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Industry: Financial Services

Agile, Precise and Profitable in the 2026 K-Shaped Economy

One Portfolio, Two Economies

One Portfolio, Two Economies: Model Drift, Consumer Divergence, and the Case for Decision Intelligence

How Financial Institutions Can Stay Agile, Precise, and Profitable in the 2026 K-Shaped Economy

Executive Summary 
  • Model drift is no longer a theoretical risk. In a K-shaped economy, the assumptions baked into your AI and ML models are often eroding in real time, often invisibly. 
  • The speed-to-change gap is getting wider. Institutions that can detect a shift and act on it in days rather than months have a competitive advantage 
  • Advanced decisioning orchestration — the ability to connect data, models, and strategy across your existing environment without rip-and-replace — is the defining infrastructure decision of this cycle 
Introduction

The economic ground is shifting beneath financial institutions in ways that defy conventional risk models. Interest rate trajectories remain unpredictable. Consumer vulnerability is rising. And perhaps most challenging of all, the divergence in financial outcomes across customer segments has created a market where a single strategy can no longer serve a diverse portfolio.

This is the reality of the K-shaped economy, and it demands a fundamentally different approach to risk management and decisioning.

This paper explores the dynamics shaping the 2026 financial services landscape, the unique pressures they create for institutions of every size, and how Decision Intelligence platforms give forward-thinking organizations the speed, precision, and adaptability to turn volatility into competitive advantage.

ADDITIONAL RESOURCES

Agile, Precise and Profitable in the 2026 K-Shaped Economy
eBook ::

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Buy the Engine. Build the Advantage

Buy the Engine. Build the Advantage.

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Buy the Engine.
Build the Advantage.

christian-ball

Christian Ball

Enterprise Account Executive

Why the smartest capital allocation decision in financial services risk infrastructure isn’t build vs. buy, it’s knowing what’s actually worth building. 

The competitive environment in financial services has fundamentally changed. Margins are compressed. Regulatory complexity is accelerating. Customer acquisition costs are at historic highs. And the fintechs gaining ground aren’t necessarily the ones with the most sophisticated technology, they’re the ones deploying it fastest. 

That context matters when you’re evaluating whether to build proprietary risk decisioning infrastructure from scratch. 

The Real Cost of Building

The true cost of building a decisioning platform compounds over time. 

The upfront capex is significant: architecture design, engineering resources, data integration across bureau and alternative data providers, security infrastructure, compliance frameworks. Organisations that have gone through this report 18 to 36 months before a production-ready system is operational. In a market where a competitor can launch a new credit product in weeks, that gap carries direct revenue implications. 

The ongoing opex picture is frequently underestimated at approval stage. Maintaining data integrations as providers update APIs. Rebuilding model deployment pipelines as cloud infrastructure evolves. Keeping pace with regulatory change across markets. Resourcing the support function so the decisioning engine doesn’t become a bottleneck to every product iteration. These aren’t exceptional costs. They’re structural, recurring, and they scale with complexity. 

McKinsey research consistently shows that large-scale internal technology builds in financial services exceed budget in many cases, with five-year total cost of ownership frequently running 40–60% above initial projections. The resource drag on engineering teams is harder to quantify but equally real. Senior talent allocated to infrastructure maintenance is senior talent not working on competitive differentiation. 

Speed is Now a Strategic Variable

Digital-native lenders are entering established segments with lower cost bases and faster decisioning cycles. Embedded finance is putting credit products inside customer journeys that traditional institutions don’t own. Open banking and alternative data are changing what good underwriting looks like. Regulators are demanding more explainability and auditability. 

The organisations gaining ground can test, launch, and iterate on new products in weeks, not quarters. That agility is very difficult to sustain when the decisioning infrastructure itself requires lengthy development cycles every time the business wants to change something. 

What Provenir Changes in the Capital Equation

Provenir’s Decision Intelligence Platform is built for exactly this trade-off. The infrastructure is already built, maintained, and continuously updated: cloud-native deployment, a marketplace of integrated data providers, model management, compliance and auditability frameworks. What organisations configure on top of it is entirely their own. 

Rather than funding a multi-year infrastructure build, capital goes into configuration, integration, and the proprietary decisioning logic that actually differentiates the business. Time to production is measured in weeks, not years. 

The opex shift is equally significant. Data provider integrations, infrastructure scaling, security patching, regulatory update cycles all move from internal cost centres to the platform’s responsibility. Engineering resource shifts from maintaining infrastructure to building product. The ongoing cost base is predictable, subscription-based, and scales with usage rather than requiring constant reinvestment just to stand still. 

