Close
Logo proxym

Empowering SME Credit Decisioning with Responsible AI

Access to credit is a vital growth lever for small and medium-sized enterprises (SMEs), which stand at the heart of economic development and growth. For banks, supporting SMEs is also a strategic way to strengthen and expand its own market. 

Yet, in many institutions, processing SME loan applications remains a slow, complex, and largely manual task. Each credit decision involves a sophisticated chain of risk evaluation, regulatory compliance, data analysis, and business rule interpretation, often managed by back-office teams.

This inefficiency not only delays financing for SMEs but also leads banks to miss valuable business opportunities. In this context, the use of artificial intelligence in the credit decision process offers a powerful solution to accelerate operations, improve accuracy, and unlock new growth for both SMEs and banks. However, this is easier said than done, as AI also brings its own set of challenges that must be addressed.

Bank Challenges: Speed, Compliance, and Trust

Credit Decisioning in the SME segment, presents several critical challenges

  • Heterogeneous data sources: Financial documents, tax records, POS data and business plans come in diverse formats with varying reliability. Indeed, Each industry sector of an SME comes with its own set of specific documents that provide valuable insights into the company’s financial health. Missing a document can distort the evaluation and give a misleading picture of the company’s financial health.
  • Complex decision logic: Sector-specific business rules and risk policies must be respected and remain adaptable. A miscalculation in risk evaluation can lead to significant financial losses for the bank or, at best, result in missed revenue opportunities compared to competitors.
  •  
  • Manual burden: Analysts spend substantial time validating, processing, and interpreting data. This can lead loan officer teams to waste time on low-value applications while missing the opportunity to focus on legitimate credit requests that could generate significant value for both the SME and the bank.
  • Regulatory scrutiny: Decisions must be explainable, non-discriminatory, and traceable — while complying with regulations such as:
    • • Basel III and EBA guidelines (loan origination & monitoring),
      • GDPR and local data privacy laws, which require strict governance of how personal and financial data is collected, processed, and stored.
      • Banks must accelerate and improve decisions without compromising on model transparency, fairness, or the protection of personal data.

How AI Can Help — Responsibly and Transparently

When deployed with care, AI can dramatically enhance the credit process

  • Learning from historical data: ML models uncover patterns from past loan decisions to guide new applications.
  • Generating adaptive business rules: It is now possible to build ML models that evolve with new trends and risk signals.
  • Estimating Probability of Default (PD): Each borrower is scored using context-specific models for better credit risk assessment.
  • Supporting loan officers: AI offers clear recommendations and justifications, aiding — not replacing — expert human judgment.
  • To make this responsible and compliant, existng technology allows to integrate:
  • • Explainable AI methods such as SHAP, LIME, and interpretable models;
    • Bias detection and correction to ensure equitable treatment;
    • Strong personal data protection mechanisms, including:

        • Data minimization and anonymization where applicable;
        • Explicit model design to avoid processing sensitive data beyond regulatory boundaries;
        • Full compliance with GDPR and similar frameworks, ensuring transparency and consent at every step.

     

Our End-to-End Approach

We offer a complete AI-driven credit solution

  • Data pipeline and governance
    • We build secure pipelines for data ingestion, cleansing, enrichment, and lineage tracking;
  • • We support multiple data file formats with automatic reading and data extraction
  • • Our processes ensure that personal data is handled in full compliance with privacy laws.
  • Tailored ML model development
  • • Our models are designed for explainability, auditability, and data protection;
    • Risk teams are involved early to align with compliance and internal governance.
  •  
  • Deployment and integration
    •     Seamless integration into your existing core systems or credit platforms of proven LLM technologies and models;
  • • Hybrid workflows that combine automation and human oversight.
  • Training and handover
  • • We train internal users on the tools and models;
    • We enable your teams to maintain and govern the solution independently, with full control over model updates and data compliance.

Building the Future of SME Lending with Trustworthy AI

The future of SME lending is not only intelligent — it is responsible. AI should go beyond automation to foster trust, transparency, and respect for personal data.

At Proxym, we enable financial institutions to deploy compliant, explainable, and privacy-aware AI solutions that revolutionize credit decisioning — without compromising on customer protection or regulatory standards.

Bankerise Platform, powered by AI

A key driver of this transformation is our AI Powered Bankerise Platform. Thanks to its modular architecture, Bankerise allows seamless integration of AI Agents, enabling a shift from static, process-based workflows to adaptive, intelligent decision systems.

This modularity made it possible to embed Agentic AI capabilities directly into the platform — enabling smarter interactions, contextual understanding, and real-time insights — all without disrupting core processes.

We go further by implementing an AI human-in-the-loop approach, setting a real collaborative framework that integrates human intelligence and oversight into AI system development and operation to enhance accuracy, reliability, and ethical decision-making. Enhancing LLM-driven decisions with human feedback, ensures that the system continuously learns, adapts, and aligns with expert judgment, local context, and evolving regulations.

Hence, we believe that AI should not replace human. Rather, it should empower them. That’s why we build intelligent Bankerise Customer Service Application that:

  • • Support loan officers in their daily work,
  • • Accelerate processing times, and
  • • Improve decision quality, while maintaining full regulatory compliance, data privacy, and decision traceability.

At Proxym, we’re not just building solutions – We’re shaping a responsible, human-centered AI ecosystem for the future of finance

Interested in putting responsible AI to work in your credit value chain? Let’s start the conversation.
👉 https://www.proxym-group.com/digital-engagement-platform/

TAHAR JARBOUI

Costumer Solutions Direction