Data Analytics & AI for Financial Services Summit | Day 2:
7:30 am
REGISTRATION & NETWORKING BREAKFAST: BUILD COMMUNITY CONTACTS
- Start your day off right and connect with data analytics leaders in financial services.
- Get to know your industry peers and colleagues over a delicious breakfast.
- Source practical tips, discuss best practices, and prepare for the day ahead.
8:45 am
OPENING COMMENTS FROM YOUR HOST
Gain insight into today’s sessions so you can get the most out of your conference experience.
9:00 am
OPENING EXECUTIVE PANEL: THE INTELLIGENT FINANCIAL INSTITUTION
Where Will Data and AI Actually Change the Economics of Financial Services?
The next phase of data and AI will be measured not by adoption, but by whether it fundamentally improves the economics of financial services. From acquiring and serving customers to underwriting risk, preventing fraud, and transforming operations, determine where intelligence can materially change growth, cost, and risk. Explore how to:
- Identify where data, analytics, and AI can create the greatest economic advantage across customer growth, pricing, underwriting, fraud, advice, and operations.
- Reinvent high-value financial services decisions and processes rather than simply using AI to make existing workflows incrementally faster.
- Concentrate investment on capabilities that can materially improve revenue, cost-to-serve, productivity, loss prevention, and customer lifetime value.
Drive profitable growth and competitive advantage by focusing data and AI investment on the financial services economics that matter most.
9:30 am
INDUSTRY EXPERT: WHERE SHOULD YOUR DATA LIVE?
How to Build the Right Cloud, Data, and AI Infrastructure for Financial Services
Financial institutions need the flexibility to access rapidly evolving cloud, data, and AI capabilities while protecting sensitive financial information, maintaining critical services, and managing third-party concentration risk. Rather than treating cloud as a destination, build an infrastructure strategy around the requirements of each workload. Take away practical strategies to:
- Determine where customer data, payment systems, risk platforms, analytics, and AI workloads should run based on sensitivity, latency, resilience, regulatory requirements, and business value.
- Design hybrid architectures that connect on-premise, private, and public cloud environments without creating unnecessary data movement, duplicated infrastructure, or new operational dependencies.
- Build portability, observability, and resilience into critical workloads so your institution can adopt new data and AI capabilities without becoming dependent on a single technology provider.
Reduce technology concentration risk, strengthen operational resilience, and accelerate innovation by putting every financial services workload in the environment where it performs best.
10:00 am
ROUNDTABLES – DISCOVER THOUGHT-PROVOKING IDEAS
Take a deep dive down the innovation rabbit hole in one of our roundtable discussions. Share common challenges and best practices with your data analytics peers on a topic of your choosing:
- Where Is AI Actually Delivering ROI in Financial Services?
Share which use cases have moved beyond pilots, where measurable value is emerging, and which investments are proving difficult to justify. - How Much Autonomy Are You Really Ready to Give AI?
Compare where institutions are comfortable automating decisions, where humans remain essential, and what needs to change before greater autonomy becomes acceptable. - Is Your Data Foundation Actually Ready for AI?
Discuss the practical blockers — data quality, access, integration, metadata, legacy architecture, and ownership — that are still slowing AI and analytics initiatives. - How Do You Build a 360° Customer View That Actually Changes the Customer Experience?
Explore identity resolution, real-time signals, customer intelligence, personalization, and next-best action across banking, wealth, insurance, and payments. - Can Financial Institutions Keep Up With AI-Powered Fraud?
Examine synthetic identity, deepfakes, scams, and transaction monitoring, and how customer, identity, behavioural, cyber, and AML signals can be connected faster. - What Should the Data and AI Team Look Like in Three Years?
Debate centralized vs. embedded teams, data-product ownership, AI teams, governance, skills, funding, and how the role of the data function is changing.
11:00 am
EXHIBITOR LOUNGE: VISIT BOOTHS & WIN PRIZES
- Explore the latest financial data analytics technology and strategies with our industry-leading sponsors.
- Share your challenges with the biggest innovators in the business.
- Schedule one-to-one private meetings for personalized advice.
11:30 am
CASE STUDY: A 360° VIEW ISN’T THE FINISH LINE
How to Turn Customer Data into Customer Intelligence
Banks and wealth managers already hold enormous volumes of customer, account, transaction, product, and interaction data. The challenge is connecting those signals into intelligence that can identify changing financial needs and determine what the institution should do next. Build a practical customer-intelligence capability to:
- Resolve customer identities and connect account, transaction, product, digital, advisor, and interaction data into a trusted, continuously updated customer profile.
- Apply analytics and decisioning to identify life events, changing behaviours, attrition risk, product needs, and next-best opportunities across banking and wealth relationships.
- Embed customer intelligence into digital channels, CRM, and advisor workflows, so insights trigger timely offers, interventions, and personalized financial experiences.
Increase customer lifetime value, deepen financial relationships, and accelerate revenue growth by turning connected customer data into timely, actionable decisions.
