The evolution of big data has changed the way we do business. Financial institutions are now accustomed to having real intelligence about their clients and target markets available on demand. Analytics enable us the use of data to predict the future in a way we could have previously never imagined, by providing actionable insights into behavioral patterns. While the benefits of having this detailed information are significant, conducting in-house analytics to produce the intelligence creates risks that aren’t always readily identifiable. By engaging a solution provider whose core competency is delivering analytics solutions, however, you can mitigate several of these risks:
The Human Factor
One of the primary issues experienced by financial institutions is that in-house analytics and reporting often reside with individual employees. When a key team member resigns or is recruited by a competitor, that robust reporting you’ve relied on can disappear in a day. Even if other employees can absorb the responsibility of managing your corporate data, this can result in the neglect of other duties. A potential solution to this is to automate your reporting as far as possible, through methods such as the engaging an analytics solution provider who understands your business.
The use of big data technology typically enables direct input from vendor companies to your core processing and ancillary financial systems. The information is critical for accurate analysis and reporting, but the use of multiple different systems can make for an extremely complex environment. And if one vendor’s input source changes, and programming isn’t done, it can result in a gap in data. It’s essential to be able to remain agile in your choice of operational systems without the risk of losing reporting and analytical capabilities. By engaging with a centralized analytics provider before this occurs, you should be able to unplug one vendor and plug in another without compromising the quality of your intelligence.
In many financial institutions, big data is stored in isolated silos, requiring data scientists to dedicate significant time to cleaning and integrating with other information. According to the New York Times, this “janitorial” work takes more than 50 percent of analysts’ time and is a major hurdle to getting the insights institutions need. This creates questions around the quality of the regulatory reporting, particularly when results are delayed and the intelligence is potentially out of date. You can mitigate this risk by engaging with a provider whose core competency is ensuring that this process is done effectively and efficiently.
It’s a fact that the initial costs of implementing a big data analytics solution can run into hundreds of thousands of dollars. Given that an elongated implementation cycle takes place before the client is likely to see a real benefit and value, this is a financial risk to any firm—regardless of the solution’s importance. By outsourcing to a qualified solution provider, you can avoid incurring these types of costs, which mitigates the risk of tying up funds until you start to realize results.
Outsourcing your financial institution’s analytics to a company with a blend of passion and experience gives you the benefits of mitigating risks in a cost effective manner, while still enjoying a superior ROI. The cost of implementing JOHO OneSource™ is broken up into stages that reflect agreed-upon milestones in the process, also giving you a chance to receive the true value of the solution before making your total investment. This saves you from unexpected delays and missed deadlines where your new system is not providing an ROI.