How Big Data Enhances Banking And Financial Systems

#Article
#Big Data & Highload
#FinTech
February 28, 2020 10 min read

Concerning big data in banking and financial systems, Financial Times provides a smart definition about both systems as a data store. They record people who have money, the transactions used to handle it, and the rules governing service provision. And Zachary Townsend, Co-founder of Standard Treasury, San Francisco, US, commented for FT that the banking industry budgets and organization headcounts could be optimized by fintech technologies to reduce operational costs, improve ROI, and raise financial system efficiency.

Juniper Research estimated that more than 2 billion users would access their bank account through their devices by the end of 2018. To serve huge numbers of clients faster and more effectively, banks must turn to fintech software development companies with expertise in big data solutions.

Big data is a complicated issue, but it simplifies everything: from filtering the necessary information based on the client’s name to answering the customer’s question more quickly. Big data in banking helps to perform financial processes more smoothly. Let’s see how it works.

Big Data In Banking

US banks have 1 exabyte of stored data, which is equal to 275 billion mp3s. Typically, this data is gathered from credit cards, transaction records, customer bank visits, call logs, support chats, web interactions, etc. 

Unstructured data pieces have no value but carefully analyzed big data is used for customer risk management, client relationships improvements, setting effective staff amount, understanding customer needs, gaining insights for product development, scoring credit risks.

Banks are focused on two basic business objectives: attracting new customers, and then retaining them in a way to meet their expectations. Big data introduces new schemes, enabling knowing customers’ profile, predicting their behavior, and evaluating risks.

Some time ago, Alex Lutskiy, Innovecs’ CEO, noted in his interview to Interfax:

I am sure that our industry expertise and technological one will produce excellent results. In the nearest future, we plan to connect Ukrainian banks to the internet protocol Ripple which will cryptographically secure financial transaction data and will allow to reduce the costs and speed up payments due to the system openness and absence of mediators. Implementation of the technology will also facilitate the development of an electronic government in Ukraine.
Alex Lutskiy,
CEO of Innovecs

As you read further, some of these objectives have been reached, some of them are still being executed, but one thing is true for sure, digitalizing banks through big data pros is a high priority.

Big Data Concerns in the Banking Industry

FST fintech analysis has identified financial reporting, cybersecurity, and submitting demands for banking products via electronic channels as top priorities in 2020. Traditional bureaucratic banks are no longer demanded and trusted. Users are looking for innovative solutions that bring banks closer. Big data gives knowledge about users’ wishes and helps to deliver the right banking products to the market.

The case of Monobank as a “bank without branches” is a good example of a fintech solution. The project team, in collaboration with Universal Bank, created a new, stylish functional banking product, presented it mostly on Facebook. Many people received attractive black cards, and less than a year after launch, Monobank gained 600,000 users. 

They designed a successful product because they applied big data to create a portrait of the user as a “young man with higher education” (including other details), to learn what “good credit terms” meant for the client, and what extra perks would be appreciated by the TA.

If a business is willing to benefit from all the advantages of big data (risk management, personalized solutions, customer feedback analysis, boost revenue via easing operational processes), it should be aware of the following concerns:

  • Special skills are needed to operate with big data (outsource a company with good expertise in fintech software development).
  • It’s worth remembering big data is growing, so your company’s strategy should consider how it will be treated in the future.
  • Privacy issues are important (every time dealing with big data you operate with the third party private information legally and securely).

So, big data treated well is converted into beneficial results for the business, such as gaining new clients, providing them with a better user experience, and more efficient risk management. When done well, these benefits will help to obtain a leading position within the market. And there’s one more obvious advantage for banks that apply big data solutions: it is possible to collaborate with other financial companies considering them as fast-growing competitors in the financial sector. Why this competition is taking place and more details about the fintech market is described below.

How Big Data Contributes To Financial Institution Operations

Unit City, an innovation park in Ukraine, analyzed in its fintech report that, in 2018, access to smartphones and mobile internet has grown substantially, and public trust in banks has been lost at the same time. So, these two key factors led to increasing demand for fintech services based on big data capturing, collecting, analysing, and applying in the form of the software.

Why, When, and How Big Data is Used in the Financial Industry

If business owners or stakeholders are taking care of revenue-boosting, in the context of big data, they are in search of the answer to the question, “How can big data in the financial system help to solve business problems?” In a simple way, the answer can be presented as the following sequence: 

  1. Identifying where big data resources are useful (processing support tickets, customer online support, new business models implementation, etc.)
  2. Aligning business cases with technological capacity (once the number of your clients has grown, you may need special application to automate interaction with them)
  3. Improving business processes
  4. Scaling the entire business if necessary

Usually, big data contribution to the financial sector is divided into three directions: operational improvements (reply client’s query in a shorter time, perform transactions more securely), employees involvement (reduction of staff number, optimizing workflow), and customer experience.

