Finance Digest interview with Johnathan Bangura, VP & Head of Financial Services, Industry Solutions at Rimini Street

Published On : 11/29/2024

Navigating risk is part and parcel for any IT leader in the financial services sector. Increasing cyber threats, combined with complex and often siloed IT systems, means the need for robust ERP support is at an all-time high. As a global provider of end-to-end enterprise software support, products and services, Rimini Street empowers financial services firms to address vulnerabilities in regulatory compliance, manage enterprise risk and resolve operational issues related to AI.

Rimini Street recently partnered with Censuswide for a survey of 255 CFOs and CIOs in financial services across EMEA. The survey found emerging technologies firmly on the agenda, with 87% of survey respondents either already investing in tools like AI or planning to do so this year – the strategy is to continue evolving, not revolutionise.

Questions & Answers: 

1. How has AI helped address challenges related to data management within your organisation?

AI has been a valuable tool in improving data management, operations and more at Rimini Street.

Case Assignment Advisor, a patented Rimini Street AI application, ingests multiple vectors of information about a case and then recommends the top engineers for that case based on factors such as history of solving similar cases, client satisfaction rating solving similar cases, their availability, etc. What would take a manager 20 minutes before is now usually accomplished in under four seconds. For our clients, this has helped reduce case resolution times by 23%.

Another Rimini Street application, C-Signal, uses natural language processing (NLP) and other indicators to evaluate cases in progress. This innovation has helped to reduce the number of client cases that develop urgency by 29%.

As a company obsessed with client success, AI helps make our engineers super-human in our ability to support our clients with the speed, quality and care of the highest standards.

2. Can you provide examples of how AI is being utilised to enhance data quality and accuracy in financial services?

Certainly, some examples include:

• Data profiling and cleansing: AI algorithms can automatically detect and correct errors, inconsistencies and duplicates in financial data, helping ensure high data quality.
• Fraud detection: AI systems can analyse transaction patterns to identify and flag suspicious activities, improving the accuracy of fraud detection.
• Real-time data monitoring: AI can continuously monitor data streams for anomalies and quality issues, allowing for immediate corrections and helping to maintain data integrity.

These applications help financial institutions maintain reliable and accurate data, which is crucial for informed decision-making and regulatory compliance.

Harnessing data using AI offers an unparalleled opportunity, but it’s important to establish a robust quality assurance process that includes a human element. AI and human oversight working cohesively can help ensure that data is clearly structured and can be made sense of. This helps enable you to gain a better understanding of your customers, rates, ROI and assets, all of which can impact what will help in the day-to-day running of a business.

3. How does AI contribute to improving data security and compliance measures within financial institutions?

AI plays a significant role in several ways:

• Enhanced risk management: AI’s predictive analytics capabilities help financial institutions assess and manage risk more effectively. By analysing historical data and identifying trends, AI can provide insights into potential risks and help leaders make informed decisions.
• Improving data security: AI can enhance cybersecurity measures by identifying vulnerabilities and responding to threats more quickly than traditional methods. Machine learning algorithms can continuously learn from new data, improving their ability to detect and mitigate cyber threats.
• Regulatory compliance: AI helps financial institutions stay ahead of the regulatory curve by continuously monitoring changes in regulations and helping ensure that all processes comply with the latest standards. This is particularly important in a complex and ever-evolving regulatory environment.

Overall, AI’s ability to process and analyse datasets quickly and accurately makes it an invaluable tool for improving data security and compliance. However, that data needs to be in good shape for AI to be successfully utilised. In our recent survey of CFOs and CIOs in financial services across EMEA we found that 67% of CIOs and CFOs at mid-size to major enterprises agreed their historical ERP data would need a substantial cleanup for it to be successful with AI.

4. How do you see AI evolving in its ability to handle unstructured data sources, such as text or voice data, within financial services?

