INTRODUCTION understood and should know what questions need to


Nowadays, company CEO’s and
other heads need to take fast decision making in a right way, without any
errors. Also they need to be careful in monetary terms, since a single minor
fault in financial aspect and fraud in money aspect would spoil the name and future
for not only the company, but also for the stakeholders of the entire company
(as in the case of satyam scandal 10 years before). Hence, analytics when
implemented in finance benefits a lot and makes them time saving. Some of the
articles are discussed below where analytics are used in various places like
auditing, bankruptcy and others.

We Will Write a Custom Essay Specifically
For You For Only $13.90/page!

order now


Cao et al (2015), came
up with a study how big data analytics is used in audits, its characteristics
and issues in implementing analytics for financial needs like auditing. They
have mentioned that analytics can be used in auditing fields to manage the
risks of bankruptcy, to prevent the risks of material misstatement. Analytics
were used in predicting the averages in Dow Jones Industrial Average (DJIA),
where the shifts were predicted three days ahead. Walmart used customers
demographics and managed inventories like selling a day breakfast during
unfavourable climatic conditions to their customers, which increased the sales
to seven fold times. Ayata’s Prescriptive Analytics uses analytics to drill oil
by combining all sources of data like images, texts, structured and
unstructured, retrieved information like images from well logs, drilling
operations sound, videos of fluid flows from hydraulic fractures, text, and quantifiable
data (numbers) from production reports and are progressing well and good. The
paper also discussed the biggest challenges of financial analytics, where
financial analytics may generate false positives and hence it should identify
its anomalies correctly and implement them.


Fitz,(2015), pointed out few ideas which can help financial managers to add
value and ways to implement them. Obtain top management sponsorship to get a
strong support, the need of information should be understood and should know
what questions need to be answered, full range of available advanced analytic
capabilities should be understood, comprehensive gap analysis should be
performed to understand where our data reside, barriers and other privacy laws
should be discussed, to define your transformation strategy and to buy-in the
stakeholder where the author highlighted to start small and further enhance by
building upon initial success, keep building capacity by trial and error and
not to do the entire work in one day, keep checking if the data that got
converted into information adds value to the company, Constantly revaluation of
the performed works should be done, and to accept all these modifications as
change management.


(2016) suggested that the local government faced the problems of financial
sustainability where reformation of financial data was in need. Hence factor
analysis were applied to financial ratio’s, Financial flexibility
like operating ratio and Own Source Operating Revenue ratio, Cash expense,
Unrestricted Current, Debt Service Cover and Interest Cover ratios and Asset
Renewal and Capital Works like Infrastructure Backlog, Asset Maintenance, Asset
Renewal and Capital Expenditure ratios, were summarised as a single financial sustainability
assessment ranging through ‘very weak’, ‘weak’, ‘moderate’, ‘sound’, ‘strong’
to ‘very strong’. All these ratio’s were done with regression analysis and
found the correlation between the ratio’s with the latent factors like population size, number
of employing businesses and population density would be statistically
significant regressors for econometric models employing the dominant factor
loadings as regressands. It was found that three  major latent factors driving the observed
financial  sustainability ratios which
prompted the reform process in the first place. Another important finding was
that the three factors – scale and
density, legacy and management competency acts independently.


Deborah magliozzi
(2017) done an empirical research study that analyses the economic and
financial aspects of national telecom operators in Europe through the
construction of appropriate financial strategic maps profitability map per
market share, Financial autonomy map, Capital expenditure cover map, Current
map, Liquidity mar for Telecom Italia (Italy),
British Telecom (U.K.), France Telecom (France), Deutsche Telekom (Germany),
KPN (Holland), Telefonica de Espana (Spain) and Portugal Telecom (Portugal).
Financial analysis of the operators were done using regression and maps were
formulated where the standard regression equation were done to identify the
uniformity and standard deviation of all the operators in each and every
financial aspects like current assets, liabilities, etc.,