Ø Intend of the project to develop a paradigm using conceptualization of Signal Processing

and Advance Machine Learning Algorithms to identify Fraudulent and Genuine Calls from

alerted audio calls of HSBC Contact Centre.

Ø Implemented signal processing and Channel Diarization concepts to segregate the

customer conversations from mixed raw signal. Developed scripts to derive features from

audio signal by reminiscing behaviors of fraudsters and genuine customers from audio and

implemented into Machine Learning models to predict Voice labels.

Ø Plan to replicate Fraud Ops Manual caller verification process by integrating the developed

paradigm which would impact the reduction of Fraud losses approx. 1.1M GBP monthly

Ø An automated business assistive system enables customers to know their application status

(Approved/Cancelled/Declined), amount of time left to complete the verification process

of application, amount of time it will take to final approval of application.

Ø Assists Operation AMOs/MOs, stake holders, etc. to know monthly Application volumes,

KPIs, Application Status, Application Cancellation Reason, etc.

Ø Understanding the verification process of Cards, Loans, Mortgages, and Other products for

multiple markets. Identifying TTD and Referred volumes based on Captured date,

Decisioned date and other parameters.

Ø Forecasting TTD AOP volume and Referred AOP volume using multiple forecasting

methods.

Ø Calculating Staff Productivity, RPH, etc.

Ø Predicting Staff Demand using Machine Learning models for multiple markets

Intend of the project to develop an automated VoiceID verification system by conceptualization of Signal Processing and Advance Machine Learning Algorithms to identify Fraudulent and Genuine Calls from alerted audio calls of HSBC Contact Centre.

An automated business assistive system enables customers to know their application E-2-E journey such as Estimated TAT, status of application, queue level TAT, approval TAT, decline reason, mean wait hour, etc.Assists in operations floor for understanding Application volumes, Agent RPH and other KPIs, Priority Application Status, Cancellation Reason,etc.

Forecasting daily staff demand for application verifications at operations floor for HSBC sub products such as cards, loans, mortgages, cli and overdraft. Project rolled out for most of the countries where HSBC branch exists.

Intend of the project to develop supervised models for closing price of nearly 6000 stock tickers available under NYSE and NASDAQ and perform intraday prediction for all stocks. These models will help customer portfolios to study future behaviors/trends individually and benefits them in terms of monetary aspects.

Intend of the Project for Cluster analysis of call handle time vs. various factors such as skill, campaign, customer gender, geographic areas, age, agent, background etc.Predicting Resources needed in order to improve overall productivity as well as Wrap up Time, Queue Time, Hold Time, etc.AnalyzingResource &Agent Reliability by applying Predictive Modelling to optimize cost of the organization.

Intend of the project is to understand the impact of climate change on cryospheric contribution to rivers in western Himalaya and the subsequent impact on water resource availability and socio- economic status of the localcommunity.