Successful end-to-end BI Solution implementation for an NBFC

We implemented an end-to-end BI Solution for a large Non banking finance company in India right from Data Engineering to ML based report creation to Analytics Dashboards to usage of Narrator tool to overall data & dashboard automation.  We describe the case study in detail here End to end BI solutioning

 

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Finalytica Aug-2021, Knowledge Series: The Journey of Auto Machine Learning through Clientrator

 Automated machine learning, also referred to as automated ML or AutoML, is the process of automating the time-consuming, iterative tasks of machine learning model development.. Creating a Machine-learning/Data Science model from scratch is a time-consuming and long process which has multiple stages and requires multiple iterations.Continue reading

Finalytica June-2021, Knowledge Series: NLP based automated insights & Application in Narrator

Why Insights?

Insights derived through Natural Language programming are used to solve the problem by providing key statistical highlights of the data, extracting valuable insights which are key pointers for business to act upon, and prescribing actions to be taken, given the current state of data to improve the decision-making process.… Continue reading

Finalytica April-2021, Knowledge Series: Technologies in BI Solutioning

Business intelligence (BI) comprises various strategies and technologies used by enterprises for the data analysis of business information. BI technologies provide historical, current, and predictive views of business operations. Common functions of business intelligence technologies include ETL, online analytical processing, analytics, dashboard development, data mining, process mining, complex event processing, business, benchmarking, text mining, predictive analytics, and prescriptive analytics and reporting.Continue reading

Finalytica March, 2021: End-to-End BI Solutioning

Business intelligence (BI) solutions combine business analytics, data mining, data visualization, data tools and infrastructure, creating data models and helping organizations to make more data-driven. All of these things come together to create a comprehensive view of a business to help people make better and actionable decisions.… Continue reading

Experiential learning: Expected Credit Loss Framework

What is Expected Credit Loss (ECL)?

Based on a risk, banks and financial institutes want to take actions in these rapidly growing financial markets and one of most important risk that they are exposed to is credit risk. ECL is used to recognize the impairment losses arising from potential defaults in future.… Continue reading

Best and most read G-Square articles of 2020: Knowledge Series & Experiential Learning

1. HR Analytics

HR analytics is better known as workforce analytics and plays a very important role in all the organisation in terms of improving the employee performance and retention.  Problem statements which can be answered using HR analytics are: Manpower: How to optimize the manpower based on the manning in different locations.… Continue reading

Finalytica Dec, 2020: Human Resource Analytics

Background to HR Analytics

HR analytics is better known as workforce analytics and plays a very important role in all the organisation in terms of improving the employee performance and retention.  Problem statements which can be answered using HR analytics are :

  • Manpower: How to optimize the manpower based on the manning in different locations.
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Finalytica Nov, 2020: News Curation

News Curation

 

What is News Curation ?

On the internet, searching for the right kind of news can be a time consuming task simply because sometimes you cannot exactly explain what you are looking for or that the system fails to understand the requirements.… Continue reading

Finalytica Oct, 2020: Analytics-based Collection Models

Analytics-based collection models help banks and NBFCs recover loans more efficiently. A collection model helps a bank or an NBFC identify groups of customers where the collection efforts need to be focused on. Many collection systems even now are just rigid rule-based setups, which only take in limited amounts of data to make decisions and do not change with dynamic factors such as markets, client behaviour, their actions, repaying patterns, etc.… Continue reading

Finalytica Sep, 2020: Experiential learning

Credit Risk Analytics: Macroeconomic modelling for Bank for PD impact

Background

One of the Banks wanted to predict the impact of Covid scenario on futuristic PIT Probability of Defaults (PD) for their portfolio considering the current environment for this year and subsequent years.… Continue reading