AI’s ability in this area is rapidly evolving and holds significant promise. There are two standout areas where AI is excelling:

• Customer service transcript analysis: AI has become more adept at understanding sentiment and improving these services. It can handle this task far quicker than humans, rapidly analysing and outlining call highlights and potential risks for customer support teams.
•  Personalisation for customers: AI can quickly analyse customer data and offer tailored advice, product recommendations and a personalised experience in just a few clicks.

Overall, the evolution of AI is transforming the financial services sector in this area by improving efficiency, enhancing risk management and providing deeper insights. This trend is likely to continue as AI technologies advance and become more integrated into financial systems.

5. What impact has AI had on data governance frameworks and practices within financial institutions?

Amidst the excitement of AI, it’s never been more paramount to uphold the governance of our data frameworks. It’s vital that financial institutions consider how they’re using and feeding data into AI models, and to ensure they uphold security measures. You also need clear agreements and policies with your providers and partners regarding the ownership and usage of your data and content.

However, just as AI has unlocked new capabilities for financial services firms, it has also given a new set of tools to bad actors. This must remain front of mind for institutions – to mitigate risks, institutions must be adaptable, making sure data is securely shared and stored, and to focus on the quality of the data to help ensure GenAI models deliver quality output.

Overall, AI is transforming data governance by improving data quality, enhancing compliance and strengthening risk management practices. As AI technologies continue to evolve, their impact on data governance is likely to grow, further enhancing the efficiency and effectiveness of financial institutions.

6. Looking ahead, what are some emerging trends or developments in AI-driven data management that you anticipate will shape the future of financial services?

We’ll see the traditionally risk-averse financial services becoming more proactive. In our recent survey, we found 71% of CFOs are increasing their corporate IT budgets, indicating that the financial services industry is open to technological innovation, including the likes of AI.

Looking ahead, several emerging trends and developments in AI-driven data management are poised to help shape the future of financial services. As mentioned previously, personalised services, advanced fraud detection and regulatory compliance can all be improved with AI implementation. In addition, other trends include:

• Integration of AI with blockchain: Combining AI with blockchain technology can enhance data security and transparency. This integration can improve transaction verification processes and reduce the risk of fraud.

• Ethical AI and bias mitigation: As AI becomes more integrated into financial services, there will be a greater focus on ensuring that AI systems are ethical and free from bias. This includes developing algorithms that are transparent and fair.

With the rapid development of this technology, the future of financial services will require organisations to stay flexible. To drive the best business outcomes, consider what the high-impact areas of AI are for you, and choose a best-fit vendor to get the right AI solutions at the right time.

Johnathan Bangura

About Johnathan Bangura

Johnathan Bangura, Vice President & Head of Financial Services, Industry Solutions at Rimini Street, is responsible for developing global strategy to build and grow revenues across the financial services sector, supporting growth initiatives across all geographies and serving as a thought leader for all things related to the financial services industry both internally and externally. 

Johnathan joined Rimini Street in early 2024 with more than 25 years of success in the banking and financial services industry as CFO and advisor to CEOs, CIOs and other C-suite executives, providing strategic guidance, expert advice on banking innovation, business process automation, digital transformation and best-practice eBanking services and solutions.

Jessica Weisman-Pitts

Jesse Pitts has been with the Global Banking & Finance Review since 2016, serving in various capacities, including Graphic Designer, Content Publisher, and Editorial Assistant. As the sole graphic designer for the company, Jesse plays a crucial role in shaping the visual identity of Global Banking & Finance Review. Additionally, Jesse manages the publishing of content across multiple platforms, including Global Banking & Finance Review, Asset Digest, Biz Dispatch, Blockchain Tribune, Business Express, Brands Journal, Companies Digest, Economy Standard, Entrepreneur Tribune, Finance Digest, Fintech Herald, Global Islamic Finance Magazine, International Releases, Online World News, Luxury Adviser, Palmbay Herald, Startup Observer, Technology Dispatch, Trading Herald, and Wealth Tribune.