Our consultancy is focused on all aspects of your company. However, experience gained from several projects has shown us the most important activity is to understand and analyze your data. Using a variety of data science tools including data mining, predictive analytics, inferential statistics and machine learning enables us to present results in easy to understand interactive dashboards which highlight possibilities for improvement.

Requirement: reduce fraud in short term benefit payments due to sick certificates Strengths: well defined operational processes, centralized IT system with data collection including sick certificates, well structured organization with roles and responsibilities and dedicated antifraud department which prepared a fraud risk register Weaknesses: lack of antifraud process and use of data analytics for controlling activities, manual decision process, missing fraud risk quantification and prioritization of suspected events in order to investigate the highest risks first. In consequence no proven calculation of how much fraud really costs the organization. Solution proposed: • Introduction of a separate antifraud process interacting with the operational processes • Introduction of fraud cycle – a feedback loop from the fraud confirmation activity toward the fraud-detection activity. Newly detected cases should be added to the database of historical fraud cases, which is used to learn or induce the detection model • Data analytics at every process stage • Profiling of business process actors in order to associate risk behavior modelling

Reference Example 1 – A public insurance client

Reference Example 2 – An energy consultant

Requirement: Develop a structured approach to expanding a small business Strengths: Business owned by a successful entepreneur who is also an experienced salesperson Weaknesses: lack of organisation leading to missed sales opportunities and consequent loss of revenue. Solution proposed: • Construction of a database which can be viewed/updated on Android, Apple and Microsoft hardware. • Development of interactive reports and dashboards which are updated as required • Dashboards to analyse changes in key variables and show e.g.new clients and the salespeople who found them, energy consumed, finance, further sales opportunities with existing clients

Reference Example 3 – A credit reference bureau

Requirement: to build a common, sector-wide fraud risk management platform to be used by banks in order to prevent organized credit fraud crime and avoid insolvent clients Strengths: centralized credit register for a number of universal and consumer banks which represent significant market share in credit business. Behavioral models for credit risk assessment. Online access to credit reports for all banks. Weaknesses: no cross check algorithms for fraud risk detection because banks did not agree on common data set which might be a subject of data matching analysis. Consequently the credit applications are only checked for credit risk using behavioral models. Solution proposed: • Retrospective test on a number of banks which showed the size and value of the fraud • Preparation of a rule set and design of the antifraud shared-system • Definition of a minimum commonly used data set for application data matching • Storage of all fraud and suspected data records • Ongoing rule improvement methodology based on monitoring results which build learning set for machine learning algorithms.

ZG Consulting Limited Liability Partnership is an initiative of Tony Green and Krzysztof Zielinski. Both partners have extensive experience as business consultants helping financial institutions in the management of their credit and fraud processes. The combination of the skills of our team detailed below ensure that complex projects are delivered successfully in a timely manner.

• An independent analytics consultant who has worked on data analysis and fraud prevention with several European and African clients. Formerly National Hunter Manager and Senior Fraud Consultant for Experian Ltd. • M.Sc. in Mathematics and Computer Science. • I8 years involvement with many complex IT projects from pre-sales and proof of concept through to final delivery and post-sales support, interfacing with senior management, business and technical teams. • Specializing in data analysis and preparation of dashboards to assist management in acheiving their objectives.

• An independent consultant specializing in helping financial institutions with their IT projects. In particular, understanding It challenges and problems of implementation • M.Sc. in Computer Science and Mathematics • Skills: Project methodology, budget responsibility, strategic key account management, branding campaigns for new start-ups, understanding IT solutions in the context of business process optimization and end-user needs versus corporate requirements. • Extensive knowledge of the central European financial market especailly in Poland and Austria.

Contact: zgc@zgconsulting.eu