Welcome to APDS ANALYTICS
Explore a 2026 of Change in Your Business with APDS
🚀 High-Value 2026 Projects You Can Kick Off Right Now
1️⃣ Origination Scoring Using Alternative Data
Go beyond traditional application data. Use mobile data, digital behaviour, sector variables, and new proxies to widen approval rates while controlling risk.
2️⃣ Collections Scoring With Open Banking & Traditional Contact Insights
Prioritise who will cure, who needs early action, and who is likely to roll — using rich, live data that outperforms old strategies.
3️⃣ Independent Model Validation for Innovation & Governance
Strengthen your model risk framework, challenge assumptions, and give your board / auditors confidence as you scale.
4️⃣ Credit Scoring-as-a-Service
Perfect for new portfolios, new-to-credit lenders, or fintechs without the internal data science team yet. Fast to deploy, fully transparent, and high-performing.
5️⃣ Analytics & Modelling Training
Upskill your teams with hands-on, practical courses delivered by senior modellers — not junior trainers.
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About Us
We are APDS Analytics, a specialized consultancy in retail credit risk analytics and modeling, established in 2016 to provide cutting-edge analytics to the global financial services sector through contract and freelance projects.
Our focus is on innovative retail credit analytics initiatives that enhance bank revenue while ensuring compliance with relevant regulations.
We specialize in developing models alternative data sources, such as transactional data from Payment Gateways, Telco, and Government Agency Data, to address financial exclusion.
As an independent firm, we also provide validation services to help you navigate the increasingly stringent model risk guidelines.
Furthermore, we offer training and knowledge transfer sessions on Scoring Concepts, Model Monitoring, and Validation, backed by our extensive experience in the emerging markets of Southeast Asia.
The company is led by Matthew Freeman, a 30 year veteran of the banking scoring / analytics sector, with experience gained globally.
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Credit Scoring & Propensity Modelling
(Empirical Data Driven Models)
**** Click on the pictures to go to that area *****
Open Banking Analytics
(Risk, Collections & Marketing)
Generic / Expert Scorecards
No Data Models and Roadmap to Empirical
Monitoring, Validation & Model Risk
Retail Risk Management Framework
Innovation & Financial Inclusion
Bureau / CRA Analytics
Training
Partners
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Papers
Global Experience Applied Locally
Across the globe our consultants have delivered varied projects, adding experience and knowledge that can be applied to new projects, whatever the challenges
Past and Present Clients
Since 2016 we have worked with a number of organisations, directly or through partners, for which we are very grateful.
Let's add to this list, click on the link below
Analytically Powered Credit Decisioning
Origination Scoring
Determining from a risk perspective which (new) customers to accept under what terms
(assessing how rejected customers would have performed had they been accepted)
Behavioural Scoring
Behavioural Scoring
Determine how to treat existing customers from a extended lending perspective, early collections treatment etc.
Collections Scoring
Collections Scoring & Payment Projection (Recovery Modelling / Pseudo LGD)
determining the treatment of customers that have fallen into delinquency and how they roll between delinquency buckets, with the aim of maximising the amount of debt collected or recovered, at the same time as prioritising the use of organisational resources.
Colls Scoring, click to download
Benefits of Scoring
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automated and quick decisoning
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consistent decisions made
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ability to control the flow of applications into fulfilment or the flow of accounts into collections
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improved customer service as the bank proactively handles customer decisions based upon behavioural traits
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utilising summarised customer data allows the bank to determine future customer needs and offer appropriate products and services at the right time
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Maximises the amount collected / recovered from defaulted accounts
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Operational scoring will also provide a platform for the bank's regulatory models, potentially lowering capital (IRB) and provisions (IFRS9)
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The development & use of both application and behavioural scoring engenders a deep portfolio understanding across the portfolio teams
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APDS Consultants will work with your risk analytics team to deliver scoring solution whilst ensuring awesome knowledge transfer
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Take me home
Propensity & Tree Based Models
Utilising Analytics to target Marketing Effort
Propensity & Tree Based Models
Utilising Analytics to target Marketing Effort
APDS propensity models helped increase card spend by 15% in 2 months for a large Middle East issuer, see how we could help your organisation
Propensity Modelling 101, click to download
Bureau Scoring / Analytics
Does your bureau / CRA utilise proprietary scores from a global provider of scores?
