Since Open Banking and PSD2 came into place, banking APIs have gradually started to have an impact on financial services. By becoming more widely used in recent years, they have enabled financial institutions to leverage best-in-class third-party providers and offer better products.
While this development has improved customer experiences, it also brings value to institutions in reducing operational costs and creating opportunities for additional revenues. This potential is particularly large for markets where APIs haven’t been as widely adopted, namely SME lending.
How could APIs introduce efficiencies in this field? Consider data processing and decisioning, which are arguably two of the more costly and time-consuming parts of the process. Through third-party technologies, institutions can gain instant insights about their customers and consequently make attractive offerings such as tailored financing. This is exactly what Spotcap’s Business Bank Account Insights ML does with years of SME lending data.
Here’s how it works: by “consuming” Spotcap’s proprietary risk assessment algorithm, not only can institutions pre-score SMEs on their risk level, but also make fast credit decisions — in some cases, in less than a minute. To achieve this prior to Open Banking, they would have needed to build entire platforms internally, but with products like Business Bank Account Insights ML, all they need is an API call and their customers’ transactional data.
Why transactional data
Transactional data provides a real-time snapshot of the customer’s financial health. Compared to annual accounts, this type of data holds more up-to-date information and provides insights such as:
- Trends in income and expenditure
- Available balance over time
- Supplier and customer concentration
- Regularity of administrative payments
By interpreting these bank account characteristics, our decisioning technology calculates a probability of default and recommends a credit amount suited to their current financial performance.
Combined with more traditional financial indicators, these insights have played a major role in keeping single-digit default rates below market average in our direct lending operations. All of which we have achieved while delivering a decision in less than 24 hours — a feat made possible through strategic automation.
Where APIs and automation combine
Finally, by leveraging external insights through APIs, institutions have the opportunity to cut down on manual tasks in their own system. Let’s look at two examples of how this could work.
Firstly, institutions can automatically reject applications that are far beyond their risk threshold. By pre-scoring applications before they reach an underwriter, algorithms from external APIs identify cases where the probability of default is too high, and deliver a rejection to the customer. This spares time and resources, which can be invested in cases that pass through the risk threshold.
Alternatively, institutions can automate cases which reach a limited credit amount, and therefore pose a limited level of risk — for example, for applications up to 50,000. If the customer is within the maximum risk threshold, external algorithms can automatically deliver an approval and cut “time to yes” from days to minutes. The institution delivers a fast and seamless experience while capturing additional revenue without any manual work involved.
The possibilities through API integrations are endless. By leveraging technologies from third parties, financial institutions can quickly take hold of new opportunities in the SME lending space, deliver seamless experiences, and find ways to increase their productivity without compromising on quality.
Originally published January 28 2020 , updated February 7 2020