11:30 am
CASE STUDY: BEYOND PREDICTING LOSS
How to Turn AI into an Underwriting Advantage
Richer datasets, advanced analytics, and AI are creating an opportunity to move beyond predicting what is likely to happen toward identifying emerging risks. The competitive advantage increasingly lies in using your data for better underwriting decisions. Source practical tips to:
- Adapt traditional actuarial information with new internal and external data signals to create a more dynamic understanding.
- Bolster advanced analytics and AI to improve pricing accuracy, strengthen risk selection, and identify changing exposures.
- Advance from predicting risk to actively preventing it by translating intelligence into earlier interventions.
Improve underwriting profitability, reduce preventable losses, and strengthen your competitive advantage.
11:30 am
CASE STUDY: THE MOMENT THAT MATTERS
How to Turn Real-Time Payment Signals into Real-Time Decisions
Payments and fintechs generate some of the richest real-time signals in financial services, yet much of that intelligence is still analyzed after the transaction or customer moment has passed. Build the capabilities to interpret live payment, transaction, and behavioural data and trigger the right decision while there is still time to act. Take away practical strategies to:
- Connect transaction, payment, merchant, behavioural, and contextual signals through streaming data infrastructure to understand what is happening as transactions occur.
- Apply real-time analytics and decisioning to trigger personalized offers, payment routing, customer interventions, retention actions, and other next-best decisions.
- Embed decision engines directly into payment and fintech journeys so intelligence can trigger actions in milliseconds rather than feeding another retrospective dashboard.
Increase conversion, customer value, and transaction efficiency by turning live financial signals into intelligent action at the moment it matters.
12:00 pm
INDUSTRY EXPERT: WHEN THE CUSTOMER CONTROLS THE DATA
How to Win in Consumer-Driven Banking
As customers gain greater control over how their financial information moves between providers, banks need to turn consumer-permissioned data into something they can securely connect, understand, and activate. Build the data foundation and capabilities required to compete in a more open financial ecosystem. Take away specific solutions to:
- Connect customer-permissioned data with existing customer, account, and transaction information through secure APIs, identity, consent, and interoperable data architecture.
- Activate newly connected financial data through analytics and decisioning to improve onboarding, personalization, financial advice, credit decisions, and customer engagement.
- Develop new products, partnerships, and customer experiences that capitalize on financial data moving more securely between banks, fintechs, and other providers.
Accelerate customer acquisition, deepen financial relationships, and unlock new revenue by turning consumer-permissioned data into better financial products and decisions.
12:00 pm
INDUSTRY EXPERT: WHEN SHOULD AI MAKE THE CALL?
How to Build the Next Generation of Underwriting
AI is giving insurers new ways to automate routine decisions and identify risk faster. The challenge is connecting data, models, and underwriting workflows without losing human judgement where it matters. Take away practical strategies to:
- Connect internal and external data with predictive models and AI to create faster, richer risk assessments.
- Automate routine underwriting decisions while routing complex or higher-risk cases to the right underwriter.
- Embed AI directly into underwriting workflows with clear decision thresholds, monitoring, and human escalation.
Increase underwriting efficiency, improve risk selection, and accelerate profitable growth through smarter, more automated decision-making.
12:00 pm
INDUSTRY EXPERT: PAYMENTS WITHOUT PAUSE
How to Build the Data Infrastructure for Real-Time Payments
As payments become faster and always-on, the underlying data infrastructure must keep pace. Payment providers need to process transactions instantly while maintaining reliability, intelligence, and control. Take away practical strategies to:
- Build resilient, real-time data infrastructure that can support always-on payments and growing transaction volumes.
- Connect transaction data, analytics, and decisioning to improve routing, authorization, and payment performance.
- Modernize legacy payment architecture through APIs, streaming data, and interoperable platforms that can respond in real time.
Increase transaction efficiency, resilience, and customer value by building a faster, more intelligent payments infrastructure.
12:30 pm
NETWORKING LUNCH: DELVE INTO INDUSTRY CONVERSATIONS
- Meet interesting speakers and pick their brains on the latest data analytics issues.
- Expand your network and make connections that last beyond the conference.
- Enjoy great food and service while engaging with your financial services colleagues in data.
1:30 pm
EXHIBITOR LOUNGE: VISIT BOOTHS & WIN PRIZES
- Browse through different sponsor booths and test drive new technology.
- Enter your name for a chance to win exciting prizes.
- Take advantage of event-specific offers and special content.
1:45 pm
CASE STUDY: BEYOND THE COPILOT
Where Generative AI Is Actually Creating Value in Financial Services
Financial institutions have moved quickly from GenAI experiments to production applications. The priority now is finding the use cases that deliver measurable value and can scale across the business. Build a practical roadmap to:
- Target high-value applications across customer service, advisor support, operations, research, compliance, and knowledge-intensive work.
- Move successful GenAI use cases into repeatable workflows by connecting them to trusted enterprise data, systems, and processes.
