How to Use Big Data Analytics in Finance

The finance industry is up against massive challenges as 2023 shapes up to be a tumultuous year for the market. The closure of Silicon Valley Bank signaled another big fall in trust, and businesses are scrambling to make sure that they’re providing security and safety alongside their normal client services.

Now more than ever, it’s critical that companies have trustworthy ways of performing their practices, finding new investments and conducting research. And all of those boxes can be checked off in one fell swoop when companies begin using data analytic tools.

In this blog, we will outline the ways in which big data can help financial professionals. Use this as a checklist for how to implement the tools, with an in-depth and researched description on each issue.

Increase customer satisfaction with customer insight and analytics

Customer satisfaction is at the forefront of everyone’s minds in this current financial climate. After the SVB failure, consumers are extra wary of making new investments or entrusting their assets to both familiar and unfamiliar third parties. To combat this, data analytic tools use automation and AI to secure and report on customer analytics.

Rajat Jhingan from Akounto Inc. points to Dickey's Barbecue Pit as a great case study for how big data can help improve the customer experience; in a recent report, Dickey’s CEO said that the trial of using big data in a smaller setting is so successful that the chain plans to roll out the process across 350 restaurants. Dickey’s stakeholders use data analytics to oversee restaurant performance, customer concerns and to project sales numbers.

Ultimately, Dickey’s use of big data has helped them better understand consumer needs. CIO Laura Dickey said: “Its biggest end user benefit is bringing together all of our different data sets from all of our source data – whether it’s our POS system in stores directly capturing sales as they happen, or a completely different source such as a customer response program, where folks are giving us feedback online or in different survey formats.”

Use big data for predictive analysis to make informed investment decisions

Another massive benefit that big data tools have to offer is with predictive analysis. Using a non-biased equation to spot trends in numbers is a fool-proof way to estimate future earnings and losses. As Jhingan puts it, “Data analysis helps crunch big numbers enabling real-time market insights, risk assessments, and other crucial metrics.”

In one case study, Uber used big data to analyze the demand of cars in certain areas. They implemented machine-learning algorithms to pick up on when demand was on the rise so they could alert more drivers and, ultimately, induce surge pricing to benefit from higher demand.

This can be applied to the finance industry for even bigger company gains. Jhingan points out the example of BlackRock’s Aladdin platform, which “integrates information from various sources, including market data, economic indicators, and news, to provide a comprehensive view of market conditions and help inform investment strategies.” This in turn allows BlackRock to confidently suggest new investment opportunities and hold a critical eye at potential areas to be wary of.

MORE: Top 3 Ways Financial Research Can Help Your Portfolio Through Tech Layoffs

Detect potential fraud with transaction data

Fraud and hacking are both on the rise right now. To assuage these concerns, companies can implement big data practices that serve as fraud detection algorithms and alert consumers and stakeholders to suspicious activity.

American Express has shown a great deal of success with using big data for fraud prevention. The company began investing in big data in 2010, and now, “In less than a second, American Express’ ML algorithms and fraud prevention tools analyze thousands of data points of merchant and cardholder alike to minimize the risk of fraud.”

Improve risk management with big data and advanced analytics

Advanced analytics and deep dives into data can allow for companies to build a better understanding of the long-term, big-picture view of their own finances and the finances of the investment opportunities they trust. This happens not just with the aforementioned fraud detection abilities, but also by analyzing credit data and detecting downturns.

As Jhingan points out, JPMorgan Chase have used big data to successfully mitigate risk. “The Corporate & Investment Bank (CIB)'s solutions include predictions, pricing models, client intelligence, virtual assistants, news analytics, and anomaly detection. These techniques have allowed JPMorgan Chase to reduce its risk exposure and enhance the stability of its operations.”

MORE: Achieve These 3 Goals for Financial Services with Timely, Well-Researched Business Intelligence

Leverage finance data APIs for better compliance

When it comes to running the numbers side of a business, compliance is a huge concern. Businesses want to ensure that their data is coming up clean and that there are no issues like criminal activity, money laundering or fraud happening under their radar. By automating the process of scanning data, stakeholders can rest assured that any and all red flags will not slip through the cracks.

In a blog about the benefits of big data, CEO Views writes that “If you are in the process of obtaining compliance certifications, you must maintain the risk associated with sharing the data with vendors appropriately. Big data analytics can help you manage vendor-related risks.”

Research big data for insight into financial trends and better forecasting

Financial data is helpful for specific company reports, but it also applies in a more macrocosmic setting. Beyond simply tracking businesses and monitoring consumer data, big data tools will help financial providers to see the market as a whole and gain insight into larger global and national trends.

Walmart makes great use of this ability by bringing larger trend reporting, such as weather forecasts, into its business strategy. The company boasts of improving consumer experience by optimizing the checkout process, identifying and avoiding supply chain blockages and even predicting a customer’s future purchases based on their areas of interest.

Use technology to streamline your financial services research

As the world transitions into a more tech and AI-forward culture, businesses need to find ways to use technology to their advantage before they fall behind. Big data tools provide many helpful features that can result in improved customer experiences, risk mitigation, better investment recommendations and increased security across the board.

Nexis offers a trustworthy tool where companies can dive into tons of data from thoroughly vetted sources, all in one easily-searchable place. The Nexis Dossier function expands access to data by offering business snapshots and reports that are automatically built for you. Start your free trial today to witness how your business improve with the help of big data tools.