Unstructured Data Applications For The BFSI Industry

Evaluating The Emerging Trend Of Unstructured Data Applications For The BFSI Industry!

Posted on : February 24th 2022

Posted by : Viswanathan Chandrasekharan

You’re not alone! The BFSI Industry at large is striving to figure out ways to use the vast resource of unstructured data to its advantage.

From your routine shopping needs to running your house or your business requires funds. Traces of digital banking dates back to as early as the 1960s since the launch of ATMs and cards and with the internet emerging in the 1980s we’ve not looked back ever since. Digitalization has abridged the processes and taken over the BFSI industry where now everything is just a click away.

Think about the number of card swipes or ATM visits or fund transfers you could do over a month’s duration. Considering the entire world’s population, now multiply that to billions of times over the years. That’s how much data is collected on a regular basis. Every interaction with your banking or financial institution generates customer-centric data such as feedback forms, customer forms, KYC forms, email exchanges, request forms, call transcripts, web server logs, social media interactions, pdf documents, text messages, etc. resulting in astronomical sizes of data of which a whopping 80% amounts to unstructured data. Imagine, tackling this data to make sense of it and eventually analyzing it to grow your business can present an enormous undertaking which if done right, can amp up your business along with a huge competitive advantage.

To gain an edge over the competition, customization and an eye for detail become crucial.

Increased focus on customer service has gained popularity boosting the need for digging deep into locked away customer-centric unstructured data and attaining invaluable insights to up the competitive game. Needless to say, that security against data breach/theft where customer’s financial safety is at risk becomes of prime importance begging the need for innovative yet effective and efficient early fraud detection tactics in Banking, Financial Services & Insurance (BFSI).

Studies show that the global data analytics market for BFSI Industry added up to around USD 15.65 Billion in 2020 and is expected to incisively rise and reach USD 86.68 Billion by 2027 resulting in a significant incline of the data analytics in the BFSI market revenue (link). Suffice to say that the application of big data and especially unstructured data to gain an edge in the market is most certainly the emerging trend. Keep on reading to get the complete know-how about how to ace the concept and beat the competition.

Value Addition Processes are the key to unlocking this intimidatingly big trunk of unstructured data.

Undertaking the value addition processes is essential to normalize and standardize the unstructured data and transform it into comprehensible information that is in an organized form such as charts, graphs, and more for your business use. The aim is to restructure and transform this data into an analyzable structured format that can potentially empower you to draw conclusions leading to well-informed business decisions that prove to be beneficial for the success of your organization.

Leveraging unstructured data in combination with structured data to your advantage can help you discover comprehensive insights.

From filtering the essential information with the use of something as basic as the customer’s name to answering customer’s questions quickly and accurately and finally, making strategic corporate decisions regularly based on vital information, the importance of using customer-centric unstructured data is endless. Combining the unstructured data with the structured data to your advantage can uncover detailed insights into customer preferences, facilitate identification of market gaps, help to realize unmet customer needs, and so on. This can eventually result in productivity boost, new product developments, better customer services, and whatnot.

FYI, it is worth the time and investment required to deep-dive into the unstructured data.

Standardizing the unstructured data has its perks right from acquiring in-depth knowledge about your customers’ needs to conducting sentiment analysis on a rather complicated financial subject can help you gain the right perspective for let’s say your risk management plans or your marketing strategies and so on. If you could analyze the patterns of customer liaison with your financial institution with ease and make sure to proactively address potential issues on priority, then be rest assured that your organization will be unbeatable in today’s competitive industry.

The possibility of attaining profitable opportunities resulting from the untapped resources of the unstructured financial data is endless.

It all starts with sourcing the raw data from numerous public and other sources but the difficult part is that every source has its data in different formats and different terminologies which effectively presents itself as a big portion of unstructured data. This diversely sourced data is then head-on addressed to with its complete complex glory under the observant eyes of subject matter experts with the assistance of our custom-designed algorithms, multiple high-tech software, and advanced platforms, that showcase competent processes to normalize and standardize this amount of unstructured data in real-time.

