Addressing current account fraud using predictive analysis

Synectics Solutions have designed, piloted and deployed over 20 predictive models across 11 Tier 1 banks and insurance companies in the UK to help them improve their ability to prevent fraud, as well as substantially reducing the cost of doing so. To help companies without access to sufficiently relevant target data Synectics has also built a standardised predictive analytics fraud solution, for specific financial products, called Precision Standard. Customer Challenge Synectics Solutions recently worked with a well-known financial brand to help them deploy a successful fraud prevention solution, despite the client having no relevant product historical data in the geography they were launching in. The client wanted to ensure that when it launched its new Current Account it was optimising its fraud defences by utilising both the National SIRA fraud database, in conjunction with Synectics Precision predictive analytics capabilities. The following case study records the results of the proof of concept in preparation for the clients product launch. Business Need Optimise fraud prevention capability and reduce costs when launching new Current Account product. Solution Deployment of a standardised predictive analysis model in addition to SIRA fraud prevention solution. Benefit Ability to identify almost 70% of fraudulent applications while only investigating around 15% of referrals. Uplift in identification of fraud. Reduced false positives. Estimated savings of over £2 Million per year when product goes onto the market. Background Predictive analysis has become a widely used tool in financial services in the drive to improve fraud detection, and reduce investigation costs. However, many organisations struggle to deploy a viable predictive analytics programme because of a lack of sufficiently relevant or accurate target data, to build truly effective models. Because of Synectics unique position, as custodian of the National SIRA fraud prevention database, the company used its data science capabilities, and ability to leverage the National SIRA database, to successfully build a standardised product specific predictive fraud prevention model to identify fraud - despite the client’s lack of sufficient in-house data. Building the solution Over 2 million historical current account applications were utilised to train the target model, which included adverse fraud data from National SIRA. Over 25 data features were then used to build the model, including personal applicant details along with additional data features only available from within National SIRA, such as historical adverse flags. Once built Synectics comprehensively tested the model with the client in a proof of concept to prove its effectiveness. Results

How to address your repeat fraud offender problem

Helping the Utilities Sector save over £3 million in just 3 months by cutting fraud

The UK boasts a highly efficient and successful water industry, one that leads the way in research, training and accessing new water sources. Providing essential energy, water, sanitation and drainage to all households, businesses and organisations up and down the UK, the social responsibilities of utility providers are paramount. As part of their social obligations, all providers offer social tariffs to ensure domestic customers have access to a discounted service should they be struggling financially. This significant payment reduction is a lifeline for those who genuinely need it, protecting them from entering debt and ensuring continued provision of such essential services. However, these social tariffs can be abused and many customers are mistakenly or fraudulently receiving reduced charges when they are not entitled to them. A PROBLEM FOR PUBLIC SERVICE PROVIDERS To identify the scale of this problem Synectics Solutions worked with Sagacity and a number of the UK’s water companies in 2019 over a period of three months. The water utility providers it worked with covered rural and inner-city areas of the UK. Each of the companies in the pilot were experiencing problems such as: Customers dishonestly obtaining discounted services Failing to declare residency to avoid paying for their service entirely Declining to update their provider when their circumstances changed Without the intelligence in place to flag these potentially fraudulent claims or errors, these companies were exposed to considerable fraud and error and millions in lost revenue. The method that these organisations were deploying previously to address this problem involved using credit reference agency (CRA) data. The annual cost of these procedures for each company was several million pounds annually, and yet the problem continued to be an issue. "One of the reasons this fraud was not being identified through these measures was because a customer’s claim for a discounted service, or a zero-rated account, cannot be accurately verified through credit reference agency matching alone.” “This process in isolation doesn’t provide the data landscape needed to find the explicit qualifying criteria to confirm a genuine claim.” A POWERFUL PARTNERSHIP IN FRAUD PREVENTION To address this problem Synectics Solutions and Sagacity worked with the UK Government’s Cabinet Office and took the opportunity to use the National Fraud Initiative (NFI) intelligence database to help these companies understand and identify the scope of fraud or error that they were suffering. The NFI provides an invaluable database of up-to-date insights and offers 19 different data sets against which to match. This vast solution has already helped over 1200 public sector organisations to identify over £1.7 billion in savings from fraud and error.