Integrated Risk Management: Improving Fraud Detection and Identity Verification


Online fraud is on the rise, with perpetrators employing increasingly sophisticated methods to tap into the growing stream of online payments and transfers. The industry has responded in kind with state-of-the-art identity verification and fraud detection tools, leveraging physical and behavioral biometrics, device intelligence, graph networks and velocity metrics.

These tools are like screwdrivers and hammers. For the most part, they reduce fraud losses. What they obfuscate is that fraud is a component of general organizational risk. Beating the hammer too hard makes it difficult to grow your top line, as you are turning away potentially good customers for lack of credit history. Too little torque on the screwdriver combined with ballooning losses affect credit rating and access to capital. In short, using the hammer and screwdriver together inappropriately will give you a sore thumb.

Below, we break down how integrating fraud prevention and identity verification into your organizational risk management strategy can decrease losses, drive growth, and free up working capital. We also highlight how the experts at Instnt can help manage fraud so you can focus on what you do best: providing compelling customer experience for the products and services you offer.

A Brief History of Risk Management 

Risk, in its most basic sense, is the possibility that something bad might happen. Risk management is an old craft but a young science. Examples of risk management are evident as early as the 14th century in Northern Italy, with merchants and lenders sharing risk by tying loan repayments to the safe arrival of ships using maritime loans. 

Managing any type of risk hinges on the availability of mechanisms to transfer the exposure. Credit risk can be collateralized, market risk can be hedged through diversification in a large equity portfolio, and insurance can cover specific types of operational risk viz. cyber security. 

Fraud detection tools available today flag fraud risks but offer no backstop against getting it wrong. Organizations are left holding the exposure of a poorly performing detection system. In response, they spend increasing amounts of capital erecting barriers to potential customers, choking both the top and bottom lines.

Drawbacks of Traditional Risk Management 

The 2021 GARP FRM Global Practice Survey indicated that risk managers are spending on average 22% of their time on operational risk and resilience, up from 17% in 2017, the biggest jump in all risk areas surveyed. Nearly three-quarters of respondents indicated that artificial intelligence, machine learning and big data would be key focus areas for enhancing risk management practices.

Unfortunately, traditional risk management strategies address threats within individual departments or silos. Separate teams handle operational, financial or cyber risks, resulting in fragmented data and technologies.  

The disadvantages of conventional risk management programs include:

  1. Irregular risk assessment: Siloed risk management leads to inconsistencies in risk evaluations, methodologies and criteria. 
  2. Limited information sharing: A lack of communication makes identifying interconnected risks and interdependencies harder. 
  3. Inadequate resource allocation: Independent risk management processes can result in duplicative efforts or risk coverage gaps.

Looking at different risk factors in isolation gives an inaccurate picture of your organization's exposure . Since data is siloed, the problem can spread through more than one department, increasing your enterprise’s overall risk.

How Does Integrated Risk Management Fit In?

Integrated Risk Management (IRM) looks at an organization’s overall exposure. This includes market risk, interest rate risk (ask Silicon Valley Bank), reputational risk and not least of all operational risk, which includes cybersecurity and fraud. 

An integrated approach to fraud risk management allows organizations to identify fraud risks as well as transfer a portion of this risk off their books. Doing so facilitates business growth, lowers regulatory capital requirements and improves access to credit. Working with a provider like Instnt then allows organizations to effectively shift this fraud prevention and fraud loss liability off the balance sheet. By indemnifying institutions up to $100MM in fraud loss liability insurance, Instnt allows them to focus on top-line growth without the risk of turning away good customers. 


Overcome Barriers With IRM Solutions

Integration with other systems is a critical component of the IRM framework. The best solutions connect with other enterprise applications, such as cybersecurity software, financial systems and governance, risk and compliance (GRC) platforms. 

Implementing the IRM framework helps organizations:

  1. Reduce operational losses from fraud.
  2. Ensure data consistency
  3. Reduce duplication of efforts
  4. Enhance the overall effectiveness of risk management initiatives
  5. Strengthen identity verification methods
  6. Maintain regulatory compliance

Fraud management is a critical aspect of safeguarding businesses in today's digital age. Yet adopting a singular approach to tackle fraud in isolation can prove to be insufficient and ineffective. The key lies in integrating fraud management within the broader scope of overall risk management strategies. By doing so, companies can create a comprehensive framework that not only detects potential risks but also facilitates risk transfer mechanisms when necessary. 

While many organizations may struggle to strike this balance, one standout player in the field is Instnt. With a fully-integrated and automated AI technology purpose-built approach, Instnt offers a unique and innovative solution that seamlessly combines fraud and risk management. By harnessing the power of this integrated approach, businesses can stay one step ahead in the ongoing battle against fraud while ensuring the safety and success of their operations.

Reduce Fraud Risk While Integrating Risk Management Processes

Integrated risk management solutions help companies proactively manage risks and enhance decision-making processes. By integrating risk management measures, organizations can fill gaps in risk coverage, reduce duplication of effort and achieve a more efficient and comprehensive approach to handling risks. An effective system improves overall resilience and business performance.

Tech-enabled integrated risk management centralizes an organization’s mitigation strategies, preventive measures, and detection mechanisms. Moreover, the advantages of IRM solutions and frameworks are vast, from improved decision-making to increased risk awareness. By adopting this approach, you can reduce fraud risk across your company. 

In response to the shortcomings of traditional risk management approaches, Instnt has created a fully-integrated and automated AI technology purpose-built to frictionlessly let more good customers open new accounts without fraud losses. The low-code and no-code integration options make for easy implementation, increasing the number of complaints and fraud-free customer sign-ups for organizations without the typical hassle.

For Day-Zero to Day-N identity assurance and fraud prevention, turn to Instnt. Our full-stack solution complements the IRM framework and protects your business against fraud loss. Instnt’s interoperability also means you don’t have to understand blockchain or worry about complex integrations. 

See how it works by scheduling a demo.


GARP FRM Global Practice Survey 2021 
Basel III and Operational Risk
Regulatory Arbitrage in the Use of Insurance in the New Standardized Approach for Operational Risk Capital
Dun & Bradstreet – Global Business Risk Report Q2 2023
Gartner – Integrated Risk Management (IRM)

About the Author

Justin is the Chief Product Officer at Instnt. He has over 20 years experience designing and building high performance distributed systems in the telecommunications, IPTV, identity verification, social media analytics, and IIoT industries. He holds patents in computer vision and collaborative filtering. He has leveraged his technical and quantitative background to deliver AI-driven solutions at Salesforce, Alcatel-Lucent, and Bell Canada, in North America, Europe, and Africa. Justin holds a degree in mechanical engineering from University of the Witwatersrand, South Africa, as well as MS in computer science and mathematics from University of New Brunswick, Canada.