UK Bridging Lenders: Modern LOS Key to £10.3B Market Growth

The UK Bridging Finance Sector: A Milestone Achievement

The UK bridging finance sector has reached a significant milestone, with loan book values surpassing £10.3 billion for the first time in Q4 2024. This remarkable growth represents one of the most dynamic segments of the UK's alternative lending market, offering substantial opportunities for lenders who can efficiently process applications and manage risk. However, it also exposes a critical challenge: outdated loan origination systems (LOS) are becoming a significant bottleneck in an industry where speed and accuracy are paramount competitive advantages.

Bridging completions surged to £2.30 billion in Q4 2024, marking a 28.6% increase from the previous quarter and contributing to a 14.4% rise in overall loan book values. This robust growth was driven by several factors, including increased property investor activity seeking to capitalize on stabilizing interest rates, a rise in development exit refinancing, and growing demand for short-term liquidity solutions among property owners. The market's expansion reflects broader economic confidence and the increasing recognition among brokers and borrowers of the advantages offered by flexible, short-term property finance solutions. The recent expansion of the Bridging & Development Lenders Association (BDLA) with three new members, including Ward Hadaway, Bluecroft Finance, and a UK Top 100 law firm, further reinforces the association's position as the authoritative voice of the bridging and development lending sector, creating additional momentum for market growth.

The Cost of Outdated Loan Origination Systems in Bridging Finance

Manual processes and legacy systems are creating substantial operational inefficiencies for bridging lenders. These outdated approaches cause operations to slow down, increase costs, and ultimately frustrate borrowers. In a sector where funding decisions often need to be made within days rather than weeks, these inefficiencies can be the difference between winning and losing business.

The impact of these inefficiencies is quantifiable. While the average completion time for bridging loans decreased by 23% year-on-year, dropping from 58 days in 2023 to 47 days in 2024, this industry-wide improvement masks significant disparities between lenders with modern systems and those still relying on manual processes. By Q3 2024, the market showed further improvements with average completion times dropping to 46 days—the fastest since Q2 2019—and gross lending rising by 9% to £220.8 million.

The operational impact of outdated systems extends beyond just processing times. Siloed systems and poor integration capabilities prevent access to comprehensive borrower data, increasing risk exposure and limiting accurate property valuation assessments. Additionally, inflexible loan origination systems require extensive IT support for even minor workflow changes, preventing rapid adaptation to market opportunities and regulatory requirements.

Recent case studies demonstrate the tangible benefits of modernization. West One Loans completed a complex £11.1m bridging loan in just six days, saving £1.4m in potential losses for an experienced portfolio landlord who had only 10 days left to complete the purchase of a £14m apartment block. This rapid turnaround was only possible through efficient systems and strong industry relationships that enabled a property valuation in just three days.

Beyond processing speed, the operational cost differential is substantial. Case studies demonstrate the tangible benefits of modernization: AltCap, a community development financial institution, implemented an advanced Loan Management System (LMS) and reported a 30% reduction in loan processing times, leading to higher borrower satisfaction and improved internal workflows. Similarly, Alta West Capital achieved a 30% decrease in underwriting duration and a 25% improvement in client retention after adopting an optimized LMS to automate underwriting processes and enhance borrower communication.

"Fraud detection and the combination of technologies helped us accelerate legacy processes. We were able to take 50% of the documentation processes normally done by humans and completely automate them, enabling us to invest our human capital very effectively," noted Cross River Bank's Technology Chief of Staff after implementing automated underwriting with built-in fraud detection.

The most recent data shows even more dramatic improvements in the UK market specifically. According to Financial Reporter, the average completion time for bridging loans decreased by 23% year-on-year in 2024, dropping from 58 days to 47 days. This significant reduction demonstrates how technology adoption is transforming the sector's operational efficiency.

Essential Features of Modern LOS Platforms for Bridging Lenders

For bridging lenders looking to capitalise on the £10.3 billion market opportunity, understanding the critical capabilities that define modern loan origination systems is essential. A truly effective modern LOS must enable smarter, faster decisions, strengthen fraud protection, and provide frictionless engagement at all levels of the business.