A recent survey dictates that banks globally are striving for digital convergence strategies to effectively engage customers along with improved asset quality and sincere regulatory compliance. A whopping 2.5 quintillion bytes of unstructured data is generated from internet banking and ATM transactions. This massive volume of data can be useful for fraud detection, risk management, and customer satisfaction industry-wide cracking the mystery of achieving competitive advantage. Let’s look into some of the advantages it provides in Banking alone:

  • Complete acquisition and analysis of customer’s data such as expenditures, incomes, etc to calculate factors like credit extensions, risk management, and so on
  • Effective segmentation of the customers based on vital indicators such as customer insights and their interactions with the institution can then help serve them better.
  • It also helps improve another growth metric for the banks, its employees, by actively tracking their performances and involvement to appropriately recognize hard work and talent.
  • It improves efficiency and reduces the cost of processes such as reporting, auditing, and verification by easy analysis of the stocks, customer transactions, etc to facilitate risk analysis and fraud avoidance.
  • It effectively improves market trading analysis by analyzing complex data types like asset classes, hybrid datasets, and market types in seconds, eventually enabling providing personalized banking solutions with ease.

Overcoming challenges in the BFSI industry is made easy by letting go of the traditional methods

Challenges do come up every step of the process since persistent accuracy and consistent compliance with several existing policies is a given but effectiveness and efficiency cannot be missed either. Some of the constant challenges faced by the BFSI sectors with unstructured data are:

  • Due to its ambiguous nature, unstructured data is not included in the traditional enterprise search engines
  • The traditional key-word based searches imply that the user should be well aware of what they are looking for which becomes a hassle when it comes to unstructured data.
  • The inconsistency between the information required and the data available results in inaccurate search results and loss of valuable time.
  • The use of multiple different platforms to extract information from structured and unstructured data in different ways is very challenging and requires numerous man-hours.

From the traditional keyword-based searches to the inventive context-driven real-time searches it is in itself a giant leap towards the future but of course, it brings its hurdles considering the irregularities and ambiguities that make the data even more difficult to understand. Constant distress also lies in the fact that these processes might take too much time on insufficient and inaccurate searches until a defined process is established over time.

The new generation of technology in every industry including BFSI is what makes it all happen.

Cognitive Search Techniques, a new and reformed innovation in the field of data and information, uses Artificial Intelligence to enhance enterprise searches. This refines the end user’s search queries and extracts relevant information which can further be tagged and personalized as per the organization’s needs. Fintech tools that are built on the aforementioned cognitive search techniques hold the capacity to integrate unstructured data along with Fintech information, leading to the generation of API services, services which are the means for applications to interact with a server-side system to retrieve and/or update the data. Leaning on these services has become increasingly popular in the realm of Financial Institutions.

Proactive employment of AI & ML technology implies future financial services stability.

Artificial Intelligence and Machine learning especially have gained sustainable importance in the BFSI industry and are changing the provision of some financial services. Their applications for fraud detection, capital optimization, and portfolio management are swiftly increasing. Their consistent applications will result in key benefits such as accurate and efficient data processing, systemized risk management, low-cost customer interaction, compliance with regulations, and much more.

The potential scalability of these new technologies warrants the presence of organizations such as Straive. We offer end-to-end data solutions that help provide extensive knowledge of customer preferences, determine market gaps, explore unmet customer requirements and successfully fill in process gaps to profitably make a difference in your business revenue.

When it comes to the BFSI industry, the emerging trend of normalizing and standardizing in order to analyze the unstructured data and gain deeper insights into customer behavior holds immense promise in revolutionizing the Fintech future.

An elaborate range of business areas can be transformed with the aid of the imperative information extracted for the ever so dynamic unstructured data such as from client-facing sales units, ideation & initiation of financial transactions, to IT service management. In addition to this, one cannot forget the risk management services for financial portfolios or the background checks conducted as part of KYC, and for many such processes including but not limited to detecting fraud, streamlining transaction processing, optimizing trade execution, and of course, competing in a crowded market.

Undeniably, the fact remains that there will always be room for improvement, rather we can say room for automation and transformation.

Leading the way in the light of modern cutting-edge financial technology towards a well-oiled machine-like automated Fintech future is the ultimate goal. Hence, we can undoubtedly say that tapping into the untamed power of unstructured data resources and applying it in the ever-evolving BFSI industry can certainly help bring success to your enterprise amidst its chaotic dynamism.

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