BBVA, Atom Bank, and SoFi each deployed Provenir to run fundamentally different business models: global commercial lending, retail digital banking, consumer refinancing, at different scales and in different regulatory environments. The underlying platform is common. The decisioning logic, risk models, and customer strategies are not. 

The IP Question

The executive concern about IP is legitimate and worth addressing directly. Competitive advantage in financial services credit sits in the credit policy, the data strategy, the risk appetite calibration, and the customer relationships built on top of the engine. On Provenir’s platform, all of that remains entirely proprietary. Scoring models are deployed inside the platform, not exposed. Decision logic is configured by your team to reflect your underwriting philosophy. Two organisations on the same infrastructure share no more of their competitive advantage than two companies hosting on AWS share their code. 

What Provenir removes is the infrastructure layer: the part that costs the most, delivers the least competitive differentiation, and consumes the most ongoing resource to maintain. 

There’s also value that’s difficult to replicate internally. The R&D investment across Provenir’s global client base creates platform capabilities that no single organisation, building in isolation, could justify on its own. 

The Bottom Line

The build option carries significant upfront commitment, multi-year timelines, and a structural opex burden that compounds over time. In a market where speed and adaptability are increasingly decisive, it also means slower product iteration and delayed competitive response. 

Provenir reframes the question from build vs. buy to where you deploy your capital and your talent. The platform provides the infrastructure. Your team builds the advantage. Your IP, your models, your risk strategy are fully proprietary, executing faster and at materially lower total cost than the build alternative. 

That’s a strategic decision, not just a procurement one. 

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Event WFIS

WFIS Indonesia 2025

Event

WFIS Indonesia 2025

The Premier Financial Services Innovation Event

  • November 25–26, 2025
  • Booth P13

Provenir is proud to be a Gold Sponsor at WFIS Indonesia 2025 – The Premier Financial Services Innovation Event 

The two-day event will unite C-suite leaders, VPs, Directors, and decision-makers from over 200 banks, insurers, and fintechs across Indonesia. Together, they’ll explore how data, AI, and intelligent decisioning are reshaping the region’s financial ecosystem. 

Discover Intelligent Decisioning @ Booth P13 

Join us at Booth P13 on November 25–26, 2025, to experience how Provenir enables intelligent, data-driven decisions for financial services providers. 

As a global leader in AI decisioning, Provenir empowers organizations to automate, predict, and personalize every customer interaction – driving growth and trust across the financial lifecycle. 

Why Meet Us at WFIS Indonesia 2025? 

  • Smarter Risk Decisions – Automated in Real Time – Manage losses and approve more good customers with adaptive, AI-driven decisioning that learns continuously from data.
  • Predict Customer Needs with Behavioural Insights – Leverage contextual and behavioural data to anticipate customer intent and deliver proactive, relevant offers.
  • Hyper-Personalize Customer Experiences – Use AI-powered decisioning to personalize onboarding, engagement, and servicing at every touchpoint – driving loyalty and lifetime value.
  • End-to-End Financial Decisioning Solutions – Credit Risk Onboarding: Fast, accurate approvals with intelligent automation
    Application Fraud & Compliance: Detect, prevent, and stay compliant in real time
    Customer Management & Hyper-Personalization: Understand, engage, and retain with data-driven intelligence
    Collections Optimization: Recover smarter, faster, and more empathetically
  • Scalable, Cloud-Native Platform – Accelerate innovation with a configurable, low-code environment that scales effortlessly with your business.

Join our Session at 9.25 am | Day 2 – 26th Nov

Balancing Innovation and Trust: How AI Decisioning is Redefining Risk, Inclusion, and Customer Experience

  • How Provenir helps financial institutions embrace AI innovation responsibly by balancing automation, transparency, and compliance
  • Exploring how real-time decision intelligence detects social engineering and safeguards digital trust across customer interactions
  • Using Provenir’s AI and data marketplace to promote financial inclusiveness and expand access to underserved customer segments
  • Delivering hyper-personalized financial experiences that remain compliant, secure, and customer-centric
  • Uncovering how GenAI and agentic AI are shaping the next generation of intelligent, ethical, and inclusive financial ecosystems
Register your interest here

Speaker:

Wana Sedayu

Wana Sedayu

Senior Presales Consultant, APAC – Provenir

Wana is a Senior Presales Consultant at Provenir, supporting clients across the APAC region in driving digital transformation within the financial services sector. With over 15 years of experience in the industry, Wana brings deep expertise in loan origination, core leasing, credit decisioning, and customer management solutions.

Beginning his career as a software developer, Wana later transitioned into business consulting before dedicating the past decade to presales and value engineering roles. He has worked with prominent institutions such as Citibank, SMBC Indonesia, Bank Danamon, Bank of America, the Indonesia Stock Exchange, and the Ministry of Finance, contributing to numerous high-impact technology initiatives. OnlinePajak as Senior Manager Presales, and Fujitsu Indonesia as Presales Manager.

