Emerge Analytics is passionate about forming partnerships with our clients to unlock potential and create value in corporate data using data analytics, machine learning and process analytics.
Machine learning has only recently become well known now that computing power is more available but the different methods have been around for a long time. Emerge Analytics have been researching the technology for almost 15 years and on the back of our research, we have built software that allows us to implement cutting-edge artificial-intelligence methodologies and have bespoke models operational very quickly.
Our models can be used to identify patterns in a client’s data like propensity to buy a product, cross-sell to another product, cancel a contract, claim against a policy, complain to customer service as well as manage insurance, credit, fraud and other risk amongst many others – all things that can become big competitive advantages.
We have done work across the customer lifecycle achieving results exponentially better than industry norms achieved using conventional model building. For example, in the area of credit scoring, we have achieved models with as much as three times the predictive power as the average score card deployed by South African credit providers.
We pride ourselves on being expert at feature engineering (the term used in machine learning circles for data preparation so that maximal predictive value is extracted from the data) and believe that the a substantial part of the value of our models comes from our work in this space.
We also have expertise in operational design and improvement which helps to maximise our models’ value. We will work with our clients to ensure value is achieved and not just leave that to them.
We have worked with some of South Africa’s top corporates including banks, insurance companies, lenders, medical companies, educational institutions and more.
Danny has a Bachelor of Economic Science followed by Fellow of the Actuarial Society of South Africa and Fellow of the Faculty of Actuaries (Edinburgh). He is currently researching a PhD in the application of machine learning to credit scoring.
He has worked in various actuarial and other analytics roles across the South African insurance industry and other financial services companies, various ministries of finance and other government ministries.
Besides for being a Founder of Emerge Analytics, Danny is also a founder of Why Guess, a company that provides services relating to the optimisation of call centres and call-centre-agent performance using machine learning methods; as well as Blue Sky Direct Sales, an outbound sales call centre that uses machine learning for optimising the use of leads and agents. Danny is also a founder of Gondwana International Networks and the Global Digital Village Group, companies involved with the creation of a pan-African communications network as well as related financial and logistical services. He was also centrally involved in the construction of Jemstep.com, one of the first robo advisors in the USA, which was recently acquired by Invesco.
Laurence holds a Bachelor of Science in Industrial Engineering and has almost 15 years of experience leading business process re-engineering and improvement projects in corporate companies across financial services and other services industries
Besides for being a Founder of Emerge Analytics, Laurence is also a founder of SNAP Recruitment, a company that provides an innovative process to make employee recruitment more effective and efficient and S Cubed Process Solutions, a company that offers process engineering consulting services to medium sized corporations.
Laurence and Danny have also founded Datastar and Datastar Logistics together, companies that use machine learning methods to coordinate the efficient and cheap arrangement of global logistics operations.
- Problem identification - Identifying key business problems that can unlock profitability
- Data provision - Understanding client data and when to enrich it with 3rd party providers
- Data preparation - Feature engineering as preparation for model building. We are particularly expert in this step and have patented feature engineering methods
- Model building - We have built our own software to apply a wide range of different machine learning methodologies when building our models including some proprietary methods
- Process integration - Ensuring the model is implemented into the operational process and enhancing the process where required
- Operational value - Monitoring model performance to ensure the model is always adding value and being enhanced