To succeed in today’s digital-first world, banks are under pressure to orchestrate differentiated customer journeys to attract, win, and maintain long-term loyalty. Troves of real-time customer data and advancements in artificial intelligence (AI) technologies are paving the way for delivering hyper-personalized experiences that are both relevant and timely.
However, many banks are struggling to realize ROI from their data and AI investments. Shackled by legacy systems, siloed data, and bogged-down IT teams, digital transformation projects are still failing at an alarming rate.
Some are attempting to address the value leak by narrowly focusing on AI-point solutions tailored to specific fixed use cases. While this may result in limited short-term lift, it only adds to the technical debt across an already strained and sprawling infrastructure. Plus, these bespoke solutions often lack the integrations needed to curate a holistic customer experience across functional silos.
Balance short-term wins with long-term gains
An equally challenging approach to transformation assumes wide-scale modernization across the entire technology stack is necessary. IT teams faced with replacing core banking systems, upgrading outdated data infrastructures, or building full-scale platform solutions from scratch are feeling the pressure.
These daunting multi-year, hundred-million-dollar projects are incredibly risky and the payoff cycle is often too long. They drain already deprived IT resources, and the business is often left limping along in the meantime.
A more flexible approach is needed to unlock quick time to value while simultaneously accelerating transformation roadmaps. The key lies in an intermediate intelligence layer where data-driven decision making is operationalized across the entire enterprise. This layer harnesses a dynamic mix of AI, advanced analytics, and human expertise to transform data into insights and take action at scale – a concept we like to call applied intelligence.
Add a flexible layer for intelligence
Think of it this way. Similar to the tendons and ligaments connecting bones and muscles in our body, an applied intelligence platform binds and strengthens components within your existing technology infrastructure.
This modular, API-first layer augments and transmits intelligence between your digital front-end applications and your back-end servicing systems and data stores. It’s the place where decisions are made and strategies come to life. Where data and AI insights are operationalized. Where actions are taken that drive business outcome.
And it does this all at scale and in real-time through expertly choreographed dataflows and orchestrations. It adds flexibility where it was previously lacking, plying your rigid legacy infrastructure into a nimble participant in a digital-first strategy.
Embrace a platform operating model
Leading companies are already embracing a new way of thinking about their data, their systems, their human capital, and their overall enterprise intelligence.
BCG describes a technology operating model where AI unlocks the ability to make better, faster decisions. In this model, “the bionic company puts a modular technology stack fueled by data at the heart of the new organization.”
McKinsey describes an AI-bank of the future where a decisioning layer sits between the bank’s engagement and core technology layers. Working in unison, these layers “provide customers with distinctive omnichannel experiences, support at-scale personalization, and drive the rapid innovation cycles critical to remain competitive in today’s world.”
In both approaches, AI-powered decision-making capabilities are integrated holistically within a platform operating model to deliver value across the technology stack.
Banks that lack a unified AI decisioning layer have a massive opportunity to realize near-term wins while aligning to longer-term modernization efforts and enterprise architecture roadmaps. This platform-based approach is well positioned to scale AI-powered decision intelligence across diverse functional areas and accelerate time to value with each incremental use case.
Create a space for collaboration and innovation
An enterprise platform approach provides a strategic, unified space for applied intelligence. IT teams can leverage the extensible platform to expose functionality across silos while maintaining overall governance. Business leaders, analysts, and data science teams can leverage a low-code/no-code environment to author, edit, access, share, and deploy valuable decision assets, such as data features, predictive models, or business rules.
Within this space, teams are empowered to collaborate at new levels, experiment and compose new digital experiences, personalize decisions, and drive unique customer moments that differentiate the bank.
Most importantly, this approach can meet you wherever you are in your digital transformation journey. By changing the conversation from rip and replace to augment and mature, a layered approach to transformation tackles and solves problems that cut across lines of business, helping you extract immediate value out of your existing systems, all while driving better customer experiences and bottom-line results.
Learn more about how FICO Platform is helping leading banks connect, develop, and deploy data-driven intelligence.
-Jaron Murphy, Decisioning Technologies Partner, FICO