How is digital decisioning automating the banking sector?

Banking automation is not just about the process, it's about rethinking how to use data collected to reliably make automated, informed decisions.

digital decisioning in banking

Whether it’s deposits, markets, lending, investments or any other corner of the industry, at the core of almost all banking is a transaction. That transaction is part of a process, and that process requires data and decisions in order to close it out. The two key participants in that process are the institution and the customer, with compliance and regulators watching from the sidelines. The primary objectives are accuracy of the outcome and adherence to the process, there has also always been a general expectation around timeliness too, although this expectation has amplified over time.

What was new quickly becomes a customer expection

Some people reading this may remember the good old deposit/withdrawal book – a little book of deposit slips that you would walk into the branch and hand over to the teller with your well-earned cash. That book was a record of the transaction and your record of the running balance. That deposit followed a (manual) process, required data, and relied on decisions to (eventually) see it completed.

Things have obviously changed a little since then, but whilst that nostalgic journey may sound archaic, it was less than a third of a generation ago. The introduction of ATMs (which have now started gathering dust) revolutionised retail banking and not only started the evolution of consumer behaviour but provided a crucial foundation for automation in banking that would solve many problems, and create a few new ones.

We now have a generation of consumers who know and expect nothing less than digital-native banking. Cashless payments, real-time clearing, no account numbers (just a mobile number) and loans approved and funded in minutes. None of this is achievable without a great deal of automation of process and decisioning, underpinned by data, and plenty of it.

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Using digital decisioning for transparency and compliance

Despite the neck-breaking speed of change we’ve experienced, the needs of the key participants remain somewhat unchanged. Customers want a successful (albeit immediate) transaction, the institution wants a happy customer and an accurate transaction that sticks to defined processes. What has emerged however, is a far more demanding regime of transparency from the regulator, who is ultimately looking to be able to monitor process adherence at an institutional and industry level, but also at a forensic level when something goes wrong. Satisfying this thirst for insight efficiently is the latest challenge for the banking and insurance industries.

Process automation and intelligent, real-time decisioning are key to the ongoing evolution of the banking sector. This is more than a mere technological challenge though, it often requires institutions to be prepared to stand at a whiteboard with an open mind and rethink what they do and how they do it, re-shaping their business processes into digital-friendly and data-oriented ones.

Most people think innovation in banking starts with process automation. However, the real frontier is in data (quality and quantity) and decisioning (how do we use it to make quicker, better decisions), which is key to allowing any process to move through its stages faster and with confidence.

“…the real frontier is in data (quality and quantity), and decisioning (how do we use it to make quicker, better decisions)"

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How the lending space is using digital decisioning

Banking automation is not just about the process itself but about how you rethink the data collected and how it’s used to reliably make automated, informed decisions. Also referred to as Digital Decisioning. A great example of digital decisioning driving banking automation is in the lending space.

The calculation of serviceability is an age-old and fundamental step in determining someone’s ability to service a debt. Who do you work for, how much do you earn, how long have you been working there – most of us are familiar with this line of questioning and can appreciate the basis of them. Reliability of income is assessed and what the customer can afford to repay is then calculated, based on rules set by the institution identifying what portion of income can be used to service the debt.

The arrival of open banking and the on-tap availability of transactional data has created an opportunity for organisations to start looking at transactional history to determine and validate income and expenses. The data is all there, it just requires interpretation. Deducing, rather than requesting from the applicant, the income and expenses data not only makes for a swifter application process, but also leads to decisions and calculations being made consistently and on meaningful, factual data.

At the nucleus of change is data

So whether it’s quicker loan decisions, rapid fraud and money laundering detection, or digital onboarding of customers, the banking industry is an ever-evolving landscape that will continue to benefit from automation. At the nucleus of change is data and the ability to automate decisions, driving speed, accuracy and traceability of process.

At Digital Experience Labs we are specialists in rules and process automation. We partner with organisations like Decisions and Microsoft to deliver smart and scalable automation solutions and have helped organisations of all shapes and sizes to set new foundations for a digital future. We’d love to help you too.

Luis Nejo | Founder & CEO

Luis Nejo | Founder & CEO

Luis is the CEO and founder of DXLabs and has spent 20 years leading technology innovation and strategy across a wide range of industries. A self confessed digital pragmatist, Luis is great at reading between the lines to find the hidden problems worth solving and building motivated, skilled teams that deliver solutions with an edge.

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