{"id":2430,"date":"2018-04-24T08:56:56","date_gmt":"2018-04-24T13:56:56","guid":{"rendered":"https:\/\/opsdog.com\/resources\/?p=2430"},"modified":"2020-05-18T16:58:15","modified_gmt":"2020-05-18T21:58:15","slug":"big-data-in-banking-wall-street-results","status":"publish","type":"post","link":"https:\/\/opsdog.com\/resources\/big-data-in-banking-wall-street-results\/","title":{"rendered":"Big Data in Banking 101: Top Ways You Can Improve"},"content":{"rendered":"

It\u2019s a question we hear all the time: \u201cHow can my company use big data in banking?\u201d<\/p>\n

The short answer is: \u201cLots of ways.\u201d Here at OpsDog, we\u2019ve got scads of experience with big data in banking, based on our work with banks of all sizes, across the country. We\u2019d like to share some of that experience, and the insights it generates, with you in this article.<\/p>\n

What is big data in banking?<\/strong><\/h2>\n

Before we go too in depth into the ins and outs of big data, first we must define it. Big data in banking is defined as data sets that extremely large in volume and variety in the banking industry that it can not be dealt with in traditional ways, therefore is analyzed with software to bring banking trends and patterns to light, which can be used to make more informed decisions inside a bank.<\/p>\n

First things first, however. \u201cBig data\u201d is a fashionable catchphrase, but wield it with caution. As we\u2019ve said numerous times in these blogs, \u201cbigger\u201d doesn\u2019t automatically mean \u201cbetter.\u201d The data must be clean. It must be available. It must be relevant. And it must be wrangled in a way that gives you actionable insights. That may sound like an IT challenge. But don\u2019t be fooled. It\u2019s a business challenge. Sure, it takes IT skills to clean and wrangle data. But it requires business acumen to assign the right<\/em> information to your big-data-in-banking challenge. That\u2019s where you\u2019ll get the KPIs that matter.<\/p>\n

\"A<\/a><\/h2>\n

The interplay of big data in banking and data science in retail banking <\/strong><\/h2>\n

You needn\u2019t be a Wall Street behemoth to have a lot of big data in banking. While we work with these mega-banks all the time, we also apply data science in retail banking to local and regional banks. They may be small, but their data is big.<\/p>\n

What, then, is data science in banking? It\u2019s a field of analysis that combines different scientific methods and systems to wring knowledge from banking data. You might know it as data analytics, business analytics, or even business intelligence. There are lots of names out there, but the goal is the same: transforming all that big data into profitable decision-making.<\/p>\n

Transform your business via a big data project in banking <\/strong><\/h2>\n

When working with major banks, we\u2019ll often encounter a disconnect between the senior leaders and the retail banking branches. Everyone knows<\/em> there\u2019s room for improvement. They just don\u2019t know where to look.<\/p>\n

This is where OpsDog can, and does, help. We\u2019ll wrangle the data, clean it, run the numbers, and generate made-to-order insights that provide \u201caha\u201d moments and operational improvement opportunities. Best of all, our teams routinely do all this remotely.<\/em> That\u2019s fast, easy, and incredibly cost effective. It\u2019s the best way to leverage data science in retail banking.<\/p>\n

Properly leveraged, the big data gives a new perspective. We\u2019ll reveal bottlenecks and pain points in operational processes. We\u2019ll suggest improvements ranging from future-state models to employee job aids. We\u2019ll scour our vast library of best practices to help them improve. (You can do that right now! Check out our banking best practices<\/a> which you can download.)<\/p>\n

Big data in banking<\/strong> and investment management: Moving from qualitative to quantitative analysis<\/strong><\/h2>\n

Investment management is a ripe area for big data in banking. If it feels like you\u2019re following your gut, then that\u2019s the wrong feeling. Time to put big data to use.<\/p>\n

The key here is KPIs: key performance indicators. (Want to learn more about what they are? Check out our informative \u201cKPIs 101\u201d articles<\/a>. Want to download the essential KPIs for your bank? Just click here<\/a>.) These are the metrics that really let you visualize performance and correlate it to regions, functions, even individuals. Chances are, you already have tons of data\u2014i.e.,<\/em> \u201cbig data\u201d\u2014on all this. But you need to draw comparisons between the right<\/em> portions of data (the numerator vs. the denominator) to arrive at the KPIs that matter.<\/p>\n

But once you do, the power of big data in banking really pays off for you. Whereas before you had to rely on qualitative factors, now you can quantify and visualize them. The new quantitative data can help you lower cost, increase productivity, and improve the customer experience\u2014not a bad outcome!<\/p>\n

\"ultimate-guide-of-benchmarks-for-banks\"<\/a><\/h2>\n

Big data in banking<\/strong>\u2014the OpsDog way<\/strong><\/h2>\n

Here\u2019s how we tackle a project like this at OpsDog. When we work on big data in banking projects, we take data from multiple sources and aggregate in a way that makes sense for our clients (i.e.,<\/em> you). The best part? We work with you to identify what data exactly works best for your needs. That way, everything matches and matters to your bottom line. Need data for behaviors or opinions? Lacking insight into internal performance data? All that and more is possible with big data.<\/p>\n

By the way, if it wasn\u2019t clear to you, know that OpsDog offers products and<\/em> services. The products are the things like KPIs<\/a> and best practices<\/a> that you can purchase (inexpensively!) and download (instantly!). The services are customized, like when we remotely wrangle your own data for you, and deliver things like beautifully informative dashboards, as we\u2019d described above. Learn more about our custom services here<\/a>.<\/p>\n

Big data in banking, simply put, brings improved volume and variety to data sets. It also makes aggregating data, once cleaned, faster. We bring it all together to improve your banking services. Contact us<\/a> today to get started.<\/p>\n","protected":false},"excerpt":{"rendered":"

It\u2019s a question we hear all the time: \u201cHow can my company use big data in banking?\u201d The short answer is: \u201cLots of ways.\u201d Here at OpsDog, we\u2019ve got scads of experience with big data in banking, based on our work with banks of all sizes, across the country. We\u2019d like to share some of […]<\/p>\n","protected":false},"author":9,"featured_media":2511,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[214,238,237,239],"yoast_head":"\nBig Data in Banking 101: Main Street Roots, Wall Street Results - OpsDog<\/title>\n<meta name=\"description\" content=\"\u201cHow can my company use big data in banking?\u201d How much time do you have? It\u2019s a question with arguably thousands of answers. Luckily for you, we have years of experience with big data and banks of all sizes. 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