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Three Whales of FinTech: AI, Big Data and Cybersecurity

According to the World Economic Forum, in 2018, for the first time, FinTech finally went mainstream with over 40% of all deals being global and not limited to the UK, China, and the USA as before. Today, the FinTech sector counts over 50 unicorns totaling altogether $147 billion in value. The vast majority of those companies specialize in peer-to-peer money-lending and bank loans services and solutions, followed by InsurTech, RegTech, and cybersecurity.

Since nothing speaks louder than facts and figures, we’ve reviewed some of the hottest trends and challenges facing the FinTech industry in 2019 and beyond.

Key FinTech Trends and Challenges of 2019 and Beyond

  • Peer-to-peer lending platforms will see a 48% increase YoY by 2024;
  • When it comes to FinTech API, the two leading categories are payments and financial services;
  • ⅔ of millennials are open to using financial services from trusted brands such as Nike or Google;
  • Loan rates are expected to increase in all major markets worldwide;
  • 75-80% of all IT budgets in banking are spent on maintaining the existing (or legacy) systems and applications;
  • Almost 90% of finance experts believe that investments in RegTech will keep growing during 2019;
  • 40% of the global population is still unbanked which opens up ample opportunities for FinTech startups and established brands;
  • By 2020, total penalties imposed on financial companies and banks for compliance violation will exceed $400 billion;
  • Last year, the following hyped unicorns entered the FinTech ecosystem: Revolut, Atom Bank, Plaid, Brex, Monzo, Toss, Stripe, Coinbase, SoFi, Credit Karma, Gusto and Robinhood;
  • This year, we see a significant shift from traditional plastic cards to contactless payment technologies, QR-payments and mobile payments;
  • Rapid development and implementation of biometric technologies such as face and fingerprint recognition;
  • More FinTech technologies will migrate to the Cloud.

FinTech rests on three whales: artificial intelligence (AI), Big Data, and cybersecurity. Let’s see how each helps bring FinTech to the next maturity level.

Artificial Intelligence Use In FinTech

Estimates suggest that by 2021, global AI investments will reach $58 billion, of which $10 billion will be invested by FinTech alone. AI allows FinTech companies to:

  • Identify patterns in Big Data and any deviations from them;
  • Make more precise predictions;
  • Customize products and tailor them to the most sophisticated client needs;
  • Make informed and data-driven decisions, and more.

Today, it’s common practice to set up Centers of Excellence within companies. AI enables a back-office-as-a-service model which allows banks to both add value and generate additional revenue and gather more data and insights for better business intelligence.

The more data goes through your systems, the faster the systems learn and the better your service becomes. As a result, those financial institutions that can’t eliminate their tech debt and replace legacy systems will never be able to compete with such corporate Centers of Excellence. After all, the winner isn’t someone who owns the algorithm, but someone who owns the data.

As a result, these centers will create a continuous cycle of product improvement: a great product attracts new users, who in turn generate new data, and new data again improve the product and make it even more customizable. Examples of such services are Google translate and Facebook. Competitors will have a hard time finding the data of millions of users to make their product better. Imagine that banks’ back-office processes have become almost the same. Under such conditions, a new force is emerging – service providers. It is they who will dictate their rules and set prices. Switching away from such Centers will become expensive and time-consuming.

Because lack of qualified tech talent remains a severe issue that slows down the evolution of emerging technologies, back-office-as-a-service will rely largely on FinTech solutions outsourcing, as it’ll give companies access to overseas talent pools and robust 3rd party expertise for in-sourcing.

How else can AI take banking to the next maturity level?

Customized products

Banks need to learn not only to create individual offers for customers but also to become their advisors and recommend them the best financial management solutions. Clients need to be so impressed that they want to share their data and maintain an interactive dialogue.

Customer attraction and involvement

AI-driven chatbots help personalize customer communication with banks and financial companies. They will help banks automate most of the service dialogues and add smart intelligence to customer interactions.

Creating ecosystems

Banks need customer data from all customer service providers (e.g., merchants, products, insurance, travel, booking services, and so on. For example, RBC Royal Bank pilots a predictive solution for car dealers. Based on customer data, the bank predicts the probability of buying a car. And of course, it offers an immediate credit solution.

Another good example is the Chinese company Ping An Insurance. The company creates personalized financial products. Having built a powerful ecosystem, it can now process data from 880 million users, 70 million companies and 300 partners.

Big Data Use In FinTech

Two simple facts will quickly explain why Big Data is a key trend. Numerous psychological studies have shown that 40% of all our daily activities and decisions are made by habit rather than conscious choice. In other words, we have developed solutions for different occasions not to overload our brains. This explains why data is so important – because if you know about your customers’ habits, you and your services can fit seamlessly into your user’s world. And they will eventually develop a habit of buying your product or service if you can deliver unparalleled FinTech UX.

Today, all products and services are designed to entice users to share data. Modern companies quickly realize that Big Data = Big Money. As an example, Apple and Google launched Apple Pay and Google Pay primarily to gain access to the financial data of their users.

Cybersecurity and Data Protection In FinTech

According to a recent survey of 1,200 companies, 71% have experienced some data loss or cyber fraud in past months. Approximately 46% of the data thefts occurred last year. As a response to ever-growing cybercrime rates, in 2018, the EU launched GDPR – the initiative aiming to protect personal data of all its citizens. Non-compliance with these rules can cost companies up to 20 million euros in fines. At the same time, it is believed that about 80% of multinational companies will not be able to meet all of the requirements.

As always, artificial intelligence comes to the rescue – almost 87% of U.S. cybersecurity professionals use AI to protect data and prevent hacker attacks. Unfortunately, we are still very far from reliable protection, and not every company has a cyber attack prevention plan in place.

Recently, many of us have been notified that Google+ is closing. The service was not very popular but still managed to surprise us with two massive data leaks: 1) data of 500,000 users was stolen and the information about the leakфпу wasn’t disclosed until six months later, and 2) data of 52.5 million users was compromised. These data leaks contributed significantly to the complete close down of Google’s social network.

Yahoo was hit the hardest by lack of data security: 1 billion users’ data was hacked as a result of multiple attacks.

In conclusion, the following trends will define the FinTech agenda in the months to come:

  • More in-depth customer understanding: behavior patterns, habits, performance, interactions, engagement, etc.;
  • Creating new products requires new skills and knowledge (AI, ML, DL, NLP, biometrics, data analytics, predictive analytics, and so on;
  • Tough competition for user data and user experience;
  • Most of FinTech data will be owned by large companies so smaller providers and startups will have to collaborate and create ecosystems around the data owners to take advantage of user data for own business growth and benefits.

The further evolution of FinTech is impossible without globalization and outsourcing, as resources and talents are in short supply in countries competing for global FinTech leadership (United States, UK, China, Israel, South Korea, etc).

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