Are the provided scores that are 'black box' in nature?
Do your customers need to understand the components / characteristics that constitute the bureau score for their Model Risk Compliance?
Do you want to be able to better support your clients when using your scores, through better model understanding?
APDS can build any CRA a transparent score with each characteristic available for explanation
SME Scores Based Transaction Data
Selling SME Scores
Using Payment Gateway Transaction Data for SME Scores
We Recently developed a suite of models for a Payments Gateway in Asia and realised the potential of the data as an SME Score. A Payments Gateway could develop scores from the data to : -
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Sell Loan Target List to Partner Banks, increasing volume for the bank - CUSTOMER NUMBERS UP
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Risk Assessment Scores, an origination score for a bank wanting to lend to the PG's Merchants - HIGHER ACCEPT RATE
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A Behavioural Transaction score for on-going risk, where banks wish to renew loans, upsell additional projects - REVENUE UP
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An Early Warning Score to detect which businesses with loans are starting to struggle so that pro-active strategies to save the business can be put in place - LESS BUSINESS' IN COLLECTIONS, NPLs DOWN
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Collection scores based on affordability calculated from business operations - MORE COLLECTED, NPLs DOWN
SELLING SCORES MONETARISES THE PAYMENT GATEWAY DATA, INCREASES REVENUE & DEEPENS RELATIONSHIPS WITH MERCHANTS AND PARTNER BANKS
Ask us
Regulatory Models
Compliance through Analytics
Over recent years models that predict a bank's capital and provisioning requirements have become increasingly important to both financial services providers as national and international regulators have become ever more vigilant to systemic risks within financial markets.
The main areas of focus have been capital (starting in the 2000s with the Basel Accords, accelerating after the Global Financial Crisis of 2008/9 and the introduction of global accounting standards in the 2010s.The key components of the regulations have been PD, EAD, LGD and Stress Testing models (ensuring the components can be adjusted for a range of downturn scenarios).
APDS can help your organisation build or enhance your regulatory models (quickly and efficiently), covering PD, EAD, LGD, macroeconomic models for stress testing and scenario planning & staging analytics
Monitoring, Validation & Model Risk
Model Monitoring
Confirming that your models are still working
Model Monitoring helps to determine when the operational or regulatory models deteriorate to a point that they cannot be used for the reason they were originally deployed. Monitoring also helps to determine how model performance dynamically changes of time.
Where models start to underperform the monitoring pack looks to determine the reasons why.
Key Metrics
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Gini Co-Efficient / KS Test
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Characteristic Misalignment
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Population Stability at overall and characteristic levels
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Rank Ordering
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TTD Tracking
Portfolio Monitoring helps to determine what aspects of the portfolio needs to be investigated or new strategies / policies introduced to fix problems, it's essential for portfolio health
Key Metrics
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First Payment Default
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30 days dpd at 3 MOB
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Dynamic Delinquency Reports
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Override Reason / Policy Rules Review
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Scorecard and Strategy
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Performance over Time
Independent Model Validation
Independent Models Validation using a proven & repeatable framework
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Discovery
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Gap Identification
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Data Audit - Confirmation of data being fit for purpose
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Quantitative Validation - Replication of Results (Gini, KS, Predicted vs Actual, PD Grade Ratings etc.), Model Selection amongst Alternatives
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Qualitative Validation - Confirming Modelling Assumptions, Model Selection, Post Model Adjustments
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Report & Recommend
True independence means no conflicts, no legacy bias, no pressure to make it pass & not done internally
🚨 Is your “independent” model validation actually independent?
Serious question.
Because regulators, boards, and auditors aren’t just asking whether models validate anymore —
they’re asking who validated them… and how independent they really were.
If the same organisation:
• built the model
• governs the framework
• sets the assumptions
• and “independently” validates it
…that’s not independence.
That’s internal comfort.
And everyone in the room knows it.
