A Deep-dive into Quantexa’s GenAI Assistant for Decision Intelligence: AiThority Tech Bytes with Dan Higgins
Quantexa’s Chief Product Officer, Dan Higgins explains his company’s role in transforming Decision Intelligence SaaS with GenAI.
Last month, leading decision intelligence solutions software provider, Quantexa unveiled its generative AI (GenAI) assistant Q Assist at the QuanCon24 event. During the event, Quantexa tapped its partnership with Microsoft to reveal its product roadmap for Decision Intelligence capabilities, powered by AI and data analytics. As part of the company’s growth strategy for 2024, Quantexa showcased its ability to use GenAI to build a trusted data foundation for mid-sized banks in the US. The Quantexa AI Stack will pilot Decision Intelligence programs to tackle financial crime, fraud, and risk, and to identify new revenue opportunities with customer intelligence. The company’s growth strategy will deliver greater effectiveness for customers in banking, telecommunications, and government agencies. In our latest AiThority Tech Bytes interview, Quantexa’s Chief Product Officer, Dan Higgins explains his company’s role in transforming the existing AI SaaS and banking technology marketplace with new technologies and solutions.
Here’s the full interview script with Dan.
Hi Dan, welcome to the AiThority Interview Series. Could you tell us how you started in the data and analytics industry?
My experience in the data and analytics industry dates back to the start of my career, actually. Early on, as a new staff consultant with Arthur Andersen, I helped companies adopt and implement various ERP and business intelligence solutions that leveraged data and analytics to enhance operations and deliver greater business insight. I grew into roles building and leading data warehousing practices, and eventually spent over 22 years at EY culminating in leadership of their Technology Consulting business globally. In this role, I was responsible for setting global strategy for the $5.5 billion business and helped to shape the firm’s platform, product, and asset strategy. I drove infusion within client teams and sector leaders to ensure the technology was embedded within our end-to-end solutions while also advising and participating in global client solutions and opportunities.
This eventually led to my current remit as Chief Product Officer at Quantexa, where I am responsible for our product vision, strategy, and roadmap. Our mission of empowering every organization with the right data to make the right decisions guides our product direction to help our customers build their trusted data foundation, helping them uncover hidden risks and opportunities using context in data and analytics to protect, optimize, and grow their organizations.
You have conceived and led a decent number of successful strategies in the data and analytics industry. Which one of these is your favorite and why? How did you measure the success and impact of this strategy?
As part of a global Women in Tech program that I sponsored, I drove the development and deployment of a STEM-learning encouragement platform which targets girls aged 13 – 18 years old, aiming to help them enter, remain, and thrive in the field of technology. The mobile app has a heavy focus on data and analytics and is now deployed to almost 100,000 girls globally.
I list this as one of my favorite initiatives because of the measurable impact that we were able to achieve.
As the son of a strong woman in the medical field, the husband of a Ph.D. in Biomechanical Engineering, and the father of two daughters who aspire to careers within STEM – I have a personal passion and purpose to help address the gender gap in these critical fields.
Through hard data and analysis of how girls are using the platform, we were able to measure the direct impact we were having in terms of how much time was being spent learning, subjects of greatest interest/motivation, the contributions being made to others on the platform and the societal uplift that the girls were making via the platform. I rank this as one of my proudest and most rewarding achievements in my career.
How has your leadership style changed in the last 4 years through the pandemic era? What challenges did you face in your role that led to these changes?
When the pandemic originally hit, I was leading a global team of over 40,000 professionals.
Given the scale and spread of that organization, there were many aspects of my operating model that already relied upon virtual connection and remote working. Most of my team was already well-equipped and well-practiced in many of the tools and techniques that became ‘the new normal’ for working day-to-day. That said, there were several impacts of the pandemic that went well beyond the structure and cadence of daily working habits and tools. Many of our professionals were also dealing with the emotional aspects of much more isolated interactions and a heightened level of uncertainty about what the ‘future of work’ held in store for them. Many had new and different pressures being applied as schools closed, freedom of movement was restricted and so much of the usual conveniences became more complicated. As a result, I had to step back and really think about my approach to leadership.
