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.


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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.

Categories: Articles


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