Combining his technical foundation with a strong business perspective, Wana is passionate about helping financial institutions accelerate innovation, optimize their decisioning processes, and achieve measurable business outcomes through data-driven solutions.

Why Provenir:

At Provenir, we help financial institutions automate smarter risk decisions, use behavioral insights to drive growth, and personalize every interaction with contextual intelligence all from a single, unified platform. 

Let’s Connect:

Meet our team at Raffles Jakarta to discover how Provenir’s AI Decisioning Platform can help your organization accelerate approvals, prevent fraud, and deliver personalized customer experiences that build trust and profitability. 

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Navigating the Promise and Peril of Generative AI in Financial Services

Navigating the Promise and Peril of Generative AI in Financial Services

Financial services leaders are being bombarded with AI pitches. Every vendor claims their solution will revolutionise decisioning, slash costs, and unlock untapped revenue. Meanwhile, your competitors are announcing AI initiatives, your board is asking questions, and your teams are already experimenting with ChatGPT and other tools—sometimes without your knowledge.

The pressure to “do something” with AI is intense. But the organisations that rush to deploy generative AI without understanding its limitations are setting themselves up for problems that may not become apparent until it’s too late.

At Provenir, we’ve built AI decisioning capabilities that process over 4 billion decisions annually for financial institutions in 60+ countries. We’ve seen what works, what doesn’t, and what keeps risk leaders up at night. More importantly, we’ve watched organisations make costly mistakes as they navigate AI adoption.

In this article you’ll find a practical assessment of where generative AI delivers real value in financial services, where it introduces unacceptable risk, and how to tell the difference.

Where AI Delivers Value

The efficiency benefits of AI in financial services are tangible and significant. Here’s where we’ve seen AI deliver measurable business impact:
  • Faster model development and market response:
    What once took months in model evaluation and data assessment can now happen in weeks, enabling lenders to respond to market changes and test new data sources with unprecedented speed.
  • Transaction data transformed into intelligence:
    Advanced machine learning processes enormous volumes of transaction data to generate personalised consumer insights and recommendations at scale—turning raw data into revenue opportunities.
  • Operational oversight streamlined:
    Generative AI helps business leaders cut through the noise by querying and summarising vast amounts of real-time operational data. Instead of manually reviewing dashboards and reports, leaders can quickly identify where to focus their attention—surfacing which workflows need intervention, which segments are underperforming, and where action is most likely to drive business value.
These aren’t future possibilities. Financial institutions are achieving these outcomes today: 95% automation rates in application processing, 135% increases in fraud detection, 25% faster underwriting cycles. While GenAI-powered assistants accelerate model building and rapidly surface strategic insights from complex decision data.

The Risks Nobody Talks About

However, our work with financial institutions has also revealed emerging risks that deserve serious consideration:
When AI-Generated Code Contradicts Itself

Perhaps the most concerning trend we’re observing is the use of large language models to generate business-critical code in isolation. When teams prompt an LLM to build decisioning logic without full knowledge of the existing decision landscape, they risk creating contradictory rules that undermine established risk strategies.

We’ve seen this play out: one business unit uses an LLM to create fraud rules that inadvertently conflict with credit policies developed by another team. The result? Approved customers getting blocked, or worse—high-risk applicants slipping through because competing logic created gaps in coverage. In regulated environments where consistency and auditability are paramount, this fragmentation poses significant operational and compliance risks.

When Confidence Masks Inaccuracy

LLMs are known to “hallucinate”—generating confident-sounding but factually incorrect responses. In financial services, where precision matters and mistakes can be costly, even occasional hallucinations represent an unacceptable risk. A single flawed credit decision or fraud rule based on hallucinated logic could cascade into significant losses.

This problem intensifies when you consider data integrity and security concerns. LLMs trained on broad, uncontrolled datasets risk inheriting biases, errors, or even malicious code. In an era of sophisticated fraud and state-sponsored cyber threats, the attack surface expands dramatically when organisations feed sensitive data into third-party AI systems or deploy AI-generated code without rigorous validation.

The Expertise Erosion

A more insidious risk is the gradual erosion of technical expertise within organisations that become overly dependent on AI-generated solutions. When teams stop developing deep domain knowledge and critical thinking skills—assuming AI will always have the answer—organisations become vulnerable in ways that may only become apparent during crisis moments when human judgment is most needed.

Combine this with LLMs that are only as good as the prompts they receive, and you have a compounding problem. When users lack deep understanding of what they’re truly asking—or worse, ask the wrong question entirely—even sophisticated AI will provide flawed guidance. This “garbage in, garbage out” problem is amplified when AI-generated recommendations inform high-stakes decisions around credit risk or fraud prevention.

