Financial institutions were slow to adopt business intelligence technology and lowered lending standards, contributing to the spread of toxic loans. Bringing data together through business intelligence can help institutions make better decisions by providing visibility into loan quality, risk exposure, and package contents. Clean, integrated data is needed to power these analytics and help the financial industry avoid similar crises in the future through improved data management, governance, and decision making.

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Adding Value with Business Intelligence
industry chAllenges: PrOBleMs whAt cOuld Be dOne next And
with finAnciAl institutiOns hOw Business intelligence
Financial institutions have been slower to cOuld helP?
adopt such technology. Enthused to simply get We should realize that information/
mortgages out the door, financial institutions data/business intelligence has increased
repeatedly lowered standards. Agents pushed visibility and transparency in our financial
paper in the market knowing well that many of institutions.
the loans had little chance of being repaid. It starts with getting the data together first
Now, the question arises how did such bad because if clean data is not captured and
mortgages become so prevalent in financial integrated, there is nothing valuable for the
institution? Why these financial houses weren’t technology to work on.
motivated to receive the payments? Why did In the context of acceptable risk
they sell the mortgages for present values that determination, institutions will need to bring
approximate full payment? I think we know data to bear in two areas of the financial
the answer. In other words, these institutions business: 1) the business (mortgages) they
Arvind Agarwal were letting others to hold the bag. The write and 2) the packages they buy. The
Vice President & DWBI Global Practice Head
problem is, while the clever bankers on the mortgages written by the institution will need
inbound side were writing the mortgages and to be tighter as the buying market for toxic
they were selling them, there had to be buyers loans dries up. Supported by data, toxic loans
T
he American economic slowdown and and on the outbound side many of the buying will no longer be able to be sold. Institutions
subsequent global financial crisis were
perhaps the biggest economic disruptors
in recent past. Who can ignore the shock waves
about Goldman Sachs, Merrill Lynch and twin
failures of Freddie Mac and Fannie Mae and the
biggest – Lehman Brothers Fall Out? While the
financial system seems to have regularized; and
a number of economic policies (like the Dodd
Frank Act, etc.) are being positioned for growth,
the overall economic environment remains
highly volatile. Recently I heard the Japanese
economy is in recession. The Indian stock
market also lost half of its value and the FDI
and FII cashed out and took away 12 Billion
USD from the Indian market. Organizations
worldwide are seeking a trajectory for recovery
and success in the post-crisis environment.
A relevant posturing in this milieu is - what
can organizations do to help successfully manage
uncertainty and complexity to foster growth?
Some answers to these questions will involve
the management of information which is
also known as Data Management or Business
Intelligence. Business Intelligence (BI) refers
to technologies, applications and practices
for the collection, integration, analysis, and institutions also happened to be the same selling will hold the bag. However, I believe this
presentation of business information. institutions! While toxicity was going out the all starts with the market controlling itself
BI systems provide historical, current, and back door, it was coming in the front door. In in terms of the packages they buy. Full
predictive views of business operations, most BI language we call it lack of data governance loan lineage within each package must be
often using data that has been gathered into a and data management. made accessible. In BI terms, we call this
data warehouse or from operational data. The complicated packaging of loans that had metadata.
It is also described as a Decision Support been subdivided into little pieces elevated the Full visibility into exposure via Information
System (DSS) since the purpose of Business valuation of some pieces to that of some of the Management/Business Intelligence tools and
Intelligence is to support better business better loans in the package. This made it difficult liquidity is going to be a necessity. Getting the
decision making. If implemented properly to tell what was actually being bought. You would data act together in financial institutions will
and supported by data, the technology exists think prudence would be in order, given that the not be an overnight sensation, but neither was
to mine the offers and consider factors such financial buying institutions were selling in the this mess created overnight. With realigned
as demand, location, and temperature and same fashion, but within the companies, the back priorities, the financial industry competitive
other product requirements, warehouse space room didn’t know what the front room was doing battlefield will move to the information front,
and price. Technology also exists to suggest and vice versa, or maybe these financial behemoths where most industries are today. This Data
a recommended decision with confidence. had grown so large, huge and important on paper Management, Governance and Data Profiling
Without compounding bad decisions, companies that they believed they could not fail and even if will all add value to economies and hopefully
that make informed decisions based on information they fail, they would be saved somehow. Some manage uncertainty and complexities that
from their BI systems have healthy bottom lines. institutions won at this level, and others did not. may arise in the future.
2 May 2011