How can NLP technology change the finance industry?

No wonder why so many financial services providers are turning to NLP technology: there are a lot of ways it can benefit the financial sector, starting from improving customer experience and ending with ensuring round-the-clock access to data through the application of natural language interfaces to databases.

According to PwC’s Global FinTech Survey 2017 (Figure 1,2), both financial institutions and fintech companies will continue investing in emerging technologies that can make data analytics and existing user experiences better. These include NLP technologies, such as natural language searches and chatbots.

So what exactly is driving this trend?

Customer experience

The first thing that springs to mind in regard to the application of NLP is a more intuitive, human-like customer experience.

Artificial Intelligence makes it possible to derive valuable customer behavior patterns and provide a more personalized customer experience. Moreover, the customer engagement process itself can be automated to an extent that customers will only be dealing with virtual assistants and back office robotics, which in business terms means lowering costs and increasing revenue.

Chatbots and virtual assistants can easily handle basic enquiries, so they can provide customers with information on how to perform certain actions, for example, open a bank account or connect to online banking.

According to the Banking Technology Vision 2017 by Accenture, 80 percent of bankers expect AI and NLP to boost technology adoption throughout their organizations, and 78 percent are looking forward to a simplified user interface that will ensure a more human-like user experience.

Data Analytics & Forecasting

Another major area of NLP application in finance is data analytics and forecasting. To succeed in this highly competitive industry banks must have access to information as close to real-time as possible. This helps them make informed, data-driven decisions and gain a better understanding of their clients and their operational environments.

Just try to imagine how much unstructured data the world generates every minute! Here are some stats that will give you an idea of what is happening in the financial sector data-wise:

  • Every day, Reuters publishes thousands of pages of financial news;
  • Every minute, Wall Street analysts produce several research documents;
  • Every second, financial services professionals receive emails with important financial information.

It is that neverending information exchange that drives hedge funds, for example, to use NLP to improve their models.

Applying NLP to this kind of data enables computer programmes to process unstructured text, identify patterns within it and turn it into intelligible insights. Financial companies can then better evaluate investment opportunities and acquisition targets, improve their risk management and make other informed decisions.

Natural Language search: Just ask your database

It’s all good to stay on top of your industry’s news and trends, but how far will you go if you can’t answer your own company’s questions? The financial industry requires its players to have real-time access to their internal company data; otherwise, they will find themselves at a large competitive disadvantage.

With natural language search, companies can perform search across their own databases and get accurate answers in a matter of seconds. For example, a lot of banks operate in different time zones, and sometimes, when a decision needs to be made immediately, they simply cannot afford to wait for the data to be sent from elsewhere.

And this is where applying natural language interface to databases comes in handy: all you need to do is ask your database a question. Once built into your database, the NLP interface will translate human language into an SQL request, process it and provide you with an instant answer.

This will allow everyone, from an C-Suite to a marketing specialist, have instant access to data and make faster decisions. This will also help move staff to higher value added roles, because all internal interactions with data will be handled with the help of NLP.

Here are some examples of how different roles can benefit from using NLP:

If you are a bank manager, imagine how amazing it would be to simply ask your database a question and get key customer insights within seconds: their loan history, information about their transactions and deposits, the products they are using, and so on.

As a mortgage broker, you will be able to increase your organization’s revenue and upsell opportunities with instant access to the status of customer loans, type of financial product or for example breakdown of all assets within a portfolio.

NLP can significantly increase the efficiency of trading operations: having immediate access to securities data, obtained from multiple sources, will help traders, provide the most accurate price estimates for every trade they make.

FriendlyData Enterprise - the best way to build a data-driven organization

However, building an in-house NLP interface requires a lot of time and investment, as well as experienced and talented data specialists. With the NLI solution, offered by FriendlyData, you won’thave to go through all this: you can easily integrate FriendlyData’s Natural Language Interface and have instant and secure access to internal data. It will turn human language into requests and return data in a suitable format.

Security is a number one issue in the bank industry. Along with other advantages the FriendlyData Enterprise solution can offer, it also ensures safety and data privacy. It doesn’t require indexing of data and moving it to an external storage: sensitive and high-profile data will never leave your bank’s private network. FriendlyData can be connected to any relational database and integrated within a few minutes. With this solution, businesses can provide their employees at all levels of the organization with access to the much needed information and help them make decisions based on company data.

The list of possible NLP application scenarios in the finance industry is endless. No matter what area of the industry your business is in, you can benefit from having instant access to the enormous amounts of data generated both externally and internally, by your own business. The ability to make faster, data-driven decisions will help you stay one step ahead of your competition.