Regulators Are Watching

The regulatory environment is evolving rapidly to address AI risks. The EU AI Act, upcoming guidance from financial regulators, and increasing scrutiny around algorithmic bias all point toward a future where AI deployment without proper governance carries substantial penalties. Beyond fines, reputational damage from AI-driven failures could be existential for financial institutions built on customer trust.

What Successful Institutions Are Doing Differently

Based on our work with financial institutions globally, the organisations getting AI right start with a fundamental recognition: AI is already being used across their organisation, whether they know it or not. Employees are experimenting with ChatGPT, using LLMs to generate code, and making AI-assisted decisions—often without formal approval or oversight. The successful institutions don’t pretend this isn’t happening. Instead, they establish clear AI governance frameworks, roll out comprehensive training programs, and implement mechanisms to monitor adherence. Without this governance layer, you’re operating blind to the AI risks already present in your organisation.

With governance established, these organisations focus on maintaining human oversight at critical decision points. AI augments rather than replaces human expertise. Business users configure decision strategies with intuitive tools, but data scientists maintain oversight of model development and deployment. This isn’t about slowing down innovation—it’s about ensuring AI recommendations get validated by people who understand the broader context.

Equally important, they refuse to accept black boxes. In regulated industries, explainability isn’t negotiable. Every decision needs to be traceable and understandable. This isn’t just about compliance—it’s about maintaining the ability to debug, optimize, and continuously improve decision strategies. When something goes wrong (and it will), you need to understand why.

Rather than accumulating point solutions, successful institutions build on unified architecture. They recognise that allowing fragmented, AI-generated code to proliferate creates more problems than it solves. Instead, they use platforms that provide consistent decision orchestration across the customer lifecycle. Whether handling onboarding, fraud detection, customer management, or collections, the architecture ensures that AI enhancements strengthen rather than undermine overall decision coherence.

These organisations also treat AI as a living system requiring continuous attention. AI models need ongoing observability and retraining. Continuous performance monitoring helps identify when models need refinement and surfaces optimisation opportunities before they impact business outcomes. The institutions that treat AI deployment as “set it and forget it” are the ones that end up with the costliest surprises.

Finally, they maintain control of their data. Rather than sending sensitive data to third-party LLMs, forward-thinking organisations deploy AI solutions within secure environments. This reduces both security risks and regulatory exposure while maintaining full control over proprietary information.

Why Inaction Isn’t an Option

The irony is that many leaders debating whether to “adopt AI” have already lost control of that decision. AI is already being used in their organisations—the only question is whether it’s governed or ungoverned, sanctioned or shadow IT.

Meanwhile, fintech disruptors are leveraging AI to deliver frictionless, personalised experiences that traditional institutions must match. The competitive gap isn’t just about technology—it’s about the ability to move quickly while maintaining control and compliance.

Organisations that succeed will be those that combine AI capabilities with strong governance frameworks, architectural discipline, and deep domain expertise. They’ll move beyond isolated experiments to implement AI in ways that deliver real business value while maintaining the trust and regulatory compliance that financial services demand.

The institutions making smart bets on AI aren’t the ones moving fastest—they’re the ones moving most thoughtfully, with equal attention to capability, transparency and governance.

Find out more about Provenir AI

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ProvenirNEXT London: Skyline Networking

  • provenir next

    Logo-ProvenirNEXT-Brandmark-REV

    Provenir Next
  • newday-WHT

    NewDay

London: Skyline Networking

Join us for an evening of connection, cocktails, and conversation among banking professionals

Provenir invites you to an exclusive networking evening — set against the stunning skyline backdrop of The Menier Penthouse. This is not your typical business event — no panels, no presentations, just great company and engaging conversation in a relaxed and elegant environment.
What’s in Store
  • Opening Insights: Rethinking “Build vs Buy”

    Kick off the evening with brief insights from our partner NewDay, who will share their unique “Buy to Build” approach. This short welcome will set the stage for thought-provoking discussions that challenge traditional assumptions and spark fresh perspectives on technology strategy.
  • Cocktail Masterclass

    Enjoy an interactive cocktail-making session led by an expert mixologist. Whether you prefer a classic or something more inventive, you’ll have the chance to craft your own drinks while learning new skills.
  • Meaningful Networking

    Connect with senior financial services professionals and thought leaders from across banking, fintech, credit and risk. Share insights, exchange ideas, and make valuable connections in a relaxed, informal atmosphere designed for authentic dialogue.
Who Should Attend
Senior professionals and thought leaders from:
  • Banking
  • Fintech
  • Credit
  • Risk Management
Why ProvenirNEXT London?
  • Networking with purpose:
    We’ve partnered with NewDay to create an evening that goes beyond typical networking, introducing fresh perspectives on strategic technology decisions
  • Challenge conventional thinking:
    Engage with new approaches to the “Build vs Buy” conversation through real-world insights and peer discussions
  • Learn while you network:
    Master new cocktail-making skills with expert guidance while building professional relationships
  • Quality connections:
    Connect with senior decision-makers and industry leaders in a relaxed, elegant environment designed for authentic networking

Ready for networking with a difference?

