Today financial service
firms face more and more regulation. The
reporting landscape is complex and constantly evolving. Financial institutions are pressured to
present increasingly timely, accurate, and comprehensive reports. Another added complication is that as
financial firms move into different sectors than have to comply with different
regulations. Considering the trend of financial
instructions merging with each other and expanding this can become a
challenge.
Big data is everywhere
today. Almost every business can benefit
from it; as we saw with the vast amount of uses even sports teams have for it
at the presentation last week. Big data
can help businesses perform better, and in this case prove truthfulness to the
public. The way firms have to meet these
regulatory requirements is by compiling massive amounts of data. The issue with this is that systems that many
firms have collecting the data.
Companies started collecting this data on legacy systems and as the
workload piled up the firms did not update their systems. The old systems struggle to keep up with the workload;
data availability, system functionality, and data integrity are compromised. Regulations require volume, complexity, governance,
and transparency that many legacy systems cannot handle. Because regulations change so often it is far
too costly for firms to continually update the legacy systems to meet the new
rules.
The solution for these
firms is the same as it was for BNY Mellon in their merger. Although costly and time consuming by
overhauling their systems they can not only meet changing regulations but also
improve their business. By upgrading the
better big data management and analytics tool, firms can accomplish four
things, speed, accuracy, control, and comprehensiveness. Small nimble servers can be easily upgraded
and changed to update the system as a whole.
By compiling all the data from what was in a multitude of places into
one place allows the systems to identify potential problems much sooner. This also adds to the accuracy factor since
all the data is in the same spot. These
benefits free up employees to do more productive things with their time. Not only will employees not need to monitor
the systems as closely but they will save an enormous amount of time by not
having to go back and fix mistakes that went unnoticed for months since the new
system will identify them much sooner, making them much easier to fix. Having the information combined in one place
gives the firm better control over it as well as a comprehensive view of the
data.
Firms should phase out the
legacy system as they implement the new system.
To do this effectively institutions must have a well-planned integration
period. New data management and
analytics tool will help financial service firms create a comprehensive view of
their trading systems, CRM systems, network and operational logs, decision
support systems, etc. This will provide
the firm with the control, accuracy and speed they need to comply with changing
regulations as well as opportunities for their businesses to perform better.
http://www.wallstreetandtech.com/data-management/how-big-data-analytics-helps-financial-institutions-navigate-todays-regulatory-maze/a/d-id/1317362?
1 comment:
The article dictates harnessing data as the solution to meeting new regulatory reporting requirements and keeping pace with constant change. The idea that data analysis is the key to keeping up with the industry is a common one. Time and again we have discussed how big data can change the way that an industry operates, the latest example being the case study of Capital One. But the idea that harnessing data will assist companies in meeting new regulatory reporting requirements is new. I would instead argue that data analytics is the cause of new regulatory requirements, and without the phenomenon of big data, meeting regulatory requirements through harnessing data would be unnecessary. That being said, companies who have been using data analytics do need to keep up with constantly evolving regulations, and I agree with the writer that legacy systems make this next to impossible. The idea that data analytics can be used to make financial reporting more sound and easy is an interesting spin on what I typically think of when it comes to using data in finance. Accountants auditing a company are already using data analytics to detect fraud, so it is only logical that internal accountants employ similar data analysis techniques. The article below gives a greater understanding of how accountants use data analytics in fraud protection, and may spark some ideas as to how companies can use data analytics to meet regulatory requirements.
http://www.wsj.com/articles/accountants-increasingly-use-data-analysis-to-catch-fraud-1417804886
Post a Comment