- Measure value through productivity gains, faster decisions, lower operating costs, improved service, and increased adoption.
Increase productivity, reduce operating costs, and strengthen customer experience by scaling the GenAI applications that deliver measurable financial services value.
1:45 pm
CASE STUDY: AI-READY INFRASTRUCTURE
How to Defend Financial Services Against AI-Powered Fraud
Generative AI is making it easier for fraudsters to impersonate customers, create synthetic identities, and manipulate traditional verification processes. Financial institutions need stronger ways to establish who they are dealing with throughout the customer journey. Take away practical strategies to:
- Connect identity, device, behavioural, and transaction signals to detect suspicious activity across onboarding, authentication, and payments.
- Strengthen identity verification against deepfakes, synthetic identities, and AI-enabled impersonation without creating unnecessary customer friction.
- Apply real-time analytics and adaptive authentication to increase scrutiny when risk changes and intervene before transactions or accounts are compromised.
Reduce fraud losses and protect customer trust by building an intelligent identity layer that can respond to increasingly sophisticated financial crime.
2:15 pm
PANEL: THE AI ADVANTAGE
How to Build Competitive Advantage When Everyone Has Access to AI
As AI models become widely available, access to the technology will not be enough to differentiate financial institutions. Advantage will come from how you combine AI with proprietary data, customer relationships, and financial expertise. Determine how to:
- Identify where AI can create differentiated products, customer experiences, and financial decisions rather than simply reduce costs.
- Combine proprietary customer and transaction data with AI to build capabilities that competitors cannot easily replicate.
- Turn successful AI capabilities into scalable advantages across personalization, advice, pricing, product development, and customer engagement.
Accelerate growth and strengthen competitive advantage by building AI capabilities around the data, expertise, and customer relationships unique to your institution.
2:15 pm
PANEL: THE DATA BEHIND THE DEFENCE
How to Build a Connected Intelligence Layer for Financial Crime
Fraud, scams, and financial crime increasingly cross the boundaries between channels, products, and traditional risk teams. Financial institutions need to connect fragmented signals fast enough to see threats that individual systems can miss. Build a more connected defence to:
- Unite transaction, customer, identity, behavioural, cyber, and AML data to create a more complete view of suspicious activity.
- Apply real-time analytics and intelligent detection to identify patterns, relationships, and emerging threats across previously disconnected signals.
- Give fraud teams, AML investigators, and decisioning systems access to shared intelligence so they can investigate and intervene faster.
Reduce fraud losses, accelerate investigations, and strengthen financial-crime compliance by turning fragmented risk signals into connected intelligence.
2:45 pm
EXHIBITOR LOUNGE: ATTEND VENDOR DEMOS & CONSULT INDUSTRY EXPERTS
- Enjoy exclusive sponsor demos and experience the next level of data analytics for financial services innovation firsthand.
- Meet one-on-one with leading solution providers to discuss organizational hurdles.
- Brainstorm solutions and gain new perspectives and ideas.
3:00 pm
CASE STUDY: HUMAN IN THE LOOP — OR HUMAN IN THE WAY?
How to Redesign Financial Services Decisions for the AI Era
AI is increasingly capable of evaluating information, recommending actions, and executing routine decisions — but simply inserting AI into existing processes rarely delivers transformational value. Financial institutions need to redesign workflows around what machines can automate and where human judgement genuinely improves the outcome. Explore how to:
- Deconstruct complex financial services workflows into decisions that can be automated, augmented, or reserved for human judgement based on complexity, consequence, and exception.
- Engineer dynamic human-AI handoffs that allow routine decisions to flow automatically while intelligently escalating ambiguity, exceptions, and higher-risk scenarios.
- Measure whether human intervention is improving the outcome — or simply adding latency, cost, and duplicated effort — and continuously recalibrate the level of autonomy as AI capabilities improve.
Increase productivity, decision speed, and service quality by concentrating human expertise where judgement creates the greatest value.
3:30 pm
CLOSING EXECUTIVE PANEL: THE FINANCIAL INSTITUTION OF 2030
What Will Separate the Leaders from the Rest?
As data, AI, and automation become increasingly accessible; technology alone will not determine which financial institutions lead the next decade. Competitive advantage will come from how effectively institutions combine intelligence, customer relationships, talent, technology, and trust to create organizations capable of continuously adapting. Look ahead to:
- Define the capabilities that will differentiate leading financial institutions from intelligent decision-making and hyper-personalized experiences to automated operations and new products and services.
- Explore how business models, operating structures, and the workforce will evolve as AI becomes embedded across customer, risk, and operational decisions.
- Determine where financial institutions should place their biggest bets today to build capabilities that remain differentiated as technology becomes increasingly commoditized.
Build lasting competitive advantage by turning data, AI, and human expertise into an institution capable of continuously adapting, innovating, and outperforming.
4:00 pm
CLOSING COMMENTS FROM YOUR HOST
Review the key solutions and takeaways from the conference. Source a summary of action points to implement in your work.
4:15 pm