The Palo Alto-based AI-enabled digital assistant platform provider for the wealth management and insurance industries, CogniCor, recently launched a first of its kind “knowledge graph” for the wealth management industry to support its range of digital assistants. This new product gives AI-enabled digital assistants context and background information to support RIAs and IBDs, enabling the assistants to learn quickly and integrate seamlessly into firms’ operations, according to the company’s release.
This year has seen significant activity from the fintech start-up with the launch of several new digital assistants, publishing a knowledge graph for the insurance industry and their acceptance in the Morgan Stanley Multicultural Innovation Lab.
DWN sat down with CogniCor Co-founder and CEO, Sindhu Joseph to get a better understanding of what these development means for the future of AI-enabled solutions within the wealth management space.
What is a knowledge graph specifically and how does it work?
A knowledge graph is the conceptual map, structured much like a huge drop-down menu, that groups together firm- and industry-specific topics, terminology and content. These digital frameworks give AI algorithms a knowledge base and context to interpret the intent behind users’ requests and return appropriate guidance.
You can think about a knowledge graph like a brain for a digital assistant. Without this brain, the assistant functions more like a specialized search engine. But when armed with a knowledge graph, a digital assistant functions more like an industry veteran that has all necessary information at its fingertips almost instantly and can automatically leverage that information to accurately, efficiently and cost-effectively address user questions and complete other tasks.
The general understanding of AI is that you feed a computer a lot of data and then it will learn enough to provide a user with answers to questions. How is that different than what you are doing a CogniCor with knowledge graph enabled AI digital assistances?
There are actually two fundamental approaches to AI. One is a machine-learning based approach in which an algorithm is put to the task of analyzing huge amounts of data to draw inferences and generalizations. This is called inductive reasoning, and it’s the predominant approach to AI among researchers in the United States.
Deductive AI, which I studied in Spain and forms the conceptual backbone of CogniCor’s technology, goes in the other direction. The algorithm starts with knowledge of what happens in certain instances and makes inferences on what is likely to happen in other, similar instances.
For example, you could show a young child several pictures of dogs and after she saw 25 of them, odds are she would be able to identify another picture of a dog based upon the information she learned from viewing those photos. But if you asked her if humans could fly like birds, she likely would be able to say no without having to accumulate 25 examples of humans failing in their attempts to flap their arms to take flight. She would be able to use the logical assumption that she has never seen a human fly like a bird and therefore they can’t do so.
Humans actually process information using a combination of inductive and deductive approaches to logical reasoning. This idea is the basis of CogniCor’s digital assistant platform, and requires the use of a knowledge graph to provide that baseline knowledge and context to interpret what users want and return appropriate, accurate and timely responses.
Why is the application of these kinds of AI solutions so critical at this moment within the wealth management industry?
The massive transfer of wealth from Baby Boomers to younger generations will require a scalable solution to enable a seamless transition from one owner to another. AI-enabled digital assistants can play a critical role in making this happen faster, at a lower cost and with fewer mistakes.
Similarly, we find ourselves at a crossroads for the professionals leading this industry. Most advisors are older and considering retirement in the next five to 10 years.
This provides an incredible opportunity for wealth management firms to change the status quo and introduce new tools, like our digital assistants, that may have seemed disruptive to established advisors but completely normal for the next generation. These tools will enable them to focus on the more important, revenue generative activities as opposed to spending so much of their time filling out requisite paperwork.