And, according to Forbes, 2.5 quintillion bytes of data pieces  are applied to ease and hasten financial processes, enhancing complex decision-making, as Pasquale Orlando smartly noticed in his interview with Ingenium Magazine:

We cannot use services based only on mathematics that consider mandatory information and legislation for giving advice on complex choices (e.g., investments, savings, trading). We must react to a complicated reality, where choices are influenced by multiple factors and cannot be separated from a deep knowledge of the customer that can be had thanks to big data analysis.
Pasquale Orlando,
Strategic Marketing Manager at Deus Technology

Let’s see where and how big data is utilized for a better reaction to the complex financial reality:

  • User experience. The BFSI industry (banking, financial services, and insurance) no longer needs linear understanding of the customer journey. To compete successfully within the market, they need precise data analytics on the clients, to know their pains and gains, to forecast how a person will interact with their financial brand.
  • Operational improvements. Software empowered by big data can detect fraud signals successfully, analyze them via machine learning, and predict illegal transactions.
  • Employee engagement. After having obtained the right tools, the employer can manage and measure personal employee performance, KPI, team spirit as well as balance back office costs.

Several directions for the improvements driven by big data, empowered by the digital tools, and obtaining certain forms, such as alternative types of payments (cryptocurrency, electronic or QR code payments); marketplace lenders (P2P lending models, when money is received both from the individuals and financial institutions); AI solutions (robotic consultants); digital identification and biometrics (voice identity, fingerprint, face recognition give additional possibilities for fraud prevention).

Totally CB Insights listed 250 companies that were transforming financial services via big data applications. It’s worth noticing Innovecs is also involved in fintech solutions, giving vast possibilities to the businesses to outsource custom FinTech software development.

Fintech Challenges

The 2019 Ukrainian fintech catalog listed about 100 fintech market players. The average financial institution profile was defined as a company focused on B2B dealing with European customers and is more self-financed than gaining investments from the banks. 

Such enterprises have mostly been working more than three years on the market, but they are still in a state of continuous changes because there’s a number of the barriers to development and necessary legislative changes. Remote client identification, EU 2nd payment services directive, and e-money legislation issues are of great importance to create new opportunities for fintech services provision in Ukraine comprising big data potential. 

A Ukrainian online platform about IT business, startups, and technologies conducted a survey outlining big data fintech services that are limited in usage or not applied at all because of legislation restrictions or insufficient digital expertise of the financial market players. Here are the top priorities for improvements (research methodology was based on WSI index and weighted sentiment index, which shows the importance of the issue for the respondent):

  • Remote client identification
  • Big data analytics for fraud prevention (obtained the highest 40.20% WSI)
  • Cybersecurity
  • Customer interaction interfaces
  • Automation/support for decision-making processes

It’s known that big data has enhanced the launch of fintech models such as PayPal, P2P loans, and cryptocurrency operations, which have yet to be introduced in Ukraine to the full. The survey mentioned above ranked the following services as non-existent or hardly limited in our country:

  • Cross-border payments for SMEs (small and medium-sized enterprises) and individuals
  • Financial services for the unbanked (for people having no credit cards, saving accounts, or personal checks)
  • E-invoicing (how trading partners arrange their collaboration to issue and monitor transactional documents to meet the term of the agreements)

So, big data is empowering a huge number of fintech solutions, making transactions faster and more secure (risk management is easier with fintech tools); assisting in more effective interaction with the clients; ensuring convenient instant mobile payments; decreasing fraud level. 

Even considering all these advantages of big data for the financial sector, banks, finance and loan companies, commodity traders, insurance providers, and others should bear in mind the following challenges when outsourcing software and application development services:

  • Cost of big data management and digital transformation
  • The complexity of key business processes (to develop efficient business tools, one must have precise knowledge of the business processes)
  • Outdated legislation
  • Investment management to increase profits—not only to apply a newly developed fintech tool

In response to quite a huge challenges list, FST (financial sector transformation) has reported an emphasis that Ukraine has large “talent pool” and under legal change, movements, as well as improved collaboration between banks and other financial institutions progressive shift, is expected in big data implementation and new fintech solutions deployment.

Summing Up with a Few Glimpses

Big data gives possibilities not only to perform digital changes, but to convert them into real company profits, employees perks, and customer benefits. Big data in financial and banking industries:

  • helps to manage arising risks;
  • improves service delivering;
  • provides possibilities for global reach;
  • enhanced reporting;
  • segments customers;
  • secures transactions.

Due to the growing fintech market, more and more financial institutions are transforming their business strategy with a focus on corporate and consumer clients. And the implementation of big data solutions ultimately provides a positive effect.

 

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