Secure your spot at London’s most sophisticated professional gathering.

Limited spaces available

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Enabling Responsible Growth and Customer Trust in Malaysia’s Digital Lending Landscape through Data-Driven Insights

ProvenirNext Roundtable

Enabling Responsible Growth and Customer Trust in Malaysia’s Digital Lending Landscape through Data-Driven Insights

Bringing together visionary minds from the financial sector to spark dialogue and innovation

  • 06th Aug 2025
  • 4:30 PM – 7:30 PM MYT
  • Sofitel Kuala Lumpur Damansara | Malaysia

As digital transformation accelerates across Southeast Asia, Malaysia stands at a pivotal point driven by innovation, increasing regulatory expectations, and evolving customer demands.

This executive roundtable will convene thought leaders from banks, fintechs, digital lenders, and regulators to explore how financial institutions can meet growing expectations for responsible lending, deliver exceptional digital experiences, and build enduring customer trust.

We’ll dive into how intelligent decisioning, low-code orchestration, and real-time data are transforming onboarding and credit decisioning, empowering institutions to drive sustainable growth, reduce risk exposure, and enhance the overall customer lifecycle—from acquisition to long-term retention.

We’re also hosting a special fireside chat featuring Kavines Karthigasan, Head of APAC, Provenir and Shawn Loh, Director, LifeTech Group. They’ll dive into how data security, collaboration, and customer experience intersect to drive trust at scale in modern finance.

Discussion Highlights

  • Responsible Lending in a Regulated Landscape How Malaysian lenders can align with BNM’s expectations using real-time affordability insights and intelligent decisioning.
  • From Acquisition to Customer Lifetime ValueStrategies to foster long-term loyalty and profitability through lifecycle decisioning.
  • Trust Through TransparencyUsing consent-driven data and explainable decisioning to enhance digital trust.
  • Frictionless Digital Journeys – Delivering seamless onboarding and lending experiences with low-code, intelligent orchestration.
  • Malaysia’s Financial Outlook – Navigating fraud risks, credit growth, and rising consumer expectations in a dynamic digital lending environment.
Why Attend?
  • Learn from local and regional success stories

  • Engage in off-the-record dialogue with industry peers
  • Grow your professional network over a curated three-course meal
  • Walk away with fresh insights to drive trust and customer growth

Who Should Attend?

This session is curated for senior executives and decision-makers across:

  • Retail & Digital Banking
  • Risk, Fraud & Compliance
  • Customer Experience & Product Strategy
  • Data Science & Decisioning
  • Fintech, BNPL & Lending Platforms

ProvenirNEXT

Register your interest here

  • Kavinesswaran Karthigasan

    Head of APAC, Provenir

    Kavines is the Principal Consultant driving business-value propositions for Provenir across the APAC Region. With a decade of experience in credit risk management solutions in the financial services sector, Kavines has worked with major banks and lenders in Southeast Asia, assisting them in optimising their business processes, automating their workflows, and complying with regulatory standards through the use of risk and decision management applications. Prior to joining Provenir, he spent nearly a decade as a key member of Experian’s Southeast Asia Decision Analytics group. Throughout his career, he has held a variety of positions, beginning as an implementation analyst, progressing to consultant, then pre-sales consultant, and finally customer success manager for the Southeast Asia region. He was born in Malaysia and graduated from Monash Australia. Kavines’ aim is to help his clients achieve customer-level consistency, digital transformation, and data-driven decision making across their products and channels.

  • Shawn Loh

    Director of Business Development, LifeTech Group

    Shawn leads the business division at LifeTech Group, a leading provider of Managed Security Services delivering next generation AI-Powered Security Operations Centre (SOC) solutions and global cybersecurity services. With years of expertise in cybersecurity and fintech, Shawn plays an instrumental role in supporting national critical industries – such as financial, healthcare, utilities and manufacturing – enhance their digital resilience, adopt proactive security operations, and strengthen their brand reputation. His mission is to ensure that organizations are safeguarded with precision and agility, so that they can focus on what matters most – growing their business.

