Importance of analytics and use cases

1. Analytics in
Finance

2. What is
analytics in
Finance ?
 Financial analytics is a term that offers distinct views
of the financial data of the organization. It helps to
have in-depth information and take tactical action
against them to boost the overall performance of
your company. It plays a crucial role in measuring the
income of your business.

3. Different use cases of
Analytics in Finance

4. Consumer
Analytics
 As their biggest activity, several financial companies have
customer personalization.Using real-time analytics to make
better strategic business decisions, businesses may gain insight
into the actions of customers in real-time with the aid of data
analytics.
 In many financial firms, such as insurance companies, Data
Science is used to understand the market by removing below zero
customers, increasing cross-sales and calculating a customer's
lifetime value in order to minimise losses.

5. Customer
Data
Management
 Data is everything, and consumer data is needed for the financial
institution to process and interpret the information.
 After the advent of big data in the field of data analysis, the
operation of financial institutions was fully revolutionised.
 The diversity and volume of data has contributed a lot to huge
amounts of purchases and social media.

6. Financial
Fraud
Detection
 Fraud is one of the main problems for financial institutions. If the
number of transactions is growing, the risks of fraud are also
growing. But now, by using computational instruments to analyse
big data, financial institutions can help keep track of scams and
frauds.
 Using different machine learning techniques, peculiar trends in
trading data are established. It warns financial institutions and
takes the irregularities for further investigation.

7. Algorithmic
Trading
 AlgorithmicTrading, which is used to calculate complicated
mathematical functions at lightning speed, is one of the key
components of financial institutions and allows financial
institutions to build new trading techniques. In a much larger
extent, Big Data has totally revolutionised DataAnalytics and
Algorithmic Investing, leading to a complete transformation in the
operation of the industry.
 Significant volumes of data that are processed by algorithmic
trading are distributed and a data model is generated that
explains data stream information.