Six essential features stand out as particularly valuable for bridging lenders:

• Automated decisioning - Systems that can apply consistent underwriting criteria while flagging exceptions for human review, significantly reducing the time from application to offer. For SME banks and fintech lenders, this capability has demonstrated substantial reductions in decision times from days to hours.
• Customisable workflows - Administrative tools that allow lenders to customise steps and decision points without requiring extensive coding or IT support, enabling rapid adaptation to changing market conditions. The right system comes with administrative tools that allow financial institutions to customise steps and decision points without requiring extensive coding or IT support. This is particularly valuable for bridging lenders who need to adapt quickly to market opportunities and regulatory changes.
• Integrated risk assessment - Capabilities that combine property valuation data, borrower information, and market intelligence to provide comprehensive risk profiles. Investment firms specializing in property-backed lending have used these integrated assessments to reduce valuation discrepancies, significantly improving risk-adjusted returns. Lack of automation in risk assessment processes creates inconsistent decision-making, increasing operational costs and potential compliance vulnerabilities.
• Seamless third-party integrations - Modern systems must integrate seamlessly with core banking systems, customer relationship management (CRM) tools, and document management solutions. These integrations are particularly valuable for bridging lenders in accelerating property valuations, streamlining identity verification, and enhancing credit assessment through comprehensive borrower profiles. Modern systems enable financial institutions to connect with third-party providers via APIs, allowing them to expand their capabilities through enhanced fraud detection tools, improved customer communication, or better data analytics.
• Comprehensive reporting - Real-time visibility into application pipelines, portfolio performance, and operational metrics to support strategic decision-making. Private debt funds have utilized these capabilities to provide investors with transparent, near real-time portfolio insights, strengthening investor confidence and facilitating additional capital raising. Limited reporting capabilities prevent real-time portfolio visibility, hampering strategic decision-making and proactive risk management across the loan book.
• Enhanced security features - Robust protections for sensitive borrower data and transaction details, with full audit trails for regulatory compliance. For regulated lenders, these features have proven essential in demonstrating compliance with increasingly stringent data protection requirements. A secure CRM is essential for protecting client data, especially following examples of serious data breaches at major companies.

Integration Capabilities: The Cornerstone of Effective LOS for Bridging Lenders

In today's interconnected financial ecosystem, the ability to integrate with other systems and data sources is perhaps the most critical capability for bridging lenders. Modern systems enable financial institutions to connect with third-party providers via APIs, allowing them to expand their capabilities through enhanced fraud detection tools, improved customer communication, or better data analytics.

For bridging lenders, these integration capabilities are particularly valuable in three key areas:

• Property valuation - API connections to property data providers can automate initial valuations, reducing the time and cost associated with manual assessments while maintaining accuracy. Fintech lenders specializing in property finance have reported significant valuation processing improvements through these integrations, with corresponding reductions in valuation costs.
• Identity verification - Integration with electronic ID verification services can streamline KYC processes, reducing friction for borrowers while enhancing fraud detection. SME banks implementing these integrations have reduced KYC completion times from days to minutes, with substantial reductions in manual verification tasks.
• Credit assessment - Connections to credit reference agencies and open banking platforms can provide comprehensive borrower profiles, enabling more informed lending decisions. Investment firms have leveraged these capabilities to develop proprietary scoring models that combine traditional credit data with alternative data sources, improving default prediction accuracy.

Financial institutions across the sector are recognising the importance of these integration capabilities. West Brom Building Society recently signed a core modernisation deal with Deloitte and 10x Banking to enhance its digital capabilities, while Banque Raiffeisen partnered with nCino to overhaul its loan and credit chain management functions. These examples demonstrate how financial institutions of various sizes are prioritising system integration to improve operational efficiency.

The trend toward integration extends to the highest levels of banking. In March 2025, Deutsche Bank announced it would grant its asset management arm, DWS, preferred access to private credit deals it originates, providing DWS with first-look opportunities in asset-based finance and direct lending. Similarly, JPMorgan Chase allocated an additional $50 billion to its direct lending initiatives in February 2025, strengthening its position in the expanding private credit market.

The Rise of No-Code Platforms: Empowering Bridging Lenders to Adapt Quickly

One of the most significant developments in loan origination technology is the emergence of no-code platforms. These solutions, long associated with consumer app development and business process automation, are becoming a mainstream trend in financial services. For bridging lenders, who often operate with smaller teams than traditional banks, this capability is transformative.

