Does your FinTech business need data analytics outsourcing?
16th August 2022 at 2:20 pm #245647samandersonParticipant
“Data is everything” is a well-established cliche and not just in the FinTech or Financial Services industry but in every possible business. But the real power lies in the ability to process raw data to produce tangible, actionable insights. What would it mean for your FinTech business to be able to process every little piece of data almost instantaneously and use it to improve customer experience and build better products faster than your competitors? That’s what data analytics does to your business.
Since the time Fintech app development companies witnessed the digital transformation, businesses efficiently utilized insights gained via data analytics reports to stop customer churn, prevent accidents, and predict and stop financial fraud and failures. Thanks to big data, FinTech has expanded its operations using modern technologies such as the Internet of Things (IoT), Blockchain, and Artificial Intelligence/ Machine Learning (AI/ML) , Smart data discovery. These applications are the primary reasons for SMBs and enterprises to prefer data analytics outsourcing.
Outsourcing is a cost-efficient strategy that helps startups, SMBs, and established enterprises effectively manage everyday operations by leveraging analytics expertise and curating data with their brand. We will discuss the pros and cons of outsourcing data analytics and how your FinTech business can outsource data management services in the latter part of our article.
First, let’s take a broader look at the role of big data analytics in FinTech.
The Role of Big Data in FinTech
The FinTech industry is growing at a CAGR of 6% and is expected to reach $28529.29 billion by 2025. The increased usage of mobile devices has contributed to more & more customers using FinTech products and services of some kind or the other. As these interactions and usage patterns are stored over time, users have an exponential increase in data produced every second.
This presents both challenges and opportunities for most FinTech businesses.
If your FinTech business lacks the ability to use this vast amount of data to cater to your customers, you are setting up for failure. On the other hand, advanced data analytics and smart data discovery capabilities can do wonders for your FinTech organizations.17th November 2022 at 9:05 am #248393dasixParticipant
The USA is a big market for outsourcing because in the US there are plenty of producers, manufacturers, and IT services that have always needed to be serviced. That’s why today almost every industry goes towards outsourced work, with reducing costs being one major advantage over hiring internally or internationally17th November 2022 at 9:07 am #248394Geremy1Participant
Outsourcing for what? Are you doing basic data entry? Are you doing complex calculations and analytics? Are you compiling and quantifying data? Are you outsourcing a call center for customer support?
It all depends, there is no “best” outsource company from It Company. This is the field I play in. If you’re a big company then go for Accenture, or Infosys because if you have big revenue then they will play ball with you. If not do your own research, ask people some questions, ask yourself some questions.17th November 2022 at 2:47 pm #248423Geremy1Participant
Why are data management and IoT analytics important?17th November 2022 at 2:54 pm #248424Melissa WhiteParticipant
Collecting, storing, and visualizing raw data is just the beginning of any meaningful IoT project. The economic effect is achieved by management decisions to optimize existing processes and bring new products and services to the market for end users. Technically, this is achieved by aggregating, processing and in-depth analysis of data received from devices, more details https://www.eliftech.com/insights/iot-data-management-and-analytics-for-manufacturers-eliftech/ . However, for each significant decision, these operations will be unique – optimizing harvested storage space is fundamentally different from orchestrating transactional data in smart grids or managing a forklift fleet.
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