5 FAQs About Adopting Behavioural Data to Lift Digital Banking Experiences in 2022

30/12/2021

Credolab and Strands recently co-hosted a webinar to discuss this very problem. Our Chief Product Officer Michele Tucci and Strands’ Product Owner Joan Alfonso delved into how retail banks can combine behavioural and transactional data to deliver a better digital banking experience to their customers.

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Retail banks often struggle to enhance engagement and extend long-term value to customers. 


At the root of this problem is a shortage of relevant data. This makes it difficult to make good recommendations and equally difficult to bring more potential clients to their products.


Credolab and Strands recently co-hosted a webinar to discuss this very problem. Our Chief Product Officer Michele Tucci and Strands’ Product Owner Joan Alfonso delved into how retail banks can combine behavioural and transactional data to deliver a better digital banking experience to their customers.


The webinar, which you can listen to on-demand right here, featured a range of questions from the audience. Here’s a quick recap of the best ones.

1. Can you provide a quick example of behavioural data in use?


These are two different types of behavioural data. Both of them fall under the bucket of alternative data. Alternative data is anything besides credit bureau data. When credolab started in 2016, we focused exclusively on analysing digital footprints. Now we work with nine industry verticals. Across each vertical — whether that’s e-commerce or buy, now pay later — we are mapping how customers interact with apps and application forms. So, for example, with their consent, we can analyse how fast they type and how much time they spend writing an answer, and that’s a small part of how we can correlate risk and build out alternative credit scores.

2. Is accessing customer data done ethically, and how do you protect and secure customer data?


We access only privacy consented data. So the customer must actively grant their permission. We are not a data controller because we don't process personal data. So the data controller is the bank. We are a processor of the data being controlled by the bank. Not only that, we go through different assessments. There is an info security assessment, data governance, ethics, and other regulatory and compliance needed in different countries and regions. A bank is free to choose to audit our software developer kit (SDK) at their own expense too.

3. How long does it take to implement behavioural data for a bank?


Roughly 95% of all credolab deployments are on the cloud. Some customers use a proxy implementation, where the anonymous data we collect goes first to the bank and then to us. A standalone bank implementation may take between two to five days.

4. How does insight-driven banking (Strands Engager) support credolab scoring mechanisms to build financial wellness journeys? How does it benefit Financial Institutions and end-users?


The Engager platform allows Financial Institutions to create fully customised experiences for their customers thanks to Engager’s insights by applying advanced ML models. Furthermore, when integrated with credolab, Engager can provide full flexibility to manage the financial wellness journeys.

Engager allows the Financial Institutions to increase their revenues and customer satisfaction by starting meaningful digital conversations whenever the customers need it the most, making day to day finance easy. 

5. Can your data help us provide products like buy now, pay later?


Yes. And it’s probably a good idea too, given that an Attest study discovered that almost half of consumers would spend more using buy now, pay later if credit checks had taken place. BNPL platforms currently operate in the absence of traditional financial data. But our innovative digital solution assesses customer creditworthiness by analysing their digital footprint from their phone in less than one second. So we can filter the real risks from artificial ones and ensure a seamless online and mobile purchasing experience with BNPL.

Discover how behavioural and transactional data, combined with advanced machine learning algorithms, can facilitate great digital banking experiences for your customers.


To learn more about our solutions, click on the links below book a demo now to speak to our experts:

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