No-code platforms allow business users to build, test, and deploy controls directly through intuitive visual interfaces without writing a single line of code. This approach enables:

• Rapid adaptation - Bridging lenders can quickly modify workflows and decision criteria in response to changing market conditions or regulatory requirements. During recent interest rate fluctuations, lenders with no-code platforms were able to adjust pricing models and risk parameters within hours rather than weeks, maintaining competitive positioning while managing risk exposure.
• Reduced IT dependencies - Business users can configure the system without extensive technical support, eliminating bottlenecks and accelerating implementation. Mid-sized financial institutions have reported significant reductions in change request backlogs after implementing no-code LOS platforms, with corresponding improvements in business agility.
• Iterative improvement - Lenders can continuously refine their processes based on performance data, implementing incremental enhancements without disruptive system changes. This capability has proven particularly valuable for fintech lenders, who typically operate with more experimental business models and require greater flexibility to test and refine lending criteria.

The shift towards no-code solutions reflects a broader trend in regulatory focus from checklists to outcomes, with supervisors increasingly concerned with how institutions detect and prevent issues rather than simply following procedures. For bridging lenders, this means being able to demonstrate not just compliance with regulations, but the effectiveness of their systems in managing risk and protecting borrowers.

AI and Automation: Transforming Risk Assessment for Bridging Lenders

The global LOS market is projected to experience significant growth in the next five years, driven by rapid advancements in automation, artificial intelligence (AI), and digital lending solutions. According to industry analysts at Astute Analytica, the market could reach nearly $10 billion during this period. These technological innovations are fundamentally changing how financial institutions approach lending decisions, with particular relevance for the fast-paced bridging finance sector.

For bridging lenders, these technologies offer particular value in accelerating property valuations, identifying fraud patterns, and assessing borrower risk profiles—all critical components in making rapid yet sound lending decisions.

Practical applications of AI in bridging finance include:

• Automated property valuation models - AI algorithms can analyse comparable properties, local market trends, and property-specific features to provide initial valuations, reducing reliance on manual assessments. Investment firms specializing in property finance have implemented these models to screen opportunities more efficiently, enabling significantly increased deal flow assessment capacity without additional valuation staff.
• Fraud detection - Machine learning models can identify unusual patterns in application data or documentation that may indicate potential fraud, flagging high-risk cases for additional scrutiny. Financial institutions implementing these systems have reported improvements in fraud detection rates compared to manual reviews, with corresponding reductions in fraud-related losses.
• Portfolio risk management - AI-powered analytics can assess concentration risks, market exposure, and potential correlations across a lender's loan book, supporting more informed strategic decisions. Private debt funds have utilized these capabilities to stress-test portfolios against various market scenarios, enhancing risk management and investor reporting.

Recent advancements in AI technology are accelerating these transformations. Artificial intelligence is revolutionizing underwriting processes by analyzing vast datasets to assess creditworthiness more accurately and efficiently. AI systems can rapidly process alternative credit data sources, such as revenue projections and business plans, enabling faster and more precise loan approvals. Additionally, recent research has introduced a hybrid quantum-classical deep neural network framework for credit risk assessment, leveraging quantum deep learning techniques to enhance the accuracy and efficiency of credit risk evaluations.

Looking ahead, the adoption of AI in loan origination is expected to accelerate. A recent study proposes a framework for utilizing Distributed Ledger Technology (DLT) in Credit Guarantee Schemes to improve operational efficiency and effectiveness. This innovation could revolutionize risk management and trust in lending practices, particularly relevant for bridging lenders who often work with complex security arrangements.

However, the implementation of AI requires careful consideration of data governance, risk management, and ethical frameworks to ensure responsible deployment. Lenders must balance the efficiency gains of automation with appropriate human oversight, particularly for complex cases or higher-risk lending decisions.

Data Privacy and Security: Critical Considerations for UK Bridging Lenders

For UK bridging lenders implementing modern loan origination systems, data privacy and security considerations have become increasingly complex in the post-Brexit regulatory landscape. The UK's data protection framework, while based on GDPR principles, now operates independently from the EU regime, requiring specific compliance approaches for cloud-based LOS implementations.