💡 What real independent validation looks like 👇
1️⃣ Qualitative Review
Clear, forensic assessment of documentation, data, methodology, and assumptions — with committee-ready conclusions.
2️⃣ Quantitative Validation
Deep performance testing, segmentation analysis, and statistical diagnostics that show exactly how the model behaves — not just whether it passes.
3️⃣ Challenger Models
True independence means rebuilding — benchmarking performance, stress-testing assumptions, and exploring alternative or new data sources.
4️⃣ Model Re-Development
If it doesn’t validate, we don’t walk away.
We fix it — fast — and redeploy a compliant, business-ready model.
And is external from the bank
The Framework aims to offer continuous stakeholder engagement, transparent knowledge and no validation surprises
Model Risk
Model Risk
As the use of models across the bank becomes more widespread covering almost every possible decision regulators have become increasingly about about the impact of using the models incorrectly or whether there are error within the modelling process or lifecycle.
Some regulators have introduced regulations to limit Model Risk, APDS can help banks comply or prepare to comply
Open Banking Analytics
Using Transactional Data to boost Financial Inclusion
Open Banking data is the next revolution to hit retail banking, allowing (with customer consent) participating banks to see a customer's entire banking relationships across multiple providers. This will enable forward thinking innovative organisations to steal a march on their competitors through the design of processes and procedure that helps to identify product need, assess the risk prior to application and provide tailored solutions to future customer needs.
What is needed is an comprehensive model infrastructure that takes the data, engineers features and builds the models that enable innovative bank decisioning.
APDS has a background in both risk and marketing models, therefore we feel ideally placed to help you exploit the opportunities that will arise.
Innovation - Alternative Data Scoring for Financial Inclusion & Economic Growth
70% of consumers in South East Asia are either unbanked or underbanked, by using alternative datasources to assess credit a Bank or MFI could steal a march on it's competitors
Whereas in Sub-Saharan (50%) and West Africa 33% of do not have access to traditional banking services, representing a large potential market to lend to. APDS can help you to credit score these new customers.
Combining credit industry expertise with innovative datasources to drive credit business, economic growth and empowerment
South East Asia, Africa and Elsewhere
Scoring for Financial Inclusion
Generic or Expert Trad Data Score
Alt Data
Score
Model Use, Monitoring and Refinement
towards Empirical Models and expansion to other South East Asia Countries
Combining Numerous Datasources to tackle
financial inclusion in Emerging Markets
In many developing or emerging markets there are large segments of the population that have limited access to financial services, limiting opportunity and constraints potential economic growth. The limited access also makes it difficult for bank to assess credit worthiness and therefore cannot lend to potential.
There may be limited access to the banking but the consumers do generate data through the use of technology, which can be harnessed to assess credit applications.
APDS and it's partners are innovating to combine 30+ years of credit scoring experience with the newer datasets to offer banks a way to assess credit.
We are working in South East Asia
(Vietnam, Cambodia (pilot implementation running with 6 lenders), Philippines and Indonesia (mobile scoring implemented) etc.) to drive economic growth and lift financial inclusion, the platform could be extended to African markets as well.
Model Development Training
Train your new analysts in the the ways of Credit Risk Modelling
Build your own innovative models (powered by Paragon's Modeller software), with class leading strategies with detailed hands-on training by APDS
(Tailored Training with a 12 month mentor programme for all attendees is available for your Organisation)
See next page for our Training and Mentoring Programme
Edinburgh Credit Conference 2023 - Identifying Model Risks during Model Development
Meet the Team Or Contact Us
Matthew Freeman has thirty plus years retail financial services industry experience, predominantly within the analytical risk management sphere, developing all manner of risk and marketing models, covering diverse geographies ranging from the United Kingdom and Western Europe, throughout the Middle East and India, China, Asia (North and South East) , Australasia (Australia and New Zealand)) and within emerging markets (such as Mongolia and Cambodia).
From a regulatory perspective Matthew has led teams (and built) all components of the AIRB and IFRS9 arenas in Europe, the Middle East and Asia (South East Asia, China and South Korea).
From an innovation perspective Matthew is leading the way in the use of alternative data for credit scoring / financial inclusion.