The financial services industry has long been a driver for technology innovation. In the aftermath of the 2008 financial crisis, volatile regulations, increased demands for compliance, and a requirement for transparency necessitate the ability to quickly create and easily manage decisions across systems. This is a perfect use case for DMN and its incorporation in the evolution of disruptive “FinTech” systems has attempted to address some of these needs. As the DMN standard is solidified, platforms become more mature, and more people are educated with respect to its power, we can move to examining more places where it can (and will) play a critical role.
Financial Technology (FinTech) used to just refer to technology that was used to enable back-end services in financial institutions. It has now expanded to include most all technology innovations across a wide spectrum of financial applications. It’s been considered a disruption as so many products and services have moved from silos and individual capabilities to generalized services available across the Enterprise.
This B2B use has spread to B2C as consumers have been enabled more than ever (think mobile banking) and have much more information and data available to them. We can certainly expect financial institutions to start applying AI techniques to all this data given the increased consumer access. This will enable them to better predict consumer patterns and behavior. Blockchain holds the potential to move and share more information securely. Robotic Process Automation (RPA) can integrate process rather than systems and applications and eliminate subjective decision making.
However, the climate now is one that is moving the opposite way as deregulation is occurring in many places in the financial universe. While that may minimize or even eliminate some standard compliance and reporting, it does open the door for other potential problems. Fears of an environment that existed as we entered the financial crisis of 2008 are starting to be considered:
“Lenders should not get so desperate chasing volume by originating lower credit non-qualified mortgage products that they are inviting the next regulatory crackdown”, said David Stevens, the Mortgage Bankers Association’s CEO.
We know that consumers are enjoying and embracing the new disrupted financial services market. According to a Harris poll commissioned by Fiserv, 69% of consumers already research loan options online and 68% said they review loan documents online. Among millennials, 48% said they would be comfortable researching loan options on their smartphone. As a result, the constant demand for faster online processes has created the need for Regulatory Technology or “RegTech”.
RegTech refers to using technology to help businesses comply with regulations more efficiently and inexpensively. But as more consumer data is powering an increased number of digital products, different kinds of regulatory measures are forcing new technology. Cloud computing enables the sharing of data between various entities. RegTech can use predictive analytics to weed through large amounts of data to both validate transactions and suggest issues in terms of previous failures. Shared data can be important when looking at Know Your Customer (KYC) regulations that look to detect and prevent potential money laundering. The more adept our technology becomes in a digital world, the more opportunities we create for potential abuse.
So where does DMN fit into this FinTech and RegTech puzzle? Not surprisingly, I believe it’s a key component across many of the disruptive technologies mentioned here. As always, the ability to create agile decision management systems – manageable by business – in a transparent and consistent fashion is a fundamental building block for most any FinTech or RegTech system. We’ve discussed those advantages many times. But it’s also a key complement for many of the new disruptive technologies described here.
With respect to artificial intelligence, decision management is a critical component. An oft-discussed issue with AI is the propensity for systems built on it to become a black box. Data goes in and answers come out. But how? Why? Auditable decisioning by incorporating DMN (no black box) can provide the needed clarity and transparency. With RPA, incorporating procedural logic for the process with decision logic results in a far more powerful system. Blockchain may provide even more possibilities. I’ve previously written about the concept of being able to exchange decisions far more easily when combining industry and technology standards. That shared message may be transported securely by the Blockchain. We may also use DMN for Smart Contracts and create self-executing contacts where we view the contract as code.
We’re entering into new uncharted technical territories driven by an ever-changing financial services landscape. Decisions and DMN are going to help us navigate those waters.
