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CURRENT FINTECH TRENDS  /
September 27, 2018
Viktoriya Polyarush Social Media Coordinator, an avid reader with the passion for technology.

With FinTech threatening to profoundly shake up traditional business models in industries ranging from insurance and banking to investment management, its soaring success and popularity is posing imminent challenges and opportunities for many existing players. It is an exciting time for FinTech as we start to see some interesting patterns emerge for the future. I would single out the following trends to be considered:

AI will be implemented across the stack

AI is sweeping across all industry sectors, including financial services, trading, and risk management (machine learning), and is being used to automate many back-office tasks. AI technologies are also giving rise to new fintech startups that use techniques like computer vision to unlock new datasets (e.g., aerial images). Besides, AI and machine learning are the top perspectives that traditional financial institutions should and are looking into in 2018 by partnering with FinTech entrepreneurs for outsourcing.

AI and machine learning are at the top of many financial companies’ research lists due to the vast benefits of using them in providing financial services. These technologies allow companies to gain insights into the expectations, preferences, and behaviors of their clients. This data (stored and operated as the Big Data) is the key to offering specific target groups the services and products they are highly likely to adopt. Consequently, using AI and machine learning is a promising path for entrepreneurs for boosting profits. Another advantage of using AI and machine learning is the opportunity to develop automated personalization software. It operates by gathering the Big Data about each client and analyzing it in order to personalize what they will receive on their devices. It makes the whole user experience more personal and, consequently, more pleasantly profitable.

Last but not least among the upcoming outsourcing trends, AI can be used for the development of next-gen chatbots. These chatbots are considered to be the future of interacting with clients by many due to their long-term cost-efficiency and availability 24/7/365. Although chatbots possess the intelligence of a three-year-old child as of now, machine learning technologies are expected to help them make a leap in intelligence and interaction quality in the next few years.

New products make advanced analytics easier

Talk to any vendor or startup in big data analytics or cloud computing and they probably have key customers in financial services. This means that many technology providers will create products tailored for finance (most likely products that comply with existing regulations), which lowers the barrier to using advanced analytics.

Blockchain technologies will be used in financial services products

Originally, blockchain technology was developed as a means for securing cryptocurrency transactions from hacking attempts. Each cryptocurrency transaction is a part of a block in a chain of transactions and is connected to the previous and next transaction. Thus, changes to a previous transaction require being approved by all the stakeholders that are a part of the chain. The system as a whole is also heavily encrypted with unique access keys for the stakeholders. Consequently, hacking into this system is considered impossible.

With security still being a challenge, more and more legacy financial institutions are considering implementing blockchain technology into their banking systems due to its unbeatable security mechanisms. Surely, with blockchain technology implemented, there will be no room for human error/mischief leading to massive hacks.

Some of the giant banks are already experimenting with the technology (among those are HSBC and Credit Suisse). Thus, blockchain technology implementation has the best chance to become one of the most demanded bank outsourcing trends. The technology is promising enough that interest in blockchains isn’t limited to financial services. Within finance, one area where blockchain technologies has grown rapidly is access to business capital (via ICOs).

Data partnerships increase

Companies have long sought more data to understand their customers. A typical consumer holds accounts with more than one financial services company. With more companies vying for the attention of consumers, data partnerships are being formed to enable companies to share (complementary) data securely.

We’ll see even greater regionalization and regulation in payments

Our daily transactions now involve payment systems (mobile, online, and offline) that didn’t exist a decade ago. This is an area where both startups and global companies are flourishing. The technologies, protocols, and players vary by region. For companies operating in the EU, PSD2 is a new 2018 regulation aimed at fostering innovqtion and competition in the payment industry.

Customer experience will be increasingly mobile

Judging by how much time users spend on them, platforms like WeChat, Facebook, and the iPhone will increasingly be how customers interact with financial services. This is particularly true in regions of the world where mobile phones are the only broadly available connected devices.

There will be increased pressure around privacy and security

GDPR is a new data protection regulation aimed at companies doing business in the EU . With Equifax joining the list of the worst security breaches of 2017, look for companies to start distinguishing themselves (again) on how they approach customer privacy and cybersecurity.

Investment And Financial Planning Software Is To Gain Popularity

Investment and financial planning software are one of the prospectives FinTech companies shouldn’t miss out on in 2018. The demand for such planners or automated advisers increases as the world gets busier and busier. Since there are online stock trading services available now, customers are in need of advisors on how to invest their hard-earned cash efficiently. Currently, those advisors are employees of investment companies. Yet, AI and machine learning can easily replace them if implemented into investments advisors software. Financial planning is already in a high demand, and this trend will keep expanding. Key improvements that should be expected are implementing personalization and automation in the planning and gathering of financial information processes through AI and machine learning technologies.