We dialed up my focus on reassuring teams that we had their back and that their continued engagement and commitment were critical to our collective success. I pivoted to more video-based communication and less email given the decrease in real physical interaction.
Personally, my camera was always on and I went out of my way to be expressive and present in all conversations. When travel started to open up again, I prioritized visits to my larger teams and the ones that I hadn’t seen for the longest duration.
Support for flexible working arrangements evolved from being exceptions to becoming business-as-usual and we also took a hard look at our career framework to consider what changes we needed to make going forward.
From an operations perspective, there were several interesting dynamics that played out in the data and analytics consulting industry. For example, the profitability of the business lifted as our travel expenses reduced significantly, while client demand for our services and support remained high. Balanced against that, we had to allow for increased home office and other work-from-home expenses.
What is Quantexa’s ICP – what kind of problems do you solve for your customers in these areas:
- Finance
- Health and social care
- Telecom
- Government
We are a market-leading decision intelligence platform. We enable our customers to create a trusted data foundation by helping them connect disparate and siloed data across numerous internal, external, structured, and unstructured sources. We apply contextual analytics, utilizing various components of artificial intelligence, to transform that connected data into intelligence. We support, augment, and automate decision processes to harvest insight from that intelligence. From this insight, we help our customers solve specific business problems across their enterprise value chain – helping them to protect, optimize, and grow their organization. Our platform is being used in several different industries, for example:
Finance: The growing volume of financial crime remains a top concern for enterprises and government agencies. For financial services company, HSBC, the deployment of Quantexa’s Decision Intelligence (DI) Platform provided the company with effective money-laundering controls that relied on context, rather than rules-based analysis. The Know Your Customer (KYC) approach has allowed the bank to take advantage of vast amounts of data at its disposal – resulting in early crime detection and prevention.
Healthcare and social care: Faced with an increased volume of patients during winter seasons, Quantexa’s ‘Patient 360’ approach provides healthcare facilities with a comprehensive, holistic view of patient’s health by aggregating and integrating data across multiple sources. This includes a patient’s medical history, clinical data, lab results, and medication records to provide personalized medicine and empower patient engagement.
Telecom: Tasked with managing a complex data landscape due to legacy systems, distrust in AI, and barriers to delivering data-driven insights, the deployment of Quantexa’s DI Platform provides companies with a full picture of dispersed data for more informed decision-making. For global tech communications company, Vodafone, this data visibility provides a single view of customer interactions, enhancing the overall customer experience.
Government: To combat rising COVID loan fraud rates, Quantexa’s AI-powered platform has helped government agencies uncover the more complex cases of fraud that have thus far gone undetected. In 2023, the UK’s Public Sector Fraud Authority (PSFA) began leveraging AI to identify cases of fraud committed through the government’s Covid Bounceback Loan Scheme. As a result, the PSFA has witnessed taxpayer savings amounting to more than $300 million.
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The UK has emerged as a hotbed of start-up innovations and economic growth. How is Quantexa influencing the business environment and talent pool in the UK with its vision and objectives?
In July 2023, Quantexa announced a $250M investment in AI (to be made by 2027) across the US and UK aimed at accelerating enterprise and government agencies’ ability to use trusted AI-enabled Decision Intelligence solutions. $105M (£50M) in dedicated UK investment will create over 170 new jobs in the London AI Innovation Centre team over the next 2-3 years. We are actively engaged in critical discussion concerning the future of UK tech, innovation, and AI – including the recent AI Safety Summit and other related forums.
Could you tell us more about the “Quantexa Decision Intelligence Platform Roadmap?” How do you use your data foundations to scale AI and Contextual Analytics?
Quantexa’s latest platform roadmap is designed to help customers break down organizational siloes and build a strong foundation of data for AI, including:
Powering human/AI decisioning
Pioneering solutions and tools to enable the use of multiple data sources and AI to automate business decision logic across various applications. The platform provides enhanced workflow capabilities including new customizable scoring, alerting, and decisioning models.
