Analytics in Financial Services

Banking and Financial Services has traditionally been the biggest users of Data Science and Advanced Analytics. With the rapid spread of the Internet and new channels of data generation, Financial Services Industry has been at the forefront in using Data and Advanced Analytics for transformation resulting in customer delight, better management of Risk and Fraud.  

Some of the use cases that help our customers use Data and Data Science to solve business problems are 

  1. Customer Analytics for Banking 

Organizations can take advantage of new sources of data to better target intended customers to specific, and potentially more suitable, products. Analysis of trends in preferences and behaviors improves understanding of changes in consumer needs, and this insight can be useful in the development of innovative new products and design of product features. At Coforge we help Financial Service companies in building Customer 360-degree views, Campaign Analytics, Customer Segmentation, Cross-Sell & Upsell, Recommendation Engine, Clickstream Analytics, Social Media Analytics, Sales Forecast, Customer Experience Analytics, and Sales Analytics. 

  1. Portfolio Optimization 

Portfolio Optimization is an advanced analytics solution that uses data science to analyze portfolio performance. It combines structured data (Historical Stock Price Movements, Portfolio Weights, Benchmarks) and unstructured data (text from news articles) to provide actionable insights into portfolio performance. 

  1. Risk Analytics 

Risk Analytics solution enables our customers to manage credit risk by estimating the probability of default, Loss Given Default, and Exposure at Default. The Risk score can be computed at an individual level as well as account level. 

  1. Investment Research 

Investment Research solution enables our customers in idea generation and advances research for finding new investment opportunities for significantly higher returns and calculated risk. It helps to understand the company’s performance with behavioral datasets like foot traffic, parking usage, web traffic, social, satellite imagery, etc. This helps in reduced Investment Research time and effort with AI-based Search & Analysis of structured & unstructured data. The solution enables ingestion & processing in real-time, large volumes of data to unlock Risk analytics, Allocation analysis, and Regulatory Alert & Historical data analysis.  

  1. Conversational Analytics for Debt Collection 

Conversational Analytics solution for Debt Collection uses Conversational AI to create agents for Debt Collection and multiple other back-office functions. 

  1. Trading, Investment, and Market 

The trading, investment, and market solution have various components for the automation of LIBOR transition, Intelligent Document tagging, Financial Document summarization with sentiment extraction, Contract data extraction from contractual documents, and investor risk profiling. 

  1. Brand Influencer 

Our solutions like Brand Awareness, Competitor Analysis, Sentiment Analytics, Topic Models, Brand Influencer uses Social Media data (Twitter, Facebook, etc) for making strategic decisions.    

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