Data Analytics Outsourcing in FinTech

What would it mean for your FinTech business to be able to process every bit of data almost instantly and use it to improve the customer experience and create better products faster than your competitors? That's what data analytics does to your business.

 Ever since FinTech witnessed the digital transformation, businesses have effectively used insights from data analytics reports to stop customer churn, prevent accidents, 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, artificial intelligence/machine learning (AI/ML), and intelligent data discovery. 

 Outsourcing is a cost-effective strategy that helps startups, SMBs and established enterprises efficiently manage day-to-day operations by leveraging the expertise of analysts and curating data with their brand.

 The Role of Big Data in FinTech

The growth in mobile device usage is contributing to more and more customers using FinTech products and services in one way or another. As these interactions and usage patterns persist over time, users have exponential growth in the data produced every second.

If your FinTech business doesn't have the ability to leverage this massive amount of data to meet customer needs, you're dooming yourself to failure. On the other hand, advanced data analytics and data mining capabilities can do wonders for your FinTech organization.

According to research, more than 66% of your customers expect you to understand their expectations, and even more so in the FinTech industry. What's more, 71% of FinTech users now demand more agile journeys with multi-channel interactions.

If you have the right data analytics infrastructure, you can use that data to create customized products and features for your customers. 

Let's take a look at a few applications and use cases where pairing big data analytics with modern technology benefits your FinTech business. 

Big Data in insurance 

Traditionally, insurance companies have relied on statistical and demographic data that is no longer relevant. They had to manually price their policies and miss out on significant financial opportunities. Today's insurance organizations use big data to create low-risk insurance offerings. 

For example, many car insurance companies use data from the field and crash statistics to assess risk and adjust their policy offerings. 

Big Data analytics in digital payments 

FinTech is actively using big data and machine learning to detect fraud and monitor security. The most recent trend of digital transformation in online payments is the merging of payment processing with sales, where users can get credit within seconds. The online mechanism combines machine learning algorithms and big data to assess risk and the amount of credit available to the customer. This has improved conversion rates for a variety of FinTech businesses. 

For example, various financial payment companies target young professionals and help them invest, save, and safely manage their finances. 

Big Data in Lending 

Artificial Intelligence models and Big Data analytics can be used extensively in microfinance and other lending businesses to make credit loans available to a wider audience. This will bring you two benefits. First, your FinTech business will promote financial affordability to your target audience, and second, loan acceptance will lead to increased revenue for your FinTech business. Moreover, the wide availability of instant loans stimulates the economy and promotes the dynamic growth of other businesses. 

Predictive data analytics in wealth management

Wealth management is one area where predictive data analytics can be used to bridge the gap between business and customer expectations. Insightful customer data can be used to create more complete customer profiles. Data also helps with customer retention; for example, you can make customized offers for different demographic groups, from student loans to retirement plans. 

In addition, predictive data analytics helps you better segment customers, deliver customer-centric products and services, and optimize operations. Perhaps that's why businesses of all sizes and sizes are using data analytics services to improve their entire customer experience.

Now that we know how important data analytics can be to your FinTech business let's look at why you should outsource these data management services. 

Why does your FinTech business need to outsource data analytics?

 

Effective data analytics needs state-of-the-art technology built specifically to meet the business needs of your FinTech organization. But if you're still not sure how outsourcing data analytics technology can help, these points are for you:

 

Access to expertise: 

As a financial or FinTech company, you understand the ins and outs of providing exceptional services in your field. Asking for the technical expertise you need in data analytics will save you from having to enter a completely different vertical with little to no experience. 

 

cost-effectiveness: 

It's a fact that outsourcing brings co-benefits, such as savings in dollars and faster project delivery. Outsourcing data analytics is no exception. Your FinTech company can save huge operating costs by outsourcing big data, as the team takes responsibility for the technical part of the business. It also reduces overhead costs such as social security tax and fees associated with maintaining your own development team. 