The Provenir Thought Leadership Roundtable Series brings together industry visionaries, C-level executives, and thought leaders for insightful discussions on redefining risk decisioning strategies. The series fosters a collaborative environment for sharing forward-thinking perspectives, exploring innovative approaches, and shaping the future of fraud prevention in an era of rapid technological evolution and increasing digital risk.

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Roundtable: Managing and Mitigating the Growing Debt Bubble

Provenir Next

Roundtable: Managing and Mitigating the
Growing Debt Bubble

great northern hotel

  • 19th November, 2025
  • 11:45 AM – 3:00 PM
  • Great Northern Hotel
    Pancras Rd, London N1C 4TB – England
As the global debt landscape grows increasingly complex, organisations face the challenge of balancing effective debt management with exceptional customer experience. This exclusive roundtable will focus on strategies for managing and mitigating the growing debt bubble, with a particular emphasis on delivering a Gen Z-centric customer experience and achieving the delicate balance of improving customer satisfaction while reducing operational costs. Participants will gain insights into innovative approaches to debt recovery, cost optimisation, and customer engagement.

Key Discussion Points:

  • Managing and Mitigating the Growing Debt Bubble:
    Addressing the challenges of rising debt levels and their impact on businesses.
  • Delivering a Gen Z Customer Experience:
    Meeting the expectations of a generation that values speed, convenience, and personalisation.
  • Achieving the Seemingly Impossible:
    Strategies for enhancing customer experience while simultaneously reducing operational costs.
Format:
  • 11:45 AM – Arrival and welcome drink

  • 12:00 PM – Keynote
  • 12:30 PM – Roundtable discussion and three-course lunch
  • 3:00 PM – Official close and summary

ProvenirNEXT

Register your interest here

Frédéric Dubout

SPEAKER

details…
About the Provenir Thought Leadership Roundtable Series
The Provenir Thought Leadership Roundtable Series brings together industry visionaries, C-level executives, and thought leaders for insightful discussions on redefining risk decisioning strategies. The series fosters a collaborative environment for sharing forward-thinking perspectives, exploring innovative approaches, and shaping the future of fraud prevention in an era of rapid technological evolution and increasing digital risk.

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Australia

Enhancing Customer Lifetime Value and Trust in Australia’s Financial Future

Roundtable & Cocktail Hour

Enhancing Customer Lifetime Value and Trust in Australia’s Financial Future

An Evening to Celebrate, Support, and Give Back

  • 3rd July 2025
  • 4:00 PM – 6:30 PM AEST
  • Park Hyatt Sydney | Sydney, Australia
Join the Conversation That’s Shaping the Future of Financial Services

In a time of accelerated digital transformation and growing regulatory expectations, how can financial institutions in Australia build lasting customer relationships while remaining agile and compliant?

Join an exclusive group of senior leaders from banks, fintechs, and neobanks for an intimate Roundtable & Cocktail Hour – a unique evening of insight-driven discussion and high-value networking.

This event will explore how data-driven decisioning, responsible lending practices, and frictionless digital journeys are redefining customer trust and lifetime value in Australia’s financial landscape.

Discussion Highlights

  • Responsible Lending and Regulatory Alignment

    ASIC continues to stress responsible lending practices and the importance of affordability checks, especially following scrutiny of digital lenders and BNPL operators.
  • Customer Lifetime Value through Intelligent Decisioning

    Banks and neobanks in Australia are shifting from transactional engagement to lifecycle value management — targeting customer stickiness and profitability.
  • Data-Driven Trust and Transparency

    With Open Banking (CDR) rollout, consumers demand more transparency, control, and personalised services.
  • Seamless Digital Experiences

    Consumer expectations for fast, intuitive digital lending journeys are rising, especially among Gen Z and millennial segments.
  • Safeguarding Customer Journeys with Intelligent Risk Controls

    Fraud Mitigation as a Trust EnablerIncreasing fraud threats in digital lending and onboarding are eroding customer trust and inflating credit costs.
Why Attend?
  • Gain actionable insights from industry peers
  • Contribute to candid, off-the-record discussions
  • Connect with industry peers over thoughtfully curated drinks and dining
  • Leave inspired with new ideas to drive customer growth and trust
Who Should Attend?
This event is designed for senior executives and decision-makers in:
  • Retail & Digital Banking
  • Risk, Fraud & Compliance
  • Customer Experience & Product Innovation
  • Data Science & Decisioning
  • Fintech & Lending Platforms

ProvenirNEXT

Limited Seats. High Impact.

This is an invite-only experience to ensure meaningful dialogue among peers.

Register your interest now to secure your seat.

