Banks After PSD2

A 50% Increase in Client Conversions Can Be a Reality for Every Bank

There are many reasons and benefits for financial institutions to cooperate with fintech companies -- for example, Commerzbank increased conversion for customers who sought and downloaded the app by 50% through collaboration with fintech IDnow.

PSD2 requirements for Strong Consumer Authentication and the rise of open banking are a good start to think of this collaboration in the wider context. Banks already have credibility, stability, and consumer knowledge, and what they need from young start-ups is their speed and the innovative technology, not only to battle SCA. AI-based fintech firms might open new paths for financial institutions to intelligent offerings by using data and machine learning to truly understand users' motives and needs.

PSD2 SCA Banks and Fintech

SMS does not give you a competitive advantage. Despite the PSD2 program assumptions about increasing the innovation and safety of banking services, most banks choose to send SMS as an additional layer of security in the SCA process. Nevertheless, text messages provide neither integrity nor confidentiality of information. Over the past few years, attacks known as SIM swapping have been increasing and a Metro Bank case showed the concerns are still legitimate. German banks are already withdrawing from this form of authentication.

This form of authentication is also full of friction; it is not user-friendly and in the digital reality, user experience is the key ingredient to make clients satisfied. 92% of consumers demand a fast, frictionless experience while also getting one that is as trustworthy and secure as possible. It is then critical for banks to use identification methods that do not cause a negative user experience and, at the same time, guarantees top-tier security.

The good news here is that the extra layer of the authentication itself is not an obstacle for users -- studies show the opposite. One showed that 28.3 percent of respondents would be more likely to use their banking apps if their financial institutions added authentication options for specific transactions, and 33.2% of respondents would be more likely to use their banking apps if their FI covers potential mobile app fraud.

The problem then lies in the speed and the quality of this process and it all comes to selecting the correct method and technology that can be provided by fintech companies.

Behavioral Biometrics -- Intro to the Power of Data Analysis

One of the most innovative identification methods that many Fintech firms offer is based on behavioral biometrics -- the new quality of fraud prevention. It is considered a solution that covers the Inherence factor introduced by SCA in 2FA. By the end of this year, 1.9 billion bank customers will be using biometrics for different financial services. Moreover, this year the global biometrics market is estimated to grow up to $35.5 billion, and by 2025 to $55.5 billion.

What is great about this technology is that, if implemented the right way, it does not cause friction in the transaction process. It works in real-time at the background of the transaction -- not affecting the purchase process, making it totally user-friendly. There is no need for sending SMS or writing down PINs or passwords. It collects a massive set of individual, physical interactions between the user and his/her device. That includes, among others, keystroke dynamics -- a piece of detailed timing information describing when each particular key was pressed and released as a user was typing, including such data as flight time (the period between releasing a key and pressing next one) or dwell time (duration of a key being pressed) to recognize whether it's an imposter or a real user.

All those gathered data, which is the heart of behavioral biometrics, needs to be analyzed by machine learning algorithms to create and spot those specific connections and patterns of each user. Machine learning with behavioral biometrics as a whole can set totally new standards for banks, merchants, and customers, not only as a fraud prevention method.

The big picture here is the precise user profiling, thanks to all gathered data, allowing banks to truly understand the user's behavior, needs, what they are doing with the money, and as a result to customize the offer to each customer. So, while adjusting to SCA, banks can at the same time gain an additional competitive advantage for future purposes. Unfortunately, only one-third of CIOs state that they see the implementation of digital capabilities such as AI/ML-based banking solutions as the most important technology area to be focused upon.

Turn Data Into Opportunities

Data enrichment that comes with combining behavioral biometrics and machine learning is an extremely powerful tool that fintech firms bring to the table. It's a first step for banks to realize that using and analyzing available data with machine learning might start a new era of intelligent customer offerings. But only quality fintech companies can turn those data into opportunities -- growing revenues, dealing with SCA, recognizing customers' needs, and helping banks succeed for decades to come.

As Benny Boye Johansen, Senior Director and Head of OpenAPI at Saxo Bank said, "Every bank that wants to stay on the market until 2030 must already start developing its own open banking strategy." With PSD2, which demands a new approach to banking, the timing is perfect to introduce the strategy, which includes cooperation with fintech firms. The sooner banks see the advantage of this partnership, the better for their future. With the right mixture of fintech companies and banks, it's a win-win game for both sides.