Fraud is a malicious activity that if you don’t look for, you won’t easily find. And, when you do discover its detrimental effects, it might be much too late in the day when the damage has already been done. Fraud is especially rampant in the financial services sector where it is an on-going threat, both internally and externally. The LIBOR (London Interbank Offered Rate) interest rate fixing where banks falsely inflated or deflated their rates to profit from trades or to improve creditworthiness is one example. The more recent Payment Protection Insurance (PPI) outrage involving banks and other lenders wrongly selling PPI to customers is yet another scandal.
Owing to the obvious vulnerability of the business, financial services organisations are forerunners in implementing next generation fraud management programmes. However, the solution does not lie in providing a reactive response to fraud. Instead, businesses should be proactive in monitoring systems and processes for evidence of fraudulent activity. This should be superseded by predictive detection models based on real-time analytical evidence.
Swindling it Online
The financial services industry has within a short span of time, taken a channel leap at improving operational performance. It has moved from face-to-face, paper-based transactions where physical cheques, securities and notes were exchanged over-the-counter or in designated trade rooms, to the ubiquitous digital platform. Unfortunately, fraudulent activity has also kept pace with this change. Most threats and malicious activities today are carried out online. These range from digital banking, mortgage and other loan frauds, to identity theft, misappropriation of credit/debit/prepaid card details and money laundering activities.
Being Proactive is Good, but…
It is a fact that the tools and technology that provide ease of use and uninterrupted service, also deliver effective fraud mechanisms. Managing unscrupulous activity is no longer a reactive process. Instead, it is a well-defined proactive mechanism that is not limited to the financial and accounting aspects of the business. Fraud management has transformed into an enterprise wide programme deployment across the breadth of the financial services business.
The industry has moved from plugging loop holes to preventing gaps that provide opportunities for fraud. The risk of not moving quickly with time could entail financial losses and huge fines levied by regulators. Event worse is the impact on organisation goodwill which affects credibility and market share.
You can Race Ahead
The current multi-channel, multi-device business landscape has resulted in the proliferation of large volumes of data. This information is dispersed across multiple systems and has multiple definitions assigned to it -- aggravating the challenges involved in extracting meaningful business insights from the data. In order to overcome these challenges and race ahead of fraudulent activity, organisations should deploy a pyramid-based approach.
Figure 1: Next generation fraud management system
Centralised Data Hub
As a start, financial services organisations should create a centralised data hub that will prevent data duplication and help manage voluminous information sources. The hub will consolidate information and serve as repository for users across the business. It will primarily be used to monitor, detect, analyse and prevent fraudulent activity, whilst offering a retrospective, albeit reactive mechanism to curb malicious behaviour.
Controls and Checks
Organisations should implement controls to prevent fraud at every stage of the transaction. For instance, deploying security and access control checks will counteract identity theft during transactions. A traceability mechanism which includes appropriate procedures and approvals as part of transaction processing will avert collusions and manipulations.
Dashboards and reports should be available to analyse available data and processes. This is necessary for day-to-day management and regulatory reporting. However, while this analysis is proactive, in terms of evidence researching, the response mechanism is reactive and not quite fool proof.
In order to stay several steps ahead of fraudsters, financial services organisations should capitalise on emerging technologies to deliver predictive analytics. This can be done by analysing internal and external data, which could be structured or unstructured such as social media information.
Businesses should employ data scientists who are specialists at creating rule engines that are predictive in nature. These professionals use a variety of tools and techniques such as web analytics, search analytics, graph analytics, behavioural analytics, to build algorithms that help predict behaviour based on existing information. For instance, by analysing the profile history of customers, rule engines can be created to assign special checks on those who indulged in fraudulent activity in the past. Similarly, algorithms can be used to predict abnormal transactions or patterns that lead to fraudulent transactions. In this way, fraud can be combatted at every step of the customer transaction lifecycle.
The ability to monitor and trace devious activity patterns and provide a quick response requires an agile response on the part of financial services organisations. Historical data, proactive monitoring and predictive analysis deliver insights into the causes of fraud, possible manifestation and trend evaluation for early detection. However, an agile response is necessary in order to prevent fraud from taking place. Agile methods work well in these situations where the scope/impact of the activity is undefined and continually evolves. At Mastek, we are experienced in using agile processes that help organisations to predict and prevent fraudulent activity. Our agile solutions can be deployed to deliver complexity at scale when required.
We have successfully deployed fraud and risk analytics solutions to predictively address fraudulent activity in the financial services, insurance, healthcare and housing benefits sector. Additionally, Kameleon, our proprietary data privacy solution is extensively used by customers to protect their data without risk, whether shared in the cloud or stored and shared with third parties.
Concerned about the security of your customer data? Connect with Jessica Shah, Business Consultant – UK Pre Sales & Solutions at email@example.com to allay your fears and provide a predictive response.