Jun 18, 2020

Addressing the problem of new account fraud

Fintech
Cybersecurity
Dean Nicolls, VP of Global Mar...
3 min
Addressing the problem of new account fraud
Jumio's Vice President of Global Marketing, Dean Nicolls, discusses how businesses should be protecting themselves from account opening fraud...

New account fraud isn’t new, but it’s fast becoming one of the biggest problems in the digital banking era, costing the financial services industry billions each year.

In fact, 48% of all fraud value stems from accounts that are less than a day old (according to RSA Security). Experian’s 2020 Global Identity and Fraud Report found that 57% of businesses report higher fraud losses associated with account opening and account takeover than other types of fraud.

This is a problem that must be addressed from many different angles.

There are 15 red flags that banks can watch out for when a new customer opens an account, according to the Association of Certified Fraud Examiners, such as mismatched names and addresses.

That’s why organisations need to adopt a risk-based approach and leverage a number of fraud signals.

Naturally, our value proposition here at Jumio is based on the capture of a user’s government-issued ID and a corroborating selfie.

But, sometimes additional data points are needed.

Address services equip financial service organisations with an improved ability to uncover deeper data relationships in real time by confirming the existence of a given address and/or confirming the subject actually lives at the address captured on the photo ID.

At Jumio, we offer two flavours of address services:

  • Address Validation: determines if the address extracted from a government-issued ID exists in the real world.
  • Proof of Residence: checks to see if the person being verified actually lives at the physical address extracted from their ID document. In the US, if the user moved, we would return whether the address provided matches the most recent address on file. 

These services help bankers and their underlying systems become more efficient and smarter, while also delivering several other compelling benefits:

  • Meet compliance mandates: Some regional regulations require you to validate addresses and establish proof of residence using independent public sources. This is especially helpful in the UK, where Financial Conduct Authority regulations require FIs to collect two different documents (one for ID and one for address).
  • Properly formatted addresses: Jumio returns a valid and standardised address which ensures that only valid billing and shipping addresses are captured and used in your systems. With this, you can help ensure that any future communications to the new customer by regular mail will be delivered to the intended person on time.
  • Single API: Instead of integrating multiple APIs for identity verification and address validation, you now just use one API.

The most comprehensive way in which to combat new account fraud without negatively impacting the end user experience is with a holistic, multi-layered approach to onboarding.

The combination of identity verification and address services helps organisations corroborate digital identities, combat new account fraud and keep their CRM data clean.

Organisations want to have higher levels of assurance when they onboard new customers, but this is becoming increasingly difficult with increasingly sophisticated fraud tactics.

Layering in address services helps triangulate a user’s digital identity with higher levels of assurance.
 

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Jul 18, 2021

Reimagining operational risk management for business value

BroadwayTechnology
riskmanagement
Finance
AI
Tom Ballard, Program Manager, ...
6 min
Tom Ballard sets out a thorough new vision for operation risk management in finance, using advanced AI and analytics technology to drive business value

The events of 2020 and 2021 have fundamentally changed how we do business, upending every industry, including investment banking. Once bustling trading floors went silent as the switch to work from home led traders to disperse locations – and gave rise to new operational risk challenges. 

Today’s dynamic regulatory landscape coupled with ongoing technological innovations have made legacy approaches to operational risk management ill-suited to tackle current challenges and complexity. And while many financial institutions have turned to digital automation and transformation projects to adapt traditional ‘revenue generating’ functions to meet their challenges and help drive growth, they must now do the same with their Operational Risk Management (ORM) functions - or risk being left out in the cold. 

The Basel Committee defines operational risk as the “risk of loss resulting from inadequate or failed internal processes, people and systems or from external events.” Unfortunately, many financial institutions still view ORM as a regulatory and compliance necessity rather than a business function that delivers real value. That means executives and risk management departments must now change their risk approach to ensure they are dynamic and flexible, can guide their organizations through complex situations, and can readily meet the evolving expectations of regulators and their clients. 

Operational Risk Management is still a young field compared to other risk sectors in the financial markets, but it has always been viewed under a broad umbrella that encompasses risks and uncertainties difficult to quantify and manage in traditional manners. ORM has also been the convergence point where corporate governance issues overlap with revenue-generating business activities, causing potential confusion between departments. 

