Fueling Business Success With The Three Pillars Of Agility
Agility in data, analytics, and decisioning can help businesses put an intelligent foot forward into the future.
The dynamic digital economy has transformed the way customers interact and transact online – with greater flexibility and convenience of one-touch, instant, and friction-free transactions. While businesses are innovating to enhance user experience, cyber criminals are harvesting riches in the parallel dark economy that had cost the global economy as much as $600 billion in 2017, according to McAfee and the Center for Strategic and International Studies report.
Fraud Is Always Evolving
Traditionally, businesses have played catch-up with fraud threats by introducing counteractive mechanisms to each new attack type. But cyber criminals continue to find loopholes and exploit them to reap rich dividends, always one step ahead. For instance, the CHIP and PIN mechanism, which was introduced with the aim of securing cards against skimming and counterfeiting, gave rise to a whole new breed of morphed threats and pushed fraud online. Whether it is CNP fraud, bank account takeovers with stolen credentials, social engineering campaigns or new strains of malware, businesses are always playing catch up, and responding, often slowly, to patch the latest gap in their defences.
The always-on, instant, and zero-friction transaction experience through mobile phones has redefined the standards for user experience. As per the Cisco Visual Networking Index (VNI) Global Mobile Data Traffic Forecast; by 2021, more people will use mobile phones (5.5 billion) than bank accounts (5.4 billion). Ubiquitous mobile transactions and new payment methods coupled with new regulations such as PSD2 provide huge business opportunities for businesses and cyber-criminals alike.
To succeed in fighting fraud, businesses need agility with data, analytics, and decisioning.
Hurdles In The Race
Businesses are innovating to thwart evolving cyber threats, but, they are well short of the target; and the world continues to witness colossal, illicit, financial criminal gains. The Executive Agency for SMEs at the European Commission estimates global financial losses of about €1.89 trillion by 2019 due to cyberattacks.
An additional challenge for financial institutions is the need to manage disparate systems and constantly be able to plug the vulnerabilities. A typical bank may manage seven different systems for authentication, fraud and AML monitoring, resulting in siloed data, low accuracy decisions and increased costs. This prevents businesses from efficiently using the more sophisticated AI driven solutions now making an impact in the market.
Agility: The Key Ingredient For Success
To succeed in fighting fraud, businesses need agility with data, analytics, and decisioning. Data agility is crucial in tackling newer fraud types that morph on a daily basis. For this, businesses need truly omni-channel data, which is not only agnostic to the 3Vs of big data – volume, velocity, and variety – but can also respond to data from new channels and give an instant 360-degree view of data across the enterprise.
Businesses cannot know the questions they will need to answer tomorrow. But, they can prepare themselves by extracting insights from data and using them to define rules and machine learning models. Since, fraud changes its form rapidly, rules based systems must be intelligent, suggesting improvements, re-weightings, or new rules based on continuous feedback. The machine learning models must have the agility and flexibility to adapt to the required changes quickly. They must be language-agnostic and flexible to allow combining both supervised and unsupervised models to prepare for new challenges. To achieve true analytics agility, businesses must be free to use sophisticated deep learning techniques while generating human (and regulator) readable decisions.
Businesses cannot take tomorrow’s decisions today, hope they are right and relax. Who knows what the next new channel to launch will be and the new threats it will face? With new challenges arising in the future, businesses need decisioning agility to establish auto-decision, refer, and alert mechanisms that propagate decisions and automate workflows. Analysts must have the ability to unlock hidden patterns, relationships, and behaviors. It is crucial for businesses to be able to define extensible feedback labels that help capture outcomes to drive machine learning models and, therefore, continuous improvements, no matter what the future holds.
Taking a holistic view of the need for agility in data, analytics, and decisioning, Simility has built an end-to-end platform that empowers businesses to achieve greater adaptability and agility to future-proof their investments.
Latest posts by Stephen Moody (see all)
- Key Considerations for Successful Customer Onboarding - March 13, 2019
- Fueling Business Success With The Three Pillars Of Agility - August 14, 2018