March 7, 2024

The AI Imperative for Asset Finance

For forward-thinking asset finance companies, generative AI is rapidly shifting from futuristic possibility to strategic imperative. While the disruptive potential of technologies like generative AI and traditional machine learning is undeniable, realising a true competitive edge requires thoughtfully charting the path ahead.

The generative AI wave is already starting to reshape the industry landscape. Early initiatives are streamlining everything from internal agent support to intelligent document generation. Performance gains and cost efficiencies are being unlocked. But these are just the initial ripples.

As a recent McKinsey report emphasises, capturing generative AI's full value means moving well beyond productivity plays and pilots. Leading organisations are setting their sights on larger strategic objectives - identifying high-impact areas where AI can create new revenue streams, outflank competitors, and redefine customer experiences. For them, generative AI is more than just another technology implementation but an opportunity to fundamentally reinvent their business.

The stakes are high for asset finance firms. Those that can successfully initiate, scale and sustain strategic generative AI implementations will seize a pivotal competitive edge. Those that can't risk swift obsolescence in an industry being reshaped by automation and intelligent decisioning.

Uncovering Your AI Opportunities

Embracing an AI-first future starts with pinpointing where AI capabilities can deliver meaningful business outcomes. It's a process of peering beneath surface-level use cases to uncover the deeper seams of value.

For asset finance companies, areas ripe for differentiation might include:

  • Intelligent routing and approval: Incorporating the ability to scan and process messages, e-mails and documents automatically
  • Residual value forecasting: Employing deep learning models to predict asset values with unprecedented granularity by factoring in usage patterns, market conditions, auction site activity and macro-trends.
  • Intelligent risk assessment: Harnessing natural language processing to extract risk signals from unstructured data (briefing notes, market, cashflow and arrears trends, etc.) to enhance credit risk models.
  • Hyper-personalised offerings: Using generative AI to create individually-tailored financing packages, documentation, and targeted customer communications.

The key is to focus innovation on domains that are true competitive battlegrounds. Asset finance leaders must critically examine where AI initiatives can genuinely move the needle on their strategic objectives. For example, increasing deal velocity is valuable and will become a given as automation expands across the market, but leveraging AI to dynamically structure deals and customer experiences that are specifically designed to expand market share could be potentially transformative.

Aligning AI to Your Strengths

Identifying the right opportunities is only half the battle. Extracting the full value from generative AI requires a clear-eyed understanding of your organisation's unique strengths and market position.

Consider an asset finance company that has established a strong competitive moat around its deep knowledge of a particular equipment category. Feeding that proprietary data into a generative AI model could yield uniquely powerful tools for predicting residual values and optimising asset maintenance. The resulting efficiency gains and risk reductions would be difficult for competitors to replicate.

Contrast this with an asset finance company that has cultivated a reputation for exceptional deal customisation and customer service. For them, applying AI to further enhance the tailoring of financing packages and streamline customer interactions could create an even higher bar for competitors to clear.

The key take-away is to not leverage generative AI as an ad hoc technological add-on, but as an amplifier of existing organisational advantages and a catalyst for strategic goals.

Building Organisational Readiness

Aligning generative AI to your strategic objectives is essential, but it's not sufficient. Truly harnessing these technologies requires a foundational level of organisational readiness. Successful AI initiatives hinge on far more than just the underlying models and algorithms. Companies must actively cultivate the right mix of talent, data, and operational capabilities to support and sustain their AI ambitions.

On the talent front, a combination of upskilling existing staff and strategic external hiring is often necessary. Asset finance firms need to build bench strength in areas like prompt engineering, data curation, and AI governance. Importantly, this capability building must extend beyond the data science and IT functions to encompass the business units where AI will be deployed.

Equally critical is putting in place the right data infrastructure and processes. Generative AI models are only as good as the data they are trained on. Organisations must invest in data quality, establish clear data governance frameworks, and architect their data pipelines to support the specific needs of AI applications.

For asset finance companies looking to jumpstart their AI readiness, Finativ's AI Readiness Assessment offers a useful starting point. Our comprehensive evaluation covers everything from your technical infrastructure to your organisational culture, providing a detailed roadmap for AI success.

But readiness is not a one-time box to check. As AI technologies and best practices continue to evolve at a breakneck pace, maintaining competitiveness will require a commitment to continuous learning and adaptation. Asset finance leaders must approach AI readiness not as a destination, but as an ongoing journey.

AI Readiness: Strategic Alignment, Technical Readiness, Organisational Readiness, AI Roadmap

Navigating the Generative AI Frontier

For asset finance companies, the generative AI revolution represents both an immense opportunity and an existential challenge. As these technologies redefine what's possible in areas from risk assessment to customer experience, competitive dynamics are being rewritten in real-time.

Seizing the AI advantage requires a strategic, holistic approach. It means:

  • Identifying the areas where AI can deliver true competitive differentiation
  • Aligning AI initiatives tightly with organisational strengths and objectives
  • Investing in the talent, data, and operational foundations of AI success
  • Committing to continuous learning and adaptation in a rapidly evolving field

The risks of inaction are stark. In an industry increasingly shaped by automation and data-driven decisioning, firms that fail to harness the power of generative AI may quickly find themselves outpaced by more agile, innovative competitors.

But for those who can successfully navigate this new frontier, the rewards are substantial. From step-change improvements in operational efficiency to entirely new business models and revenue streams, generative AI has the power to redefine what it means to be a leader in asset finance.

The generative AI future is already unfolding. The question for asset finance companies is not whether to embrace this transformative technology but how to do so in a way that maximises its competitive potential. With the right strategic approach, the AI frontier is yours to claim.

Simon Potts Finativ

Simon Potts

Simon Potts brings a wealth of expertise and experience to the field of AI and digital transformation.

With over 20 years of experience at IBM Financing, he has been the global lead on AI and digital transformation. Simon is recognised as an accomplished technology leader, holding global roles covering IT strategy and digital transformation.

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