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How Data-Driven Technology Can Transform The Financial institutions

  • July 18, 2022
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Meet the Author : Mr. Bharani Kumar

Bharani Kumar Depuru is a well known IT personality from Hyderabad. He is the Founder and Director of Innodatatics Pvt Ltd and 360DigiTMG. Bharani Kumar is an IIT and ISB alumni with more than 17 years of experience, he held prominent positions in the IT elites like HSBC, ITC Infotech, Infosys, and Deloitte. He is a prevalent IT consultant specializing in Industrial Revolution 4.0 implementation, Data Analytics practice setup, Artificial Intelligence, Big Data Analytics, Industrial IoT, Business Intelligence and Business Management. Bharani Kumar is also the chief trainer at 360DigiTMG with more than Ten years of experience and has been making the IT transition journey easy for his students. 360DigiTMG is at the forefront of delivering quality education, thereby bridging the gap between academia and industry.

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Financial sector businesses are embracing a culture where data is essential to decision-making. Consequently, organisations may use this strategic strategy to contextualise and personalise their messaging to customers and prospects, enhancing the customer-centric approach and boosting the business. So how can banks profit from a data-driven strategy?

In spite of this, data-driven development in the financial sector is still in its infancy. In fact, just 6% of financial institutions throughout the world consider themselves "pioneers" when making judgements based on data. Additionally, according to the Digital Bank Report, just 10% of banks and credit unions consider themselves to be "rapid followers."


The financial sector is experiencing disruption. Similar to how Amazon and other significant e-commerce rivals affected the retail business, tech-driven financial services companies and online banks are upending the banking industry. These companies, though, take a more modern stance. For instance, they fully use the potential of mobile apps to provide services to customers wherever. As a result, millennials have the highest regard for financial services companies that are tech-driven. Actually, the fintech sector is growing at a 25% annual rate.

What might "digital transformation powered by data" mean?

  • Digital transformation is integrating digital technology into various operational areas of an organization to increase efficiency, get business insights, and increase revenue by leveraging new business or service delivery models.
  • Data-driven insights must fuel digital transformation as a strategy. For example, because the banking industry is one of the most data-intensive businesses, it must consider using this data to generate valuable insights.
  • When successfully executed, data-driven digital transformation can lead banks to transform into smoothly running hives of data-centric systems.

The Benefits of employing Data-Driven Solutions in Financial Institutions:

Financial organisations may gain a more comprehensive understanding of customer behaviour and brand loyalty via the use of digital analytics.

There are numerous benefits of incorporating a data-driven strategy into the processes, but they can be summarized as follows:

  • Greater personalization of products and services, since everything that can be enhanced to meet client's needs is identified from start to finish.
  • Better use of available resources because all processes are streamlined, eliminating the need for significant new investments and allowing us to make the most of what we already have.
  • Better performance of the brand's digital channels since more effective, tailored, and efficient marketing, CX, and communication strategies may develop.

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The necessity of a data-driven digital transformation:

Using data-driven insights to power a traditional financial institution's digital transformation strategy can produce various benefits. Among them are:

As a crucial step in the digital transformation process, data analytics is used to accelerate change, reduce innovation cycles, allow data integration, and enhance customer experience. The areas that can be improved using analytics in a digital-first approach are almost limitless.

  1. Accelerate the advantages of data analytics:

Using new technology may appear to be an expensive investment at first, but when seen holistically, it can prove to be a cost-cutting step. Improved operational efficiencies, more automation, reduced errors and rework, and effective use of available resources all control costs.

  1. Reduced costs:

With the rise in data breaches, it is clear why security is so important in the financial sector. Additionally, these organisations require stringent data security processes because the banking industry deals with real money and the most private customer information.

  1. Improved security:

How Data-Driven Capabilities Deployment Can Benefit Financial Services:

Here are some data-driven improvements you may make to deliver value.

  • Electronic goods and services:

    Financial services companies may use the customer data they collect to create new innovative goods and services that will enhance income streams. It may take many other forms, like as working with non-bank organisations to create a network of services utilising data.

    Enhanced Effectiveness:

    Using robotics, artificial intelligence, and machine learning, data collection and optimization can assist financial services in streamlining and optimizing their internal processes. As a result, financial services businesses can reduce operating expenses while improving overall performance. In addition, they can leverage data from their consumers to reduce operational risks and lower business processing costs.

  • Personalization:

    Obtaining data-led personalization is one of the most significant benefits of getting and optimizing customer data. Banks can utilize the information they collect to tailor their products and services to the specific demands of their customers. This can include bespoke pricing, matching life demands with services, insights to improve financial well-being, etc.

  • Higher Revenue:

    Banks can increase their revenue by leveraging sophisticated and AI-driven data analysis to determine their customers' willingness to pay. This can significantly improve the accuracy of pricing models and eliminate the need for "best guesses" when pricing a new product or service.

  • Predictions:

    Financial organisations can improve their judgements going forward by collecting and optimising client data. As an illustration, AI has successfully anticipated increasingly sophisticated financial crimes. This data-driven forecast may be used by financial institutions to lower risks, gauge their liquidity needs, make more informed loan decisions, enhance collection methods, and spot fraud.

  • Enhancing Risk Management:

    By assuring accurate data, which is largely required for regulators, financial services may reduce compliance risks. To improve credit management and fraud detection, these regulators can create and evaluate risk profiles. A strong data-driven strategy may also be advantageous for the financial services industry by leveraging high-performance analytics to produce insightful results. These insights may enhance corporate processes, speed up decision-making, and help the financial industry comprehend its consumers more thoroughly.

Transformation Driven by Data:

The Future of Finance:


Being data-driven entails making decisions and taking action based on information provided by our clients. To accomplish this, we must take three steps:

  • Have trustworthy and activatable data:

    Have a data strategy that aims to expand the client's expertise to reach new audiences and develop the business.

  • Enable the data:

    Investing in data-driven campaigns may be automated, and data strategy can be used to contextualise and tailor messages.

  • Rely on insights when making decisions:

    Data analysis and interpretation and business insights are used.


Finally, as technology advances, data can keep financial institutions up to date on emerging fraud techniques. By keeping an eye on the techniques and locations used to generate fraudulent accounts or acts, financial institutions may, when required, adopt more sophisticated safety procedures. Any organization's ability to expand depends on its capacity to ask the right data questions. The right data analysis tools, on the other hand, are as important and may lead to bigger, better, and deeper investigations that will promote growth in more areas. To fully exploit the value of data, financial institutions must prioritise it and make it the priority that informs all of their decisions.

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