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

Finalytica Aug 2020: Experiential Learning: Text Extraction from PDFs

Relevant Text Extraction from PDFs

Data extraction for analysis can be as challenging as it is important to an organization with data available in sources of different sizes and formats. For this very purpose, we can use one of many techniques or multiple methods in combination to extract text and clean it, so as to make it as readable as possible to the end user.… Continue reading

Finalytica July, 2020: Knowledge Series

Price Optimisation through Machine Learning for Retail Stores

Introduction

Price optimisation refers to determining the prices of products/services such that the company can achieve its business objectives. In recent times, there have been major technical advancements in this field with more reliable and faster techniques.… Continue reading

Finalytica Feb, 2020: Knowledge Series

An overview of clustering in analytics

Just as the name suggests, clustering aims at creating clusters of the subject matter at hand, based on the various properties it possesses. This can be pretty useful when it comes to classifying elements in the future, into one of these clusters or in terms of establishing patterns in the data.… Continue reading

Finalytica, Knowledge Series: Jan, 2020

Time Series 101 : Everything you need to know about Time Series

Time is always an important factor when it comes to observing patterns or forecasting trends, be it predicting stock prices or future sales of products. For example, if the expected sales of a product are supposed to take a hit, a company can take various measures to stunt that fall or even improve the performances.… Continue reading

Finalytica: Experential Learning, Dec 2019

Credit Risk Assessment

Credit Risk assessment is a critical issue that Banks face nowadays. Which basically tells if a loan applicant can be a defaulter, so they can go ahead and grant the loan or not. This helps the banks to minimize the possible losses and can increase the volume of credit given.… Continue reading

Finalytica Nov-2019: Experential Learnings

AI Driven Narrator Chatbot – Use Cases

A chatbot is a machine that has a conversation with humans via text or audio. An AI powered chatbot is a smarter version which uses natural language processing (NLP) and machine learning (ML) to better understand the intent of the data and provide a more natural, accurate insight.… Continue reading

Finalytica, October, 2019: Experential Learning

Automated MIS Reports and triggers application through BI tool – Narrator

Introduction

A MIS Automation is an automatedreport, analysis of business or management information organized and programmed in such a way that it produces regular reports on operations for every level of management hierarchy in organization.… Continue reading

G-square's narrator

Finalytica July, 2019: Experiential Learning

Prescriptive Analytics for Sales: Combining Analytics with Business Understanding

BI and reports have been driving salesforce in an organization for some time now. But building reports manually on a monthly / weekly / regular basis is daunting, boring, and error prone.… Continue reading

Finalytica June, 2019: Experential Learning

Credit Risk Rating Using Supervised ML and Business Understanding

The risk rating models are designed to help assess the likelihood of default. Assessing risk at the loan level provides an opportunity to aggregate risk at the portfolio level and can help to quantify the risks based on the type of loan, geographic location or region, industry sector, or other variables including financials.… Continue reading

Finalytica May, 2019: Experential Learning

Converting Content to a Chat-Bot

The best way to learn or understand information is through asking questions. A QnA format of learning is more effective than reading long form content, especially when time is critical. More over searching for an information and reading multiple documents just to know one thing is inefficient.… Continue reading