 

Scalability: 

Outsourcing data analytics to FinTech gives you the adaptability, speed and flexibility you need to get ahead of the competition. This factor not only allows you to maintain a smooth development process, but also helps your business achieve global reach in the long run, ensuring stability. 

 

Diversity of development products: 

When you outsource your business requirements and goals, there is a good chance that your outsourcing team will provide you with more than one solution. It's easier to choose the most viable solution among many reliable results.



Customized data analysis solutions:

The entire financial industry is based on data collection and analysis. When you outsource your financial needs, you gain access to FinTech's customized software solutions that help them thoroughly analyze data on a sample of customers. These software solutions lead to increased sales and promote customer loyalty. This way, you can thoroughly track every prospect, from credit scoring to user buying patterns. 

 

In addition, outsourced data analytics companies are more likely to respond to every little detail in your business requests. However, every aspect of the business has its pros and cons. 

 

Pros and cons of outsourcing data analytics

As a fintech business owner, you must take into account not only the great opportunities but also the possible risks when it comes to outsourcing technology. Proper knowledge of the pros and cons will allow you to assess the picture.

 

The pros of outsourcing data analytics to FinTech 

 

Attracting competent professionals: 

The technical team you outsource will be experienced professionals in their field. They are more likely to handle the highly specialized tasks and business requirements critical to the growth of your FinTech. Not only that, research has shown that outsourced team members are 41% more reliable when it comes to delivering results on time. This shows that you have a competent team working for you.

 

Access to Best Practices and Technology:

 

Most FinTech startups and businesses can't afford to provide the latest technology to their data management team. A reliable outsourcing company offering data analytics services will be competent in current technologies and practices, as its primary goal is to offer you the most appropriate solution. 

 

New Opportunities:

 

Innovative technologies offer tremendous opportunities and benefits to financial institutions. 

These include real-time payment processing, cloud computing, wealth tech, cryptocurrencies, blockchain, chatbots, advanced analytics, etc. Imagine the number of solutions you can use for your business with these technologies. Thus, outsourcing technology is a smart advantage to explore such new technologies and create new opportunities for your financial enterprise. 

 

Cons of outsourcing data analytics to fintech 

Data analytics outsourcing has no major disadvantages except for a few factors that can be overcome.

 

Misunderstanding your business goals:

 

Your FinTech business may have nuances that need to be clarified with your outsourcing team. The right solution is to choose a service that specializes in your specific industry business. 

 

Information leakage:

It is critical to make sure that your outsourced data analytics company protects your data and safeguards it from unauthorized access. You can do this by signing a non-disclosure agreement with the company. 




Choosing the right FinTech outsourcing company

Outsourcing FinTech needs today is more of a necessity than an option. Here are a few essential tips to keep in mind when outsourcing. 

Experience

The main factor to consider is having a solid track record of developing high-quality FinTech solutions. Make a note of previous FinTech projects the company has worked on and their degree of success. The outsourcer company's portfolio should guarantee reliable services, easy integration and maintenance of data analytics solutions. 

Security

Security identification and authentication is another critical factor to consider when outsourcing FinTech data analytics. FinTech is an area that requires great accuracy and security in all operations and data. So make sure your outsourcing team prioritizes security over something of an afterthought.

Risk mitigation

Risk management is a basic decision-making plan for assessing, identifying, and dealing with risks in order to minimize potential losses. Don't forget that your business data will be at stake, so make sure your outsourcing team has a backup plan ready in case your main development plan fails. 




How can Sodeira Solutions help you with FinTech Data Analytics solutions?

As the market for outsourcing big data analytics continues to gain traction in the FinTech industry, it's safe to conclude that it will soon become a lifeline for prominent startups and businesses. With big data, your FinTech organization will become more adept at delivering a seamless customer experience on every channel. Over several years of development, Sodeira Solutions has successfully delivered data management solutions. 

 

From analytics consulting to data visualization, we can offer customized data analytics services for your FinTech business. Contact us to learn more.



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