Key considerations for UK bridging lenders include:

• UK-specific data residency requirements - While not mandated for all data types, many UK financial institutions are adopting data residency policies that require certain sensitive information to remain within UK borders. This has implications for cloud-based LOS selection, with some lenders opting for providers that offer UK-based data centers or hybrid deployment models.
• Cross-border data transfer mechanisms - For bridging lenders operating across the UK and EU, or using technology providers with distributed infrastructure, appropriate safeguards for cross-border data transfers must be implemented. This includes standard contractual clauses and binding corporate rules that reflect both UK and EU requirements.
• Security certification standards - UK financial institutions increasingly require technology providers to demonstrate compliance with specific security standards such as ISO 27001, Cyber Essentials Plus, and SOC 2. These certifications provide assurance regarding the security controls protecting sensitive borrower and transaction data.

Recent research indicates that over 60% of UK IT tech leaders are prioritising data sovereignty over the use of US cloud services, believing that reliance on foreign providers exposes the country's digital economy to significant risks, damages its domestic industry, and threatens data security. The survey, which polled over 1,000 UK-based IT leaders, also revealed a surge in interest in data sovereignty among UK IT leaders since the implementation of the US's raft of tariffs in April.

When implementing cloud-based loan origination systems, UK bridging lenders should conduct thorough data protection impact assessments (DPIAs) that specifically address the UK regulatory context. This includes evaluating how borrower data flows through the system, identifying potential vulnerabilities, and implementing appropriate technical and organizational measures to mitigate risks.

A promising approach emerging in the financial sector is the adoption of sovereign cloud infrastructure. According to a recent whitepaper by Microsoft and Core42, financial institutions can scale AI-driven services without breaching compliance requirements by adopting sovereign public cloud infrastructure. The report suggests that these environments can be used to power sensitive workloads while meeting data residency mandates from regulators. By embedding controls for encryption, audit logging and policy enforcement within a public cloud platform, institutions can access hyperscale compute for AI without losing customer data.

Implementation Strategies: Transitioning to Modern LOS Without Disrupting Operations

For bridging lenders considering the transition to a modern loan origination system, minimising operational disruption is a critical concern. The experiences of financial institutions like West Brom Building Society and Banque Raiffeisen demonstrate that successful implementation often involves partnering with technology specialists to ensure a smooth transition while maintaining operational continuity.

A notable example of successful implementation comes from Bank Central Asia (BCA), which integrated AI-powered credit scoring into its Commercial Loan Origination System (CLOS) and achieved a 40% reduction in loan processing times. Similarly, a consortium of global banks engaged Ernst & Young LLP to build Versana, a post-origination information-sharing platform for syndicated loans that digitally captures agent banks' deal data in near-real-time, enhancing operational efficiencies and reducing costs associated with legacy processes.

Bridging lenders face several specific implementation challenges that must be addressed for successful transitions:

• Legacy data migration complexity - Many established bridging lenders maintain loan data across multiple systems, often including spreadsheets and document repositories. Consolidating and validating this fragmented data presents significant technical challenges. Successful implementations typically involve detailed data mapping exercises and phased migration approaches, with parallel running of systems during transition periods to ensure data integrity.
• Specialized workflow requirements - Bridging finance involves unique processes that differ from traditional mortgage lending, including specialized property assessments, exit strategy evaluations, and complex security arrangements. Configuring modern LOS platforms to accommodate these requirements without compromising efficiency requires deep domain expertise. Lenders who have successfully navigated this challenge typically involve experienced underwriters and operations staff in system configuration from the earliest stages.
• Broker relationship management - Many bridging lenders rely heavily on broker relationships for deal flow, making broker portal functionality and integration critical to implementation success. Disruption to these channels during system transitions can significantly impact business volumes. Leading implementations include dedicated broker engagement strategies, with phased rollouts and comprehensive training programs to ensure adoption.

