Big Data & Risk Analytics in Banking

Preface:

The Banking industry provides tremendous opportunity to use automated tools for Big data and Risk analytic, In wider spectrum of operational areas.

For implementation of Big Data & Risk Analytics, we need to understand the organization, current capabilities, resources available and chart a rightful course towards the project next steps.

In terms of opportunities, these are very wide provided the managers support and buy the initiative. We will see, how this potential can be explored and businesses can be benefited,

Some opportunities:

  • Productivity improvements - Transactional data quality, Error reduction

  • Customer and Process deviations, violations of set rules and regulations

  • Compliance to regulatory requirements - Central bank compliance

  • Country Sanction reviews - Know Your Customer requirements

  • Customer behavior, Identifying transactional patterns, value,

  • Opportunities for new business, Geo Analysis, Profitability,

  • Business related analyses - Competitive intelligence

  • Generating data feeds for other operational systems

  • Relevant articles for your further reading below;

Big data, data science
Big data

Organizational Road map:

  • Take up one area of opportunity and define the critical business objectives

  • Pick up the source information/Data sources/Reports for Data analyses

  • Identify a suitable technology solution - In house or Off the shelf product

  • Develop and roll out a simple programming as a test case

  • Analyse and publish the findings from data analyses

  • Convey the story to stakeholders - communications

  • Grow by Analytical complexity & reap the business benefits.

Which tools can assist here ?

  • There are wide variety of off the shelf solutions available in the market. In addition, CAAT - Computer Assisted Audit Tools and Techniques can be of great use in such circumstances.

  • Many of the off the shelf applications, provides user friendly tools and techniques to develop end user oriented solutions. This can be tapped to a great extent to reach the desired business objective.

  • The business can invest in a typical programming, for one of the tasked areas, and this will consistently deliver results for the future.,

Business Benefits:

  • Better insights into data and lead in business decisions

  • 100% data accuracy leads to timeliness of Critical Processes

  • Transactional turnaround time reduction of at least 40 to 60%

  • Focus on the future, based on current data - Better control over future.

  • Customer oriented information can be better analysed and researched

risks, data science