Kavinesswaran Karthigasan

Kavinesswaran Karthigasan

Kavines is the Principal Consultant driving business-value propositions for Provenir across the APAC Region. With a decade of experience in credit risk management solutions in the financial services sector, Kavines has worked with major banks and lenders in Southeast Asia, assisting them in optimising their business processes, automating their workflows, and complying with regulatory standards through the use of risk and decision management applications. Prior to joining Provenir, he spent nearly a decade as a key member of Experian’s Southeast Asia Decision Analytics group. Throughout his career, he has held a variety of positions, beginning as an implementation analyst, progressing to consultant, then pre-sales consultant, and finally customer success manager for the Southeast Asia region. He was born in Malaysia and graduated from Monash Australia. Kavines’ aim is to help his clients achieve customer-level consistency, digital transformation, and data-driven decision making across their products and channels.

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Top 5 Trends Financial Institutions Need to Navigate in 2025

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Blog: Election Economics

Election Economics: How to Navigate Risk Decisioning in an Uncertain Political Landscape

How Political Outcomes Shape the Future of Lending and Financial Services
Elections are pivotal moments that shape the direction of the economy, often driving shifts that reverberate across industries, including financial services. The outcomes of national and regional elections will directly influence fiscal strategies, regulatory frameworks, and economic policies, which then impact interest rates, inflation, the employment landscape, and overall market stability. And of course, all of these factors are critically important to the world of financial services, where things like credit decisioning, fraud threats, risk management, and lending practices all depend quite heavily on the broader economic environment. Recent elections in the UK and Argentina have already demonstrated how shifts in political leadership drive significant economic policy changes, and of course, the highly contentious upcoming Presidential election in the US looms as a tipping point that will have influence across the globe. As these political events unfold, financial services providers need to remain agile, proactively adjusting to new realities to ensure stability (and profitability) amidst change.
Recent Elections and Economic Impact on Lending and Financial Services

Recent elections around the world have already triggered significant economic shifts, with far-reaching implications. In the UK General Elections in 2024, results have further shaped the ongoing Brexit process, influencing fiscal policies and regulatory frameworks that directly impact the financial industry. Uncertainty surrounding post-Brexit trade deals and regulatory realignment has already affected interest rates and inflation, creating tighter credit conditions for both consumers and businesses. And adjustments to the Bank of England’s interest rate policies or regulations governing financial institutions could further influence lending practices, with tighter borrowing conditions on the horizon for both individuals and small businesses.

In Argentina’s 2023 Presidential Election, a shift in leadership has brought about changes in economic strategy, particularly in the battle against soaring inflation. The new government’s attempts to control inflation and stabilize the economy are affecting the country’s monetary policy, leading to higher interest rates and tighter lending criteria. For financial institutions, this poses significant challenges, requiring lenders to quickly adjust their credit decisioning processes to accommodate economic instability. As inflation persists and the cost of borrowing rises, both consumer credit and business financing have become more difficult to secure, which further strains the economy.

The India General Elections earlier this year have also had effects on the fintech space. The results will influence regulatory policies surrounding fintech growth and digital finance, both of which are necessary for encouraging financial inclusion in underserved markets. Depending on the government’s support for these sectors, lending to traditionally underserved segments of the population could see either significant growth or stagnation. And changes in policy around digital finance could encourage new forms of lending, but they could also introduce more stringent regulations that will make access to credit much more challenging.

The 2024 US Presidential Election: A Global Ripple Effect

Of course top of mind these days, regardless of your location, is the upcoming US Presidential election. While it’s always something that has far-reaching effects, this year’s highly contentious ballot is poised to have sweeping global implications, on everything from global interest rates and inflation trends, to significant policy reforms on taxation, regulation, and lending practices. A key player in this process is the Federal Reserve, which closely monitors election outcomes and adjusts interest rates accordingly. If the newly-elected government pushes for changes in fiscal measures, the Federal Reserve’s response could shape borrowing costs, which in turn improves or challenges access to credit. For lenders and financial services providers, these shifts showcase how important it is to remain agile in the face of uncertain regulatory reforms and fluctuating market conditions. The global financial system will be watching closely as the election unfolds – because no matter who wins, there is bound to be significant changes that will reshape lending dynamics in the US and beyond.

Election-Driven Economic Currents: Navigating Interest Rates, Inflation, and Risk Decisioning

Election outcomes can cause shifts in all sectors of the economy, but some areas in particular directly impact lending and risk decisioning. One of the most immediate effects is on interest rates, which are often adjusted based on fiscal policies introduced post-election. As interest rates fluctuate, lenders have to reassess risk profiles and adjust their credit and risk decisioning processes to account for any potential volatility in repayment abilities of their customers. Inflation control is also directly linked to post-election economic strategies. Any policies that either stimulate or dampen the economy can lead to varying levels of inflation – which affects everything from consumer purchasing power and household debt to business investments and the stock market. Inflation can also erode creditworthiness, with rising prices and an increased cost of living making it harder for both individuals and companies to manage their debt obligations. This means that lenders are then faced with the challenge of adjusting lending practices to maintain profitability while managing increasing risks in their customer base (which requires systems and solutions that enable flexibility in decisioning processes).

