Data Digitization In Banking And Financial Services

Data Digitization In Banking And Financial Services

by Amit Jnagal, on March 13, 2019 9:15:00 AM PDT

Old school ways of conducting financial transactions are gradually bidding adieu. Automation, AI, and data analysis tools are taking over to ease the workflow. Everyone in the market wants to move ahead to enhance customer experience, deliver value, and obtain market share. So boarding the train of digital transformation has become the first choice for most companies. Now the question is what does it signify for the present and future of this industry?

Adapt and adopt, are the key terms for most companies who are walking in pace with the technological revolution. Finance being the people the first sector is shifting its focus to make their customers’ personal lives better and easier. Businesses are prioritizing greater agility and higher quality for their overall process improvements. Some of the changes they are going through are:

  • Making investments in technology that can support or expand their operating models, thereby making their processes responsive, effective, and digital.
  • Making investments on data science, information, and data outcomes which will enable the organization to get an edge in the competitive finance market via better decisions, formulation of product and services to offer better customer experiences as well as streamlining operations.
  • Making business units realigned to fully connect with the customer experience so that they can cater to their unique and individualized demand.

Data Digitization for the Financial Sector

As per a forecast from International Data Corporation, worldwide spending on digital transformation technology be it software, hardware or services is expected to be as close to $2 trillion in the year 2023. How much of it do you think would be invested for data digitization? It’s indeed a difficult thing to say. For a booming industry like finance, data in digital format will help foster an automated and block chain way of touch-less transactions. There will be a lot of business insights available to the decision makers of such companies enabling them to tailor make customer-centric services. Real-time financial reports will be available rather than periodic ones. With robots and algorithms coming into picture, new service-delivery models will come into picture. These models would make onshore and offshore operations smooth and less time consuming.

The necessity of going digital

Customer experience, business growth, and performance are directly affected by digital transformation. At a time where intense competition has taken over the market, companies constantly need to upgrade their services with advanced technologies. Leaders from financial industry are searching ways to harness technologies such as big data, AI, machine learning etc. to evolve. In fact with ready-to-run solutions and automated framework they’re being able to improve the odds for success as well as accelerate results.

Recently, Forbes Insight and Cognizant partnered up to survey more than 100 North American senior financial services executives in order to learn how they’re capitalizing on new technologies to offer value to their customers. The research shows that executives believe that 25% of their future growth will be driven by customer experience-focused digital strategies and experiences. The research also suggests that companies who fail to keep pace with them face higher risk of disruption and marketplace irrelevance.

Tips on getting started

1. Begin with automation:

Robotic process automation can prove extremely helpful in terms of taking over repetitive tasks and saving manual labor to focus on areas which require insight and judgement. With the usage of RPA, desktop automation, and other technologies, companies can increase consistency & efficiency with decreased cost, and staff.

2. Gain momentum with chatbots and virtual assistants:

These solutions help customers understand the nitty-gritty of their accounts and spending history. They can even offer personalized service suggestions and offers based on real-time and historical insights.

3. Make data organized and accessible via analytics tools:

Since finance companies deal with a lot of data from disparate sources, it’s necessary to keep them organized and accessible for future usage. That’s where analytical tools come into picture. Not only this, they also capture economic trends and client data systematically to help the companies make informed decisions.

4. Employ pattern recognition algorithms to generate better output:

After you’ve employed analytics to organize data, you can utilize AI algorithms to enable the systems recognize patterns quickly and tirelessly. If these pattern recognition algorithms are combined with human talent, then machines will be able to generate output and make continuous adjustments and improvements.

How Infrrd helps in digital transformation

We help financial enterprises in dealing with complex documents which encompass annual reports, financial numbers, account statements, legal contracts, emails, invoices, receipts etc. Automated data extraction is our forte, be it from complex tables or images or PDF files. Our platform is capable of minimizing costs and process time for such documents by 50-70% with AI-driven data extraction.

We can also help you with image processing through our real-time machine learning algorithms. You’ll be able to derive insights from them to make better decisions. Our intelligent data capture platform can focus on your specific problems and tackle them in a better way. We’ve helped many mortgage companies in data handling and processing loan applications. Connect with us at today to get a consultation or a free demo.

Topics:Intelligent AutomationAI ReadinessBusiness Insights

About this blog

AI can be a game-changer, but only if you know how to play the game. This blog is a practical guide to turning AI into real business value. Learn how to:

  • Make sense of complex documents and images.
  • Extract the data you need to drive intelligent process automation.
  • Apply AI to gain insights and knowledge from your business documents.

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