• Kathy Stares, Executive Vice President, North America at Provenir


• 28.01.2022 01:00 pm
#Pay #trends , Kathy is Executive Vice President, North America for Provenir, leading sales, customer success, professional services and pre-sales consulting teams in North America, while overseeing strategic partnerships. Provenir helps fintechs, financial institutions, and payment providers make smarter decisions faster by simplifying the risk decisioning process.

When looking at 2021 in review, two fintech trends factor prominently -- Buy Now, Pay Later (BNPL) and technology driving financial empathy/inclusion.

Organizations offering BNPL services recognized early on that to thrive in this increasingly competitive market, they needed to utilize technology that is flexible and scalable to rapidly adapt to evolving conditions; provides access to alternative data for smarter decisioning and faster onboarding; and enables decisioning across the entire customer transactional lifecycle to enhance customer responsiveness and improved speed-to-market.

Technology played a pivotal role in accelerating financial inclusion in 2021. The ongoing pandemic translated into economic uncertainty for millions across the globe. Banks and fintechs recognized this and adopted technologies such as AI and machine learning into their data models to help re-package loan terms to meet the economic needs of the customer. Utilizing technology that can quickly harness data to inform and enhance models to support real-time decisioning enabled banks and fintechs to react to changes and enable them to respond to customers in their time of need. 

We’re now seeing the theme of financial inclusion being embraced by the banking and fintech sector globally. Today, up to one-third of all adults globally lack any type of bank account, and as a result, are difficult to score for creditworthiness according to traditional methods. As such, alternative data will become a mainstream must-have in 2022 for inclusive credit decisioning. Current research underway by Provenir bears this out:

• Over 50% say the primary reason for using alternative data sources in its credit risk analysis is to serve the underbanked/unbanked. 

• Nearly 40% say the primary reason for using alternative data sources in its credit risk analysis is to achieve more accurate scoring.

In 2022, we will continue to see the growth of BNPL and technology investments that spur more accurate and timely data models, credit risk and real-time decisioning. 

The flurry of BNPL activity has not escaped the sights of traditional banks that will be more aggressive in the crowded BNPL market by offering new products or entering the market via acquisition. To succeed in the competitive BNPL space, traditional banks will need to overcome their longstanding challenges of legacy technology and speed-to-market. Many are partnering with fintechs that can quickly provide the right data modeling technology, accelerating banks’ ability to learn how their customers are utilizing the BNPL offering and use that information for cross-selling initiatives to retain and grow their customer base. 

Real-time data modeling technology will be key. Typically, data scientists take about 4-6 weeks to train these models which are then deployed months later (or sometimes are never even put into production). These models were only being refreshed perhaps once or twice a year which relegated them fairly worthless, particularly given all the disruption brought about by the pandemic. 

These key trends are based on the need for improved responsiveness and the imperative to be more sensitive and responsive to the specific needs of customers. Fintech offerings are evolving; and to compete, credit risk decisioning must evolve as well.