With our in-house and partner solutions, we provide cutting edge Analytics to the need of institutions. We specialize both in the risk analytics as well as consumer analytics.


RiskTek is uniquely positioned with all the consultants being Techno-functional in nature. Hence, we understand the functional aspect and are hands-on with the technical aspects. We implement what we recommend. Reach out to RiskTek for solutions related to:

Implementation Services

RiskTek does implementation services related to risk system and capital market solutions. Our capabilities includes end to end implementation covering:

Business Analysis:



Application Development

Looking for bespoke application development, look no further. Our hand in hand development strategy, and a large state of art development center in India will ensure that our Client derives value from developments. Our value addition is through consultative approach to the development of applications with deep domain knowledge and technological efficiency. RiskTek specializes in developments related to:

Data Management Services

RiskTek understands that for any implementation, having the right data is very important. Having right data and management of the same is a very important part in any implementation, to gain the value of such implementation. We follow the three step approach to data management:


  • Assessing the Source systems data structure
  • Assessing the business process for various points of data entry into the system
  • Development of the client specific logical data model that is specific to each of the functional areas such as risk, ALM, Profitability, Retail and Analytics the source system that will required for the work at hand. We have Logical data models that covers each of the areas, through implementation experience in large banks in the Middle east.


  • Data Quality Assessment
  • Data Gap Analysis
  • Filling Up the data gaps either through automated process (defining various business rules for the data transformation) or through manual intervention
  • Development of the data dictionary


  • Process enhancement so that the data entropy is plugged
  • Business rule engine implemented at the ETL layer which will highlight the data errors, which can be remedied through intervention