How Working With a Specialist like Ellicium is Essential To Get the Most Out of Your Data Science Initiatives

 

Banks and financial institutions are actively using data science to overcome the multiple challenges they face. Banks are also deploying methodologies like predictive and prescriptive analytics to generate powerful and relevant insights from their customer data.

There has been explosive growth in digital touchpoints in the BFSI industry. Banks have access to large volumes of data generated from mobile apps, social media platforms, IVR systems, and ATMs. Data Science is being deployed in multiple banking use cases including personalized marketing, risk modeling, fraud management, financial inclusion, and much more. 

The future of banking will be driven by digital technologies like Big Data, Analytics, and Data Science management. This is where a technology company like Ellicium Solutions can help deliver the most benefits from data science initiatives in the BFSI sector.

First, let us look at some of the major challenges for data science and how efficient Data Science Managed Services can help.

4 Major challenges in Data Science

As data emerges as the new “fuel” of modern economies, business organizations face challenges in leveraging its benefits fully for their growth.

Here is a look at the 5 major challenges in data science:

  1. Multiple data sources

More banks and financial companies are now collecting data about their business operations and customers from multiple data sources. Without the right data technology, this can be a challenging task due to the existence of unstructured (or semi-structured) data formats. As a result, data scientists find it challenging to analyze relevant information from heterogeneous data sources, leading to problems like low-quality data or human errors.

Adding to this, banks also rely on manual data systems that are time-consuming and can contain duplicate data entries. The need of the hour is a centralized data management strategy that can seamlessly integrate all data sources and produce meaningful information insights. 

 

2. Data security

The growing volume of cyberattacks in the BFSI sector has highlighted genuine concerns about data security and privacy among banking customers. In response, there has been an increase in data regulations and policies around matters like customer consent and data utilization.

Among the major challenges of data science in the banking industry, companies need to follow the 3 basic tenets of data security, namely confidentiality, integrity, and accessibility. To meet their growing data security challenges, banks and financial institutions are adopting technologies in the form of AI-enabled security platforms and predictive fraud detection models.

3. Business value

Most data experts believe that data science must be in sync with business and decision-making processes to be relevant to any organization. For instance, how can effective data offer business value to banks? Through objectives like gaining a better understanding of their customers, helping banks target the right customer base, or offering personalized banking services.

To deliver better business value, data scientists and experts must communicate with non-technical stakeholders who may not understand the technical aspects of the data technologies but recognize the business problem that needs to be addressed. 

4. Undefined KPIs and metrics

Without a clear understanding of the business value of data science among business stakeholders, data experts are often burdened with undefined KPIs and metrics, which can impact their work. Banks need:

  • Well-defined metrics that can measure the accuracy of the generated data analytics
  • KPIs that can measure the business impact of data science and analytics

Along with focusing on the business problem being addressed, business metrics can be identified from a clear business vision that is quantifiable to track the progress of any data science project.

Can Data Science Managed Services help in addressing these challenges?

How Data Science Managed Services can help the BFSI sector

An efficient managed services framework can help BFSI companies meet their desired business objectives and KPIs. A data science managed service (or DSMS) can enhance the customer experience and provide real-time insights leveraging predictive analytics.

DSMS options facilitate the work of data scientists and other data professionals by addressing tasks like:

  • Requirements management by understanding the needs of the business stakeholders and extracting information from real-world problems faced by the banking company.
  • Time & Resource management into resolving business complexities and estimating the data science project costs.
  • Big Data implementation roadmap framework that can provide clarity to all stakeholders including the project timeline, budget, and the business vision.

Using Big Data managed services, the Ellicium team has the right skills to provide services in data science projects. Let us see why.

How Ellicium can help with your Data Science initiatives

By using the data management services provided by Ellicium, banking organizations can streamline their data science operations. As a Big Data specialist, our technical team is dedicated to solving issues like improper data management and unstructured data. Our cloud-based data management solutions are designed to deliver for business users the fastest mode of accessing and comprehending the information and driving improved decision-making. 

With the Big Data implementation roadmap, Ellicium can provide BFSI companies with the right tools to improve their success rate in a competitive environment. Our data solutions are customized for banks and financial institutions that are yet to leverage the benefits of Big Data science technology. 

Other data services from Ellicium include performance tuning, cluster sizing, and Hadoop migration that are designed for achieving any business objectives.

Conclusion

Banks and financial companies often fail to leverage fully their investment into Data Science tools and solutions. A well-designed Data Science Managed Services can help banks overcome their common challenges in data science initiatives and maximize the value of business data for extracting accurate insights into their operational needs. 

Since its inception, Ellicium Solutions has been instrumental in bringing business transformation using technologies like Data Analytics and Artificial Intelligence. Here is a case study that talks about how a leading financial service company used our managed services to improve their Big Data infrastructure.

Looking to start your data journey or elevate it to the next level? Contact us today!