Yogesh Rana

Software Engineer at Capital Quant Solutions Pvt Ltd

Yogesh Rana is a skilled Software Engineer with a robust background in various development roles, currently employed at Capital Quant Solutions Pvt Ltd since August 2019. Prior experience includes serving as a Python (NLP) Developer at Phelix.ai from April 2018 to August 2019, along with a previous position as a Django Developer at SPLICE GLOBAL SERVICES PRIVATE LIMITED from October 2017 to April 2018. Yogesh holds a Bachelor of Technology degree in Computer Science Engineering from Maharshi Dayanand University, completed in 2017.

Location

Delhi, India

Links

Previous companies


Org chart

This person is not in the org chart


Teams

This person is not in any teams


Offices


Capital Quant Solutions Pvt Ltd

Capital Quant Solutions (CapQuant) is focused on solving the problem of document based information overload for the financial services industry. Banks and financial institutions across the globe receive complex and unstructured documents such as financial statements, bank statements, news, corporate announcements, research reports etc. Key financial decisions are taken based on the information in these documents. Current process is manual where an analyst (who is typically and MBA/CA) reads thru the documents and extracts relevant information and then analyzes the same. Such analysts are hired across all functions such as credit, risk, trade finance, equity, fixed income etc. Manual process has limitations: 1. It is expensive as it consumes expensive human bandwidth. 2. It is error prone. 3. It has limitation of scale. To address these problems CapQuant offers FinStinct as a comprehensive cognitive automation solution which uses the power of ML/Ai & NLP. FinStinct can process just about any financial document and pull out the relevant information for analysis. FinStinct product has pre-created models which are available off the shelf for generic documents which are used by almost all financial institutions. FinStinct also offers a platform which has a very powerful do-it-yourself engine called the K-Engine. It gives the power of building machine learning models to pull key value pairs from any document to a business user who may not know machine learning. By using the platform the user can build models specific for any document and start extracting key value pairs from those documents.


Industries

Headquarters

Delhi, India

Employees

1-10

Links