Effective implementation strategies typically include:

• Phased approach - Rather than attempting a complete system replacement, many lenders begin by implementing specific modules or capabilities, gradually transitioning processes to the new platform. One mid-sized bridging lender successfully implemented a modern LOS by first focusing on the initial application and decisioning components while maintaining existing systems for loan management and servicing, before extending the implementation to cover the full lending lifecycle.
• Data migration planning - Careful mapping of data from legacy systems to the new platform, with thorough validation processes to ensure accuracy and completeness. Financial institutions that have successfully navigated complex migrations typically allocate a significant portion of the total project budget to data migration activities, reflecting the critical importance of this aspect.
• Staff training - Comprehensive training programmes that focus not just on system functionality, but on how the new platform supports and enhances existing business processes. Successful implementations typically include role-based training paths, with particular attention to transitioning underwriters from document-centric to data-centric evaluation approaches.
• Change management - Clear communication about the benefits of the new system, with senior leadership visibly supporting the transition and addressing concerns proactively. Institutions that have achieved high adoption rates consistently cite executive sponsorship as a critical success factor, with regular updates on implementation progress and early wins to maintain momentum.

kennek's end-to-end lending management platform offers bridging lenders a comprehensive solution that addresses these implementation challenges. By combining automation, real-time data, and flexible API infrastructure, kennek streamlines every stage of the lending lifecycle, from origination through servicing to reporting. The platform's modular design allows for phased implementation, enabling lenders to prioritise the capabilities that deliver the most immediate value while planning for broader adoption.

Conclusion: Seizing the Growth Opportunity

The UK bridging loan market presents a substantial opportunity for lenders who can efficiently process applications, accurately assess risk, and deliver rapid funding decisions. With a collective loan book now exceeding £10.3 billion and strong growth projections for 2025, the sector's potential is clear. However, realising this potential requires modern loan origination systems that can support the unique requirements of bridging finance.

By investing in platforms that offer automated decisioning, customisable workflows, seamless integrations, and comprehensive reporting, bridging lenders can significantly enhance operational efficiency, reduce costs, and improve the borrower experience. The adoption of no-code capabilities and responsible AI implementation further extends these benefits, enabling lenders to adapt quickly to changing market conditions and regulatory requirements.

The private credit market is experiencing substantial growth, now accounting for approximately 20% of the leveraged finance market. This expansion is driven by increasing demand from larger borrowers and private equity sponsors seeking more flexible financing solutions that public credit markets cannot accommodate. For bridging lenders, this trend represents both an opportunity and a challenge—access to additional funding sources, but also increased competition from well-resourced new entrants.

Recent market surveys highlight the growing importance of Environmental, Social, and Governance (ESG) considerations in the bridging finance sector. In 2024, 74% of bridging finance lenders planned to implement an ESG strategy within the next 12 months, up from 58% in 2023. This indicates a growing commitment to environmentally responsible lending practices that modern LOS platforms must be equipped to support.

For bridging lenders still relying on legacy systems or manual processes, the time to modernise is now. As the sector continues to mature and competition intensifies, the operational advantages provided by modern loan origination systems will increasingly separate market leaders from the rest of the pack. Those who embrace this technological transformation will be well-positioned to capitalise on the substantial growth opportunities that lie ahead in the UK bridging finance market.

Our Opinion

The significant growth in UK bridging finance presents a clear opportunity, yet we observe that many lenders are fundamentally hindered by outdated operational infrastructure. Legacy systems and manual processes are not merely inefficient; they are a critical bottleneck that prevents lenders from capitalising on market speed and accurately managing risk. We believe the disparity in completion times between those with modern platforms and those without is stark, directly impacting competitiveness and profitability. Effective risk assessment and efficient processing require integrated workflows, real-time data access, and robust automation capabilities that legacy approaches simply cannot provide.

To truly seize this opportunity, lenders must adopt comprehensive platforms that provide a single source of truth across the entire lending lifecycle. We see integrated data, configurable no-code workflows, and intelligent automation as essential for achieving the necessary agility and control. Furthermore, we understand the paramount importance of data privacy and security within the specific UK regulatory framework, necessitating platforms built with these considerations at their core. We are convinced that embracing this technological shift is the definitive path for bridging lenders to enhance operational efficiency, strengthen risk management, and establish leadership in this dynamic market segment.

About the Author

Xavier De Pauw is co-founder & CFO of kennek, providing complete lending software for alternative credit. With 10 years at Merrill Lynch in structured finance, Xavier co-founded MeDirect Group and MeDirect Bank Belgium, building a €2.5 billion balance sheet. His fintech leadership includes founding Fintech Belgium and driving digital transformation at Degroof Petercam. His unique banking-to-fintech journey gives him exceptional insight into modernizing lending operations.

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