Operationalizing data at scale with AI and contextual analytics
The ability to help customers build a trusted data foundation and gain single customer views remains a top driver of platform adoption. The platform is moving beyond news intelligence – to support the ingestion and analysis of any unstructured data source via entity resolution and give the ability to customers to enable large-scale graph analysis and graph machine learning by combining large language models (LLMs) and knowledge graphs.
Accelerating time-to-value through simplified deployments and packaged solutions
Making it easier for customers and partners to implement new deployment methods including out-of-the-box configurations and low-code and no-code tools.
Seamlessly integrating with customers’ existing technology stacks and processes
Quantexa’s Decision Intelligence Platform has an open and extensible architecture with scalable APIs and streamlined integrations with downstream applications and systems.
Please tell us more about your Technology Partners. How do you plan to build AI SaaS solutions for banking and finance customers?
With AI at the core of Quantexa’s Decision Intelligence (DI) Platform, the company helps customers unify their data and create context to make accurate and reliable decisions. Quantexa’s AI is flexible, explainable, and adaptable, allowing it to address a wider set of business problems and deliver more powerful solutions for customers.
One exciting example of how we are collaborating with strategic technology partners is our recent announcement of advancement in our partnership with Microsoft.
This announcement included the first details of Quantexa’s new cloud-based AI-powered SaaS solution for anti-money laundering (AML), built in conjunction with a consortium of US mid-sized banks powered by Microsoft Azure. As part of Quantexa’s growth strategy, the solution relies on AI to build a trusted data foundation and bring greater effectiveness to existing decisioning processes, while seamlessly integrating into customers’ existing technology infrastructure.
You recently wrapped up the QuanCon 24 – What were the key takeaways from the conference?
In partnership with EY, KPMG, PwC, Dun & Bradstreet, and Moody’s, QuanCon 24 invited industry experts from government agencies and enterprises to speak on their top strategies for growth and optimization within their businesses.
At this year’s UK conference, Quantexa revealed its Decision Intelligence Platform Roadmap in addition to announcing our strategic partnership with Microsoft. It was clear from the discussions throughout the event that organizations across multiple industries, our partners, and industry analysts see the incredible potential that decision intelligence offers – whilst also acknowledging the importance of transparent, safe and secure adoption of AI. It was refreshing to see this confirmation and alignment with Quantexa’s corporate and product strategy.
Your take on the EU AI Act – how do you see this milestone regulation expanding the scope of AI-led innovations in the UK and EU?
As the world’s first comprehensive AI law, new regulations under the EU’s AI Act will seek to implement new guidelines on managing data and navigating AI for companies operating within the region as well as third-party providers worldwide. Among the top areas of focus under the act include transparency and safety – with the goal of targeting and preventing misuse through deception, deepfakes and disinformation.
The act categorizes AI tools and systems based on risk level with higher-risk models facing increased regulation and banning those it deems at an unacceptable risk level. AI innovation in the UK and EU will undoubtedly be enhanced through this system of adoption – increasing user trust and legal certainty to bolster the demand for AI used by companies as well as providing greater access to markets for AI providers. For SMEs and startups, the creation of real-world testing and regulatory sandboxes will lead to a more controlled and regulated environment leading to developing and deploying AI.
What is your prediction for the global data and analytics software DevOps market? Any particular area that you want the CPOs and CTOs to focus in 2024-2030?
As the adoption of artificial intelligence, and especially GenAI, increases, I expect the intersection of data engineering and DevOps to become even more important and relevant. At Quantexa, we acknowledge that AI-powered analytics are only as good as the quality and context of data being used to train models and being analyzed by models. In order for industry and society to truly benefit from advancements in data and analytics platforms, CPOs and CTOs will need to account for this and build it into their strategic and operational plans.
Thank you, Dan! That was fun and we hope to see you on AiThority.com’s Tech Bytes interview again!
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