Data Digitization In Banking And Financial Services

Old school ways of conducting financial transactions are gradually bidding adieu. Automation, AI, and data analytical 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-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 in 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 blockchain way of touchless 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 the picture, new service-delivery models will come into the picture. These models would make onshore and offshore operations smooth and less time-consuming.

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 the financial industry are searching for ways to harness technologies such as big data, AI, machine learning, etc. to evolve. In fact, with ready-to-run solutions and automated frameworks, they’re being able to improve the odds for success as well as accelerate results.

Recently, Forbes Insight and Cognizant partnered up with 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 a higher risk of disruption and marketplace irrelevance.

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 that require insight and judgment. 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 the picture. Not only this, but they also capture economic trends and client data regularly 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 to 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.

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 today to get a consultation or a free demo.

Originally published at https://www.infrrd.ai.