How Can Big Data Play a Role in Financial Risk Management?
Big data is one of the most significant trends in digital transformation today, with more and more companies leveraging the power of big data and complementary technologies such as machine learning and artificial intelligence (AI). As with all digital transformation projects, big data must be taken into consideration as financial companies develop and refine their risk management strategies. This is especially true for banks, financial services providers, and other companies in the financial space since these companies tend to have rather complex risk management landscapes.
What is Big Data and How Will it Affect Financial Institutions and Their Financial Risk Management Efforts?
Data often accounts for a company’s most valuable asset and this is especially true in the case of big data. Big data refers to massive data sets that serve as the basis for comprehensive analysis. Typical analytics software simply cannot handle big data; new, innovative computational and analysis software is required to process these massive data sets and the output can be quite remarkable.
Today’s companies within the financial sector and beyond are leveraging big data to gain important insights into customer behavior patterns, financial industry trends, and stock market trends, amongst other things. Generally speaking, these are insights that would otherwise remain elusive. But these voluminous data sets — when processed and analyzed by software with technologies such as artificial intelligence and machine learning capabilities — can reveal trends, patterns, and predictions that would otherwise go unrealized.
The financial industry is one where companies can see a significant advantage from future predictions and trend identification. For example, identifying consumer trends could position a bank to tailor its service offerings in a manner that more effectively resonates with prospective clients. Similarly, a financial services company that is able to generate accurate stock market predictions could make more effective recommendations to its investors. The analysis of big data can be leveraged for a variety of different purposes, whether it is investment consulting or refining a bank’s service offerings so they more effectively reflect a customer base’s priorities and concerns.
How Does Big Data Play into Financial Risk Management?
Big data is tied to financial risk management in a couple of ways. Firstly, a financial institution must consider big data as business leaders develop and refine the company’s risk management strategy. Data sets are commonly targeted by cybercriminals who may seek to steal data and even hold it for ransom. Unauthorized data access is a very real concern for today’s modern companies, particularly banks, financial institutions, and others in the financial business space — an industry that is a prime target for cybercriminals.
Data loss and unauthorized data access must be considered as part of a financial institution’s risk management strategy. The larger the data set, the greater the value, which means that big data is especially vulnerable and in need of protection. What’s more, a bank can easily lose consumer trust if their data is stolen or accessed by bad actors. The damage can be especially extensive in cases that involve the use of big data simply due to the massive volumes of data and the sheer number of customers who may be affected by a breach.
Security must be a key component in a company’s risk management strategy and this is particularly important for financial institutions that are dealing in big data. The financial space is frequently targeted by criminals. These valuable data sets must be protected and guarded, lest they fall victim to cybercriminals. For instance, financial institutions must ensure that their data is encrypted while in transit and while at rest in a data storage environment. Encryption protects data integrity, making it useless to a criminal if the data is accessed without authorization. Additionally. data storage platforms must have a secure architecture and robust monitoring mechanisms. These monitoring tools are configured to send alerts and notifications to the company’s IT admins in the event of a breach or other anomalous activity. This ensures a prompt response in the event that the organization’s data is subject to a data breach or involved in some other type of cybercrime event.
Big data also plays a role in financial risk management when it comes to predicting the vulnerabilities and threats that a bank or financial service provider may soon confront. After all, the most dangerous threats are those that go unrealized until it’s too late. A sufficiently large data set can offer keen insights into human behaviors, trends, and patterns. This information is then analyzed and processed in a way that allows an organization to identify the unrealized and unappreciated threats that may affect a bank, its customers, and their interests. By identifying threats and vulnerabilities, a financial institution is better positioned to develop an effective risk management strategy — a strategy that can be deployed to avoid, mitigate or minimize losses.
Big data is very useful for companies that are seeking to develop predictive models too. The larger the data set, the more accurate a predictive model tends to be. This makes big data ideal for organizations that can benefit from insights into the future, whether it’s predicting consumer trends or developing a new security strategy.
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Harnessing the Power of Big Data for Your Financial Institution
The right technology is essential if you’re going to make the most of your big data. Without a well-developed analytics platform, big data brings little benefit. The value lies within the analysis and predictions that are derived from these massive data sets.
At iTech, our expertise spans all aspects of data management and big data analysis. Our analytics and data solutions are designed to provide clients with the tools and technology they need to make the most of their data. In short, we create technology that empowers companies, allowing them to analyze big data sets in a manner that brings maximum benefit and ROI. iTech’s innovative development team specializes in a variety of big data-friendly technologies such as artificial intelligence and machine learning. Contact the iTech team today and let’s discuss a strategy to leverage your financial institution’s big data.