meet their data-driven and regulatory reporting demands. These early victories boosted user confidence in the analytics platform, which led to broader adoption.

 

5. Modernize the big data platform

 

Financial institutions are  modernizing their big data operations and the data engineering capabilities as well as adopting cloud to stay ahead of their competition . See how InfoCepts helped a leading fintech company modernize their data platform that enabled higher revenues and faster roll-out of new financial products.