June 6, 2018
By Robert de Swardt, Head of Decision Solutions, Qarar
The term ‘decision solutions’ got me thinking…
A decision is a conclusion or resolution reached after consideration, and a solution is a means of resolving a problem or dealing with a difficult situation.
We are always looking to solve problems as quickly and as easily as possible, and we look to technology to help us achieve this.
In the credit and risk industry, a lot of buzz words are floating around like machine learning, bots, hosting in the cloud, AI, Big Data, Geo-location and Blockchain. What is this all about?
Decision solutions are changing how organisations run their businesses.
The real question is how do we provide the best credit we can with the least amount of risk? The answer is based on the credit policy defined by the organisation and making the right decisions at the right time.
We all have digital assistants that make our lives easier. I believe consumers want to spend more time with family and do less of the things that aren’t important, like waiting for a loan to be approved before planning the next family vacation. We want answers now!
Data can also be used to achieve the same for our financial health. Imagine a world where your bank offers you a digital financial assistant. If you want a loan for a vacation, you could simply ask your digital financial assistant and receive an answer immediately. For a financial institute the answers all lie in Big Data, which allows them to determine human behaviour and therefore make the right decision concerning approvals, or even upselling, downselling or cross-selling products.
A great example is using machine learning to automate decisions. Using algorithms, machine learning allows us to iteratively learn from data based on past outcomes and even suggested outcomes. This allows computers to find hidden insights and make recommendations without being explicitly programmed. It’s like giving someone a map of a city that they have never visited, and turning the unknown into the known.
When expertise and predictive analytics are considered, they are forced into a process of data definition and creation. In most cases, there are bottlenecks and hard-coded inflexible systems that indicate decisioning solutions as the ideal answer to streamlining business processes and taking out the human element of subjective decisioning.
Decisioning solutions are there to automate our lives and force uniform decisions on policy rules, business processes, predictive analytics and even BI dashboards and reports. This proven approach not only helps with meeting operational requirements and enhancing the user experience, but also allows for scalability, which is essential when it comes to using big data.
Considering the required functionality and vast array of systems available within the market, some of the challenges faced by lenders in implementing an automated decisioning solution are:
To satisfy these concerns, lenders must look to vendors and ask the top 4 questions:
Find a vendor that can make informed and profitable decisions with you, and work alongside you in a partnership instead of just as a supplier. In the ideal relationship, your goals become their goals.