Every facet of the business world has been radically changed by the way data is collected, analyzed and transmitted. So much so, that past models of how major industries were run have now become largely obsolete. Data analysis is considered the “gold standard” by which companies look at the future.
To some people, this approach seems cold or overly “corporate.” However, it gives businesses and clients a direct advantage when finalizing transactions within an increasingly short period of time. This is because much of this “big data” is collected in response to issues as they occur.
Large amounts of information are compiled so that trends can be closely studied. Facts and figures are dissected, as if they were subjects in a scientific experiment. At that point, vital bits of information can be expertly chosen and designated for further investigation.
In the world of finance, the use of big data has made a significant impact on the methods in which purchases and investments are made. Nowhere is this more evident than when financial institutions look into real estate investments. By surveying trends as they form in data pools, decisions are made as to how banks can reduce their own risk. With their own financial risk lessened, commercial banks are therefore able to pass along favorable rates to their own clients.
Big data assists banks in understanding the needs of their customers. As data is closely scrutinized, ideas often emerge helping banks to better direct their marketing efforts to groups that might otherwise be underserved by their financial institution. This is true for their customers who merely want to open a basic checking account without fees, as well as necessary for major clients who require additional tools to manage their wealth.
Sorting through this data also works so lenders can better adhere to state and federal regulations. Experts in risk management are able to look at just how customers use services not only in past endeavors, but in real time transactions. This analytical awareness of financial models is the key to reducing and eliminating electronic fraud.
Banks are able to use this data wisely, especially when it comes to the purchase of real estate and how it is insured. Data gives out distinctive clues as to how new homebuyers, start-ups and business owners looking to purchase commercial property will further their investments. This is crucial before extending a risky loan or in cases where similar investments have failed in the past.
It is possible to use big data tools when insuring a house, commercial space or property as well. Every variety of insurance coverage now depends on information gathered from digital data sources. While insurance companies are naturally looking for methods in which to increase their own profits, they are also looking for how to better serve their clientele.
To offer more comprehensive insurance policies for property owners, insurance companies need to analyze data from large numbers of users. They study what types of insurance are necessary for a particular geographic region or type of dwelling. This can come down to offering earthquake, flood or hurricane insurance as a standard part of their policies to attract new customers.
When looking at realty investment, this risk also extends to the gentrification of once forlorn neighborhoods in urban areas. Using the results of data surveys, insurance companies and financial institutions decide whether to involve themselves in new real estate projects. Using risk analysis, they are better able to estimate what future claims may occur now and in the distant future.
Every homeowner knows that they must have homeowner's insurance as a requisite for maintaining their mortgage. This is based on banks and mortgage lenders using data provided by insurance companies to protect their investments. While data alone is not able to ascertain whether a house at a certain address will suffer from calamity, it is usually able to serve probable warning.
Consumers benefit from how this data analysis determines their insurance rates. Current property values can both positively or negatively affect insurance premiums. Data that is gathered from reliable sources allows insurance adjusters to see value in properties that may not seem reliable on the surface. However after looking at long term data, such property or land investments may be worth a second look.
Investing in real estate has traditionally been seen as an educated gamble or game of risk. No matter how well planned a purchase may be, there is always a chance that things could go seriously wrong. With proper data evaluation tools, companies dealing in real estate sales, investment and insurance are better able to offer reliable predictions. In addition to improving their own profits, they are now able to better assist current and future clients.
This article was originally posted/written by RisMedia.