The outcome of any election also influences overall creditworthiness as economic conditions shift in response. Changes in the employment rate, business investments, interest rates, and fiscal stability all contribute to changes in credit and risk profiles. This is where a more dynamic approach to risk assessment is critical, with the ability to leverage intelligent, proactive risk decisioning solutions. Using advanced decisioning technology and data analytics allows financial services providers to adapt easily, identifying risks earlier and making more informed decisions. This proactive approach enables lenders to protect their profitability and lending portfolios while still serving the needs of customers effectively.

Ahead of the Curve: How Advanced Risk Decisioning Solutions Mitigate Volatility

With elections comes uncertainty. And when there’s uncertainty, financial services providers need to proactively navigate shifting risk. Advanced risk decisioning solutions play a key role in helping you better predict (and respond to) risk, by leveraging real-time data and AI-driven analytics to identify emerging trends earlier and make smarter, faster risk decisions. Rather than simply reacting to sudden market fluctuations, proactive decisioning allows you to better predict future scenarios, preparing for possible fluctuations in interest rates, inflation, credit conditions, ability to repay, etc. Remaining agile and competitive is key to staying ahead of any uncertainty in the economy – election-driven or otherwise.

Holistic risk decisioning solutions also ensure a smoother onboarding process, with the ability to more accurately assess creditworthiness, even among rapidly changing market conditions. AI-powered decisioning software and solutions allows you to access and integrate vast amounts of data (everything from economic indicators and market trends to individual financial behavior), giving you a more accurate (and nuanced) view of a customer’s unique risk profile. Too often when economic conditions are volatile, the inclination is to be overly cautious. But that can stifle your business growth. With more proactive, agile decisioning, your lending portfolio remains stable (and profitable) even when external conditions aren’t.

Fraud prevention also becomes a key focus. During periods of political and economic uncertainty, fraud attempts often surge. With a holistic, data-driven approach to your risk decisioning, advanced algorithms and embedded intelligence can better detect unusual patterns and behaviors that signal fraudulent activity. Integrating fraud detection directly into the risk decisioning process allows you to greatly reduce losses, ensuring your operations remain secure, compliant, and resilient even among the unpredictability of major election upheaval.

Beyond onboarding, there is also the issue of managing ongoing customer relationships and maximizing value across the lifecycle. Ongoing account management is particularly important during periods of economic uncertainty. Advanced risk decisioning solutions empowers you to continuously, proactively monitor customer profiles and make adjustments easily. A flexible solution allows you to adjust credit limits and lending terms in real time as economic factors like inflation, interest rates, and consumer behavior evolve. Using AI-driven tools to track changes in individuals as well as broader market trends allows you to proactively mitigate risk, reducing the likelihood of defaults while maintaining a positive customer experience through personalized, flexible financial products and services.

Despite proactive, agile efforts to effectively manage your risk, post-election downturns are common, leading to increases in default rates and placing added pressure on collections and recovery strategies. Sophisticated (and more productive) collections treatment strategies are made possible with intelligent data and decisioning solutions. Leveraging advanced risk decisioning software allows you to segment delinquent accounts based on risk profiles, prioritize collections efforts, determine the best communications channels, and tailor recovery efforts to individual borrower profiles. Best of all, it allows you to anticipate defaults before they happen by closely analyzing customer behavior and economic trends to forecast likelihood of repayment, enabling you to approach debt recovery proactively and strategically. A more proactive approach not only helps to mitigate losses, but also supports a much more empathetic and effective recovery process, ensuring long-term management of your customer relationships.

Preparing for Election-Driven Economic Shifts in Financial Services

Intelligent risk decisioning solutions are key to staying ahead of post-election shifts. By incorporating AI and advanced data analytics in one holistic platform, these decisioning solutions enable you to:

  • Forecast and proactively mitigate potential risks
  • Make data-driven lending decisions
  • Improve onboarding processes
  • Reduce customer friction
  • Manage customer risks and relationships across the lifecycle
  • Detect and prevent fraud
  • Prioritize collections efforts
  • Adjust lending practices with ease
  • Continuously monitor the economic environment

Financial services providers that adopt forward-looking, proactive strategies (and which are armed with the right technology) will prove more resilient, positioning themselves for sustainable growth even in the face of political and economic change. Are you ready?

Discover how Provenir’s single decisioning platform offers you stability across the customer lifecycle.

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