Artificial Intelligence (AI), Robotics, and Their Impact on Cyber Security in the Financial Industry
Artificial intelligence and robotics are becoming increasingly important to how we live, work, and interact with businesses. Although AI is best known for consumer products like Alexa or Siri, it is a vital development area for businesses across multiple industries, including the financial sector.
The application areas have expanded from business intelligence to customer support, and fraud detection to customer safety, AI has plenty to offer. We’ll explore what AI can offer for the financial business, together with the security challenges you will need to address.
The Benefits of AI and Robotics for the Financial Industry
AI can drive significant benefits for the financial industry and there are actors on the market today that have already started their journey with the technology.
The customer focused areas include:
Customer service: Provide personalized customer support through informed agents or automated software bots.
Customer portfolios: Automatically optimize and rebalance customer investment portfolios according to risk profile and other requirements.
Investment and trading decisions: Develop sophisticated algorithms to predict and take advantage of trading financial instruments like stocks, bonds, options, and commodities.
Product and service development: Understand customer needs and develop financial products and services suited to audience segmentation.
Customer analysis and underwriting: segment and understand customers and risk to price loans, insurance, and underwriting more accurately.
The business competitiveness related areas include:
Business Intelligence: Dig into business and financial data to understand historic trends, optimize processes, take advantage of opportunities, and maximize profit margins.
Predictive analytics: Forecast likely future demand and revenue, based on changing macroeconomic, marketplace, and business environments.
The security and customer protection related areas include:
Customer security: Provide more robust security options to authenticate genuine users and secure customer and financial data.
Fraud detection: Detect, identify and prevent suspicious and fraudulent behavior, reducing loss and preserving customer trust.
“Know Your Customer” and “Anti-Money Laundering”: Ensure governance, management, and compliance by using AI to analyze KYC and AML data.
Although AI and robotics can deliver exciting capabilities for the financial industry, there is reason for caution. With any new technology or functionality, there are new risks, especially to cybersecurity. AI and robotics is no exception.
The Main Cybersecurity Issues with AI and Robotics for the Financial Industry
The main cybersecurity risks with AI for financial organizations can be split into three broad areas:
Threat landscape: How do you identify and manage threats to AI deployment across the entire enterprise, and how do you secure your “command & control” capability from being taken over by intruders?
Regulatory requirements: How do you elaborate on data and create business benefits and at the same time keep on track with all the current and upcoming regulatory demands?
Customers trust: How do you maintain your customers trust and perception of security.
Each of the following areas touches on one or more of these three areas.
AI and Robotics in the Customers Interaction
The perception of being served by a robot is still very unfamiliar to extensive part of banking customers. The personal interaction is a core activity in building trust and that will probably remain the same for large part of the services a bank provides today. Getting information on stocks and funds outperforming their peers via an application on your device is more accepted then being served by an artificial voice when you call your bank to apply for a house loan.
AI and Robotics Can Overpromise Benefits
AI and robotics is sometimes hailed as the solution to many of the financial sector’s more intractable issues. It is easy to overstate the impact AI will have, without considering the vulnerabilities, risks, and problems it could introduce.
AI and Robotics Security Controls are New and Unproven
AI is a rapidly-developing technology. As the frameworks, code, and software evolves, so too does the security risk. This can mean that security protocols and controls can’t keep up with new developments. Security must be built into all AI and robotic deployments and be a key consideration in product and service development.
AI and Robotics Can Be Expensive to Deploy and Secure
AI can be an “unknown quantity” – this can make securing all the various touchpoints, interfaces and layers of application very expensive and increase total cost of ownership.
AI and Robotics Can Have a Large and Complex Supply Chain
AI touches on many different areas – software development, integration, data management, hardware, and more. Each of these areas may involve multiple vendors, which creates a complex supply chain of information. Every part of this supply chain must be secured to provide a safe environment. “Security is only as good as the weakest link” applies very well in this case.
AI and Robotics Are Not Perfect
AI and robotics rely on complex algorithms and machine learning. These algorithms can be difficult to analyze and understand, possibly making it difficult to identify and resolve failures that impact business-, personal- or financial data.
Potential Solutions to AI and Robotics Management and Governance:
There are a few proactive ways your business can address the cybersecurity challenges posed by AI and robotics.
Be super clear about how you use AI when interacting with customers: Communicate and be distinct about how AI will be used in the interaction with the customers. Make sure it is optional to choose but attract the customers to use services provided with AI.
Verify the data and systems:
Consider using robust verification techniques to check the security and accuracy of data throughout the AI and robotics ecosystem. This means authenticating data at every point, inputs, analysis, processing, outputs, and deliverables.
Understand the complex environment:
Audit and understand the overall attack surface and ecosystem used by AI and robotics. Understand all the integrations between various technologies, frameworks, systems, and data. Clearly define, monitor, and protect all vulnerable areas across the organization.
Create adaptable, built-in controls:
Security controls must adapt to the rapidly-evolving nature of AI and robotics, and be part of the DNA of AI development, especially for new products and services. Build AI security into the entire lifecycle of products, services, and processes.
Understand integration between areas:
Manage and monitor all movement of data between various parts of the AI ecosystem. Ensure data is encrypted when in transit or at rest.
Create business continuity and disaster recovery:
In the event of a breach or other failure, ensure that there are robust recovery plans in place to minimize loss. Introduce appropriate security around the various levels of business, personal, and financial data.
Understand risk exposure:
Work with cybersecurity experts to understand the risks to AI environment and data and take the necessary corrective actions.
Don’t just focus on technology:
Remember that risk doesn’t just apply to technical infrastructure and applications. It can also impact all touch points with other processes, employees, customers, products, and services.
Together, these steps can protect the financial and other businesses and prepare them for the demands of AI and robotics.
We’re experts in helping you manage the risks to your financial organization, contact us today to find out how we can secure your AI and robotics deployment.
Written by Kevin Aytap