Fractal Labs turns data into measurable and scalable financial and risk tools.

Enabling your business to run faster, streamlined and overcome regulatory, financial and fraud challenges.

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performance

Performance

Leverage new generation technology to work smarter and faster.

scale

Scale

Maintain Lower costs with higher output.

support

Support

Access to experienced live backend support

flexability

Flexability

Tailor workflow capabilities to meet end-to-end objectives. Set your own hot keys, link windows, alerts, signals, and more.

Data is nothing if not converted to actionable insights and used to make smart business decisions. With our team of scientists, stack of bespoke technology, and industry experience, Fractal Labs can simplify your raw data, enabling you to unlock insights for strategic development within your organisation.

Our products

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sales lab

Sales Lab | Lead Optimisation

Scrutinisation of clients’ personal data to optimise leads and define quality and well as which clients are more likely qualify and convert into a sale.

sales lab

Customer Experience

Clients are presented with products suited to them based on their personal data.

sales lab

Customisable

Flow can be adapted according to product offering of the business and partners.

Client journey

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sales lab

Sales Lab

Optimise leads and define quality

score lab

Score Lab

Supervised machine learning

offer lab

Offer Lab

Transactional behaviour modelling

lender lab

Lender Lab

Reducing risk and improving turnaround time

fraud lab

Fraud Lab

Identify organized groups of fraudsters

risk lab

Risk Lab

IFRS 9 compliant expected credit loss modelling

Operating countries

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Over 2019, our solutions produced optimised credit scores for over 1.5m consumers across 10 geographies, approving total loans in excess of USD 200m.

Africa

  • Kenya      
  • Malawi      
  • Mozambique      
  • Namibia      
  • South Africa
  • Tanzania      
  • Uganda      
  • Zambia      
  • Zimbabwe      
  • Uganda

Oceania

  • Australia      
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Meet the team

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Timothy Nuy

Founder

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Timothy has 8 years of international experience across countries such as Germany, Netherlands, United Kingdom in Europe and Botswana, Kenya, Mauritius, Mozambique, Tanzania, Zambia, Zimbabwe in Sub-Saharan Africa, 4 years of experience working as a managing director and extensive experience in investments, mergers & acquisitions and corporate advisory. He joined Nifty Financial in 2014 and has constantly exceeded target and led the company’s acquisition for banks and micro-finance institutions. Timothy has expert and specialist knowledge of a wide range of financial markets and investment processes, including full treasury and corporate fundraising activities. He has extensive experience in financial analytics and a CFA Charterholder, highly developed skills in business planning, valuations and data analytics.

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Gunther Marais

MD

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Gunther has 9 years’ experience in banking risk management with a focus on stochastic modelling, counterparty risk and derivative valuations. He joined MyBucks in 2015 as a credit risk analyst and in 2019 took up the role of group CRO overseeing all risk reporting as well as the IFRS 9 modelling for the group. Gunther holds an MSc in Applied Mathematics

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Leilanie Uys

CDO

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Holds a Master’s Degree in Computer and Electronic Engineering which was focused on the automatic classification of digital signals. Completed her master’s degree at the CSIR’s. She has been working in the FinTech industry since, specialising in credit risk modelling and data engineering.

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Dirk Postma

Credit Risk Analyst

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Holds a MSc in Chemical Engineering and specialises in Data Science with a focus on financial risk modelling. He brings the engineering- and problem solving mindset to the team. Dirk is responsible for the IFRS 9 risk modelling and other machine learning projects.

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Contact Us

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Find out more about how Fractal Labs can transform your business.

Fractal Labs

The Wedge - 1st Floor
43 Garsfontein Road, Waterkloof, Pretoria, 0145

+27 12 045 0701 | info@fractallabs.net

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