This article was written in German, automatically translated into other languages and editorially reviewed. We welcome feedback at the end of the article.
Data & Artifical Intelligence for Banks
At Frankfurt Digital Finance, the emerging leaders of the COVID era are the ones questioning everything they've done before to figure out what really works and where investing in AI technologies can help them do it
Just in Banks continuity must be maintained under rapidly changing conditions. Beyond adopting technologies that simply increase productivity through automation, executives need to develop a deep understanding of the specific capabilities of AI technologies and vendors to decide where they can be useful in the challenges of distributed operations, fear of cash and contagion, extreme lending demand, and mortgage denial.
While data drives automation, information provides intelligence. That's the difference the financial services sector recognizes between technology adoption and digitization. Advances in artificial intelligence (AI) and machine learning (ML) have created the ability to go a step further in data extraction to identify entities and understand context. The capabilities in natural language understanding and generation (NLP), in particular, provide IT with access to the nuances in human language for the first time, and thus also to identify suspicious behaviors or previously unnoticed customer opportunities.
7 questions to IT providers of AI technologies at Frankfurt Digital Finance
Choosing the right processes to automate with digital technologies is critical and stems from understanding how people, processes and content interact as a whole. For Frankfurt Digital Finance, we have commented on 6 questions that can help you better understand the AI technologies used and maturity levels of AI providers.
A question that makes many people smile. As we find a very nice question to better understand the company and support culture. So you understand directly whether a central German-speaking service and helpdesk (2nd level) with reasonable response times is available.
Many new AI technologies have been developed on graphics cards without considering legacy infrastructure. Although the minimum requirements are often customizable, this question helps you understand the expectations with which the AI technology was programmed.
Rules in transaction entry are error-prone in operation, expensive to maintain, and offer no prospects for end-to-end automation (dark processing). Not everywhere that says AI on it is AI in it. Get an explanation of what automation is actually learned through AI and what components are rules-based. This question will help you understand what the AI software can learn and when an IT change request needs to manually adjust the ruleset.
In addition to certified security and ISO quality, migration and demigration concepts meet regulatory requirements. Security through encryption of communication with users, partners and third-party systems is already common. However, the question of server availability can only be answered quickly by AI providers that automatically report the availability of their servers.
In terms of marketing, platforms are flexible, fully documented, API-capable and suitable for numerous use cases and functional areas. Their core processor, which is not yet 100% "open banking", quickly becomes a stumbling block. Experienced providers talk about pitfalls and how to overcome them. Even if the future enables real-time exchange between systems of the entire organization via Open APIs as platform banking, you can try to understand what is possible out-of-the-box by asking this question.
Be curious about the images you will see. Beautiful visualizations do not mean functioning AI for a long time. However, many visualizations are worth seeing!
The answer offers possible new approaches to understanding the new normal not only as a requirement, but also as an opportunity to delight customers while getting the job done.
What does Konfuzio enable banks to do?
Not only is your workforce now dispersed, but your customers are dispersed like never before. Not surprisingly, your data is scattered, too. Content from onboarding documents and account services is captured on mobile devices in remote locations and flows into your business processes as individual transactions rather than as an aggregated file. Your document capture process needs to be able to seamlessly integrate with the customer engagement process, not outside of it.
Loan application, financing, notices and account statements: Classic processes in banks are paper-intensive. Checking and manual recording often takes several days and is not very customer-centric or transparent. With Machine Learning (ML) and AI, financing processes can be intelligently automated. This is because the relevant specialist data is automatically extracted from documents and is available in the processing procedure, whether for automated data entry, customer-centric self-services via scan or smartphone. Where others in Frankfurt are still struggling with the annoying paperwork in the financing application, you relieve your employees in the back office and offer your customers fast and transparent help in the application process - also for subsidized loans, guarantee and garnishment procedures or the analysis of payment flows.
To improve your banking processes and delight your customers, you shouldn't have to guess. Konfuzio enables you to gain the valuable, but often hard to come by, insights into your operations that enable true business transformation. With an intelligent approach that gives you access to better data from documents that enable true business transformation.
