Imagine these three characters really do walk into a bar together. They take a seat and begin talking about their priorities for the year. The banker commiserates about the latest regulatory deadline. The retailer talks about today's news about a top competitor. The accountant explains the challenges of ensuring there are no conflicts in taking on a new client. They order another round and continue the discussion.
You might be surprised how similar some of the challenges are across the banking, accounting, and retail industries. Over the last 12 months I've had the opportunity to work with leading executives across these industries and I enjoy how similar the challenges are across these three very different industries. In our fictitious bar example, I'd like to share where they find common ground...
- Customer Data - For bankers, customer data is required for regulatory reporting ranging from MIFID II to CAT. For retailers, customer data is critical in understanding millions of customers all around the globe. Accountants care too as they work with customers in nearly every country in the world and must maintain unique independence. The core issue, though, is a growing need to understand more and more about these customers while working to maintain quality of customer data across many legacy systems. They all need reliable, core reference data. They all need hierarchy and relationship data. Duplicate records are pervasive. The banking, retail, and accounting industries need additional attributes to better understand their customers.
- More Insight, Less Cost - Big banks employ hundreds of people to monitor negative news, corporate actions, and a wide variety of sources for KYC, AML, and other operational purposes. Retailers monitor local events and customer activity store by store and market by market, but not at an enterprise scale. Accounting firms look to legacy data feeds to identify changes in customers and markets that may indicate risk, independence issues, or opportunities for new business. They all are spending money on legacy systems, processes, and data vendors. They all are uncertain about how reliable this monitoring really is. All have a desire to do more monitoring and control or reduce their costs.
- Cognitive - Everywhere these banks, retailers, and accountants turn, there are reminders that artificial intelligence and machine learning are the way of the future. Banks are looking to automate repetitive processes and turn hundreds of thousands of documents that contain unstructured data to usable data and information. Retailers are working to automate decisions and improve the customer's experience at scale. Accountants are looking to cognitive to reduce risk and expand the services they can provide. They all feel the pressure to invest in these technologies. They must show progress with cognitive that drives business results.
These three categories of challenges are core to many large, global, data intensive businesses. They require accurate, yet constantly expanding data. They require new ways of performing critical processes better, but with an eye towards cost. And the good news is, cognitive is a great set of capabilities that can actually help both. Hopefully our banker, retailer, and accountant friends figured that out, but the real question is, who picked up the bill?