In the fast-paced world of fintech, the ability to quickly and efficiently onboard new customers is a critical factor in gaining a competitive edge. Unfortunately, many fintech companies are struggling with client lifecycle management (CLM) processes that are slow, cumbersome, and outdated. This is causing significant bottlenecks that are impacting revenue generation and customer satisfaction.
Recent industry data reveals the extent of the problem. According to a report, UK banks spend £2,613 per corporate KYC (Know Your Customer) review, a 19% increase year-on-year. Furthermore, if digital onboarding takes too long, up to 63% of customers abandon the process. The average time for corporate onboarding ranges from 45 to 90 days from application to activation. However, a complete rethink of the architecture could achieve reductions of up to 70%.
Challenges with Current Systems
The root cause of these issues lies in the outdated systems that many banks rely on. Platforms provided by established CLM vendors like Pega, Fenergo, KYC360, and Encompass were designed to digitise manual workflows and centralise documentation. While this was effective when compliance was primarily about record-keeping, the landscape has since changed.
Today, fintech companies need to compete on activation speed, not documentation quality. They require systems that can make intelligent risk decisions in real time, rather than routing documents through approval queues. Current structures create bottlenecks such as sequential processing across borders, manual validation of machine-readable data, compliance policies trapped in Excel files, and risk discovered after sales teams have set client expectations.
To address these issues, fintech companies must transition from using these legacy platforms as workflow engines to using them as decision engines. This requires a fundamental rethinking of CLM.
Five Key Architectural Shifts for CLM
Here are five architectural shifts that can help enable intelligence-led CLM:
1. Design Onboarding as Revenue Infrastructure
Most CLM platforms measure success by audit readiness, viewing onboarding as a risk management function that happens to enable revenue. However, a more effective approach is to see onboarding as a revenue function that manages risk. By focusing on the minimum information required to safely activate each product, companies can create a layered activation process that allows clients to begin transacting within days, rather than months.
2. Encode Compliance Policies as Executable Logic
Instead of having policies exist only as documentation, they should be encoded as executable logic. This makes compliance deterministic, with specific logic that auto-executes. The implementation of policy-as-code can ensure identical interpretation of rules across all jurisdictions.
3. Automate Document Intelligence, Reserve Humans for Judgment
By automating document review and extraction, validation, and risk assessment, humans can be reserved for tasks that require genuine judgment. This can lead to significant reductions in manual work.
4. Architect a Unified Intelligence Layer Over Distributed Data
By creating an API-based data fabric that treats all information as streams feeding a single analytical layer, companies can ensure consistency across all client data. This enables real-time data enrichment, composite risk scoring, and parallel processing across jurisdictions.
5. Measure Business Outcomes, Not Activity Completion
Traditional metrics that count activity are less effective than those that measure outcomes, such as time to activation, audit performance, user adoption, and customer satisfaction. Outcome-based measurement can expose the root causes of slow activation times and other issues.
The Strategic Imperative
With open banking adoption projected to reach 60.5% by 2026 in the UK and customer tolerance for slow onboarding processes collapsing, intelligence-led CLM has become essential. The architecture needs to be able to exploit consensual data access for instant risk evaluation and ensure a seamless onboarding process to meet customer expectations.
The Window for Differentiation
In the competitive fintech landscape, fast and efficient client onboarding is becoming a key differentiator. Companies that can make the shift from viewing CLM as a compliance gateway to seeing it as a revenue infrastructure will be the ones to set the pace for the next decade. The question is, will others be able to follow quickly enough to survive?
Anandhan Kannan is Lead Engineering Analyst and Regional Tech Lead (UK & Europe) at Standard Chartered Bank
Original Source: Here
