Algorithmic banking is the future of retail banking. But what do we mean when we call a bank “algorithmic”? The definition of an algorithmic bank is one that uses mathematical algorithms, data, and data science to drive better decisions to improve customer satisfaction, their profits, and to sustain relationships. They are customer obsessed. Algorithmic banks are agile. They develop new products faster and more quickly than their non-algorithmic counterparts and identify opportunities to shift and learn. Being an algorithmic retail bank means culture and technology work together to complete projects. It’s not just about technology. How can your bank up their game to the next level and become an algorithmic bank?
Watch our recent webinar: “The Algorithmic Retail Bank” given by analytics heavy-hitters David Rosen and Shawn Rogers. Many financial institutions used the past several years to build big data assets, ramp up their data processing and analytic capabilities, and even invest in new hires with explicit statistical or data science backgrounds. However, few banks have yet to realize the return on that effort and investment.
Now is the time to start benefiting from all the investments your bank has made in big analytics over the last decade. You’ve collected all the data on your customers, you just need help to sort through the fog of information. You need analytic engines that build upon the data you’ve stored about your customers’ behaviors, accounts and preferences, integrate real-time event data, and trigger the most ideal next action based on that combination of data. To accomplish this, we recommend a Systems of Insight approach.
In order for a System of Insight to operate correctly, you must bring to bear the right pieces that line up with the needs of your particular project, adding data virtualization, data science, visual analytics, and streaming analytics when necessary. Systems of Insight is a more modular approach that works with the people, processes, and technologies that you already have. And, they are interchangeable depending on what particular type of problem you are trying to solve.
Basically, it’s all about alignment. Matching the right people, with the right technology and processes, at the right time. Watch our webinar now to learn more about how you can bring your bank to the next level and how you can be a leader in this industry using AI and Machine Learning.