Investment banks have too often placed undue emphasis on creating governance frameworks designed to ensure they meet Basel Committee on Banking Supervision (BCBS) standards instead of recognizing that a sophisticated ORM function can bring quantifiable value. Their desire to merely meet BCBS standards and avoid historic risks has in effect led to an outdated, analogue approach in an increasingly digital world. Savvy investment banks have grasped the value potential of ORM and begun to drive a shift in awareness about the importance of a comprehensive risk identification, measurement, and mitigation program. 

Embracing a data-driven approach

Market players now recognize that adopting a digital strategy will allow them to deploy diverse and agile risk management mechanisms. It will also empower them to develop a strong and dynamic understanding of risks while adding real value to the business. This value goes beyond meeting regulatory and compliance mandates introduced as part of the Standardized Measurement Approach developed under Basel 3. A robust approach to risk allows the ORM functions to provide actionable intelligence to support business decision-making and assume a more commercial role that supports the various business units’ day-to-day activities. And that requires an intelligent, data-driven approach with a mandate to match, one that is championed at all levels of the organization.

This type of aggressive approach and embrace of digital transformation can also strengthen how ORM functions handle ambiguous and/or improbable events, especially as traditional methods of risk analysis prove unable to manage the ever-increasing volume of data. In 2010, the total amount of data created, captured, copied and consumed equaled about two zettabytes, compared to 2018 when volumes reached about 33 zettabytes. This 26% compounded annual growth rate means that if the rate of growth steadily continues by 2024, we can expect 149 zettabytes of data created per annum. 

Available data levels will make it difficult for analogue ORM functions to successfully meet the executive expectations, however organizations that adopt a data-driven approach will find increased data volumes provide them the insights to gain a competitive advantage and ability to proactively manage their risk. 

Leveraging AI and advanced analytics for high impact

Cognitive computing technologies like artificial intelligence (AI), data mining and natural language processing (NLP) can supplement a data-driven approach and help financial institutions confidently automate decisions, optimize processes and provide a deeper insight into available data. These cognitive computing technologies can help reduce or eliminate time-intensive and repetitive tasks, often related to data collection, handling and analysis which are better suited to automation. That in turn can free up critical employees to deploy their experience, knowledge of policies, and powers of assessment to support ORM functions and achieve their goals and focus on high-impact, high-value deliverables. 

Cognitive computing can teach computers to recognise and identify risk, which is especially useful to handle and evaluate unstructured data – the kind of data that doesn’t fit neatly into structured rows and columns on a spreadsheet. Natural language processing (NLP) can analyze text to derive insights and sentiments from unstructured data, which a 2015 study by the International Data Group estimates accounts for 90% of all data generated daily. When combined with the estimated future data volumes, cognitive computing functionality presents an immense opportunity for ORM functions to add additional business value in ways previously impossible. A detection model built on cognitive analytics can manage risk on a near real-time basis and can also unlock organizations’ historic datasets that have been compiled for internal, regulatory, or compliance purposes. These datasets often contain free text descriptions that contain a potential wealth of untapped, institution-specific information and could provide valuable insight into historic operational risk losses, providing data to augment employee’s qualitative experiences.    

Teaching an old dog new tricks

There are certainly challenges to launching digital transformation projects, implementing new data-driven approaches, and introducing cognitive computing technologies, including employee uncertainty and ethical considerations. That means financial institutions must preemptively address and prepare for potential challenges before they adopt a technology-enabled approach to Operational Risk Management. They must also secure employee buy-in to ensure stakeholders use these new technologies to their full potential and to assuage any concerns that technology diminishes employees’ important role in the organization.  

It’s critical that investment banks now shift their Operational Risk Management functions and focus on becoming more adaptive and agile in an increasingly volatile, complex, and uncertain world. Over 66% of banking executives report that adopting new technologies like AI and NLP will be a key driver in IBs development through to 2025. Yet for many investment banks, their ORM functions do not leverage the powerful new tools available to them – including increased computing power, digitization, advanced analytics, and data visualization techniques – much less harness the power of cognitive computing technologies. Until ORM functions leverage these tools, executive leadership cannot allocate resources and solidify ORM’s role in business strategy, performance, and decision-making processes. 

Old habits die hard, but it’s time for ORM functions to keep pace with these new technologies, methodologies, and approaches to position themselves and their organizations for success in today’s ever-changing world. If they do not adapt, there is a real risk they may stifle the wider organization, impede new opportunities and inhibit paths to valuable business growth.

This article was contributed by Tom Ballard, Program Manager, Broadway Technology

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