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Gautam Kishore
Principal Consultant, Fraud Incubation & Enablement, EMEA & APAC

How would you describe SAS Consulting’s Incubation team? 
At SAS, our Incubation team is dedicated to pioneering solutions across multiple fraud domains, including banking fraud, procurement integrity fraud, and insurance fraud. We work closely with financial institutions and organizations to enhance their fraud detection and prevention capabilities, leveraging advanced analytics, machine learning, and AI technologies.

What pain points does the Incubation team address?
The financial and insurance industries, along with procurement functions, are continually challenged by evolving fraud tactics that surpass traditional security measures. We address these pain points by developing solutions that not only detect but also predict fraudulent activities in real-time, minimizing financial losses and safeguarding organizational integrity and customer trust.

• Our team collaborates closely with partners and presales teams, enabling them to implement new fraud solutions effectively.
• We focus on developing reusable assets that can be adapted for different regions, ensuring robust delivery while optimizing costs.
• We support the entire process of fraud model development and deployment. Our Incubation team possesses an extensive list of features that contribute to building high-performing fraud models, consistently earning praise from our banking customers.
• We frequently support the implementation of complex fraud topologies within the banking sector.

What are some key fraud trends in your area, and how does SAS respond?
A significant trend in fraud prevention is the ongoing digital transformation and the increasing sophistication of cyber threats. SAS responds to these challenges by delivering advanced solutions that incorporate real-time data analysis, AI-driven anomaly detection, and adaptive learning algorithms, helping organizations stay ahead of fraudsters across various industries.

• As new fraud trends emerge, our team is at the forefront of developing the most effective rules and models specifically tailored for banking fraud.
• We respond to sudden customer demands for demonstrations by providing robust support to our presale’s teams. This ensures they remain competitive and can meet customer expectations promptly.
• We prioritize the rapid deployment of fraud solutions to help our clients meet regulatory mandates efficiently.

What makes SAS unique in these areas?
SAS stands out due to its deep industry expertise, robust analytical capabilities, and the flexibility of its solutions. Our unique approach combines domain knowledge with innovative technologies, enabling organizations to tailor their fraud prevention strategies to their specific needs, whether in banking, procurement, or insurance.

We leverage analytics/AI across solution areas. Analytics and AI are at the heart of our solutions. We use these technologies to uncover hidden patterns in transaction and procurement data, enhance predictive modelling, and automate decision-making processes. This not only improves the accuracy of fraud detection but also enables quicker responses to potential threats across all the sectors we serve.

What makes working with risk/fraud a challenge?
Working in risk and fraud analytics presents several challenges, including staying ahead of rapidly evolving fraud tactics and managing the complexity of integrating new technologies into existing systems. However, these challenges drive innovation and push us to develop more effective solutions across different types of fraud.

What makes the risk/fraud field exciting to work in? 
The dynamic nature of fraud, coupled with the opportunity to make a tangible impact on financial security, organizational integrity, and customer trust, makes this field incredibly exciting. Every day presents a new challenge, and the satisfaction of outsmarting fraudsters and protecting stakeholders is immensely rewarding.

Wrap-Up thoughts
As members of the SAS Incubation team, we take pride in contributing to our mission of advancing fraud detection and prevention across various sectors. The blend of analytics, AI, and real-world problem-solving makes our work both challenging and exhilarating. We are eager to continue innovating and driving positive change in these vital areas.

Gültap Songur Ergin
Head of Risk and CI,
Copenhagen, Denmark

What areas and solutions do you work with?

I specialize in SAS Risk Management solutions and associated value propositions. Our presence in the Nordics is significant, particularly in the domain of risk management, with regulatory compliance driving much of our engagement with clients in both the banking and insurance sectors.

What solution areas do you focus on?
SAS Risk Management solutions are used extensively across various industries, including the financial sector as well as the commercial sector. Our implementation projects cover a wide range of areas, such as integrated balance sheet management (Asset Liability Management, Expected Credit Loss, Market Risk); regulatory compliance (IFRS9/CECL, IRRBB, Regulatory Stress Testing, Regulatory Capital Management, EBA Regulatory Reporting, Insurance Capital Management); and risk modeling and decision lifecycle (Model Risk Management, IRRBB Modeling, Credit Lifecycle Management).

Additionally, we focus on risk platform transformation to drive more efficient and effective processes.

As part of SAS PSD, we work on adapting SAS Risk solutions to optimize credit risk calculations, scoring, and reporting, as well as financial management reporting, internal and EBA reporting, and asset liability management. This also includes preparation for ECB audits and a wide range of analytics-related use cases. We provide subject matter expertise and consulting, in tandem with SAS technical resources, to deliver comprehensive solutions during implementation projects.

What business problems (pains) are you addressing?
We address several key business challenges, mainly revolving around improving risk management effectiveness while reducing the total cost of ownership. We help customers respond more swiftly and accurately to emerging risks, all while ensuring regulatory compliance. 

Specific pain points include: model lifecycle management (empowering banks to effectively manage model risk across the entire lifecycle); process and model governance (enhancing governance, eliminating manual processes, and automating workflows to standardize operations); risk infrastructure (developing systems that integrate with open-source technologies, address big data challenges, and scale seamlessly to the cloud); and new regulations and data requirements (meeting emerging regulatory demands, such as CRR3 (Basel IV), CSDR, ESG, DORA, and EIOPA SII).

What are the key trends in your area, and how does SAS address them?
Data, technology, and governance remain core challenges, with growth, profitability, regulations, cost reduction, and digitalization as the primary drivers for risk management.

In the current rapidly evolving landscape, there’s a growing concern that existing regulatory capital, risk management, and operational decision-making models may be outdated. Model risk has become a critical concern for financial institutions. Banks must frequently update their models to comply with the latest regulations and trends.

How does SAS address ever-changing regulations and trends?
Here are some that are top of mind: Transitioning from legacy systems to cloud-based platforms, enabling banks to manage larger datasets more effectively; developing a cloud-first approach that emphasizes delivery, availability, automation, and scalability to establish a cloud-native risk ecosystem; providing an intuitive user interface (UI) for actionable analytics; utilizing API-driven components for seamless integration within the risk solution ecosystem and broader enterprise data environment; and supporting open-source cashflow logic while leveraging the best of SAS’s proprietary tools.

What makes SAS unique in these areas?
Our guiding principle is “Customer First.” What sets SAS apart is our commitment to delivering value through robust risk management solutions that enhance regulatory compliance, improve transparency, and offer better performance. We address our customers’ business and IT challenges with strong governance in a cost-effective and timely manner. 

What are some key differentiators?
Key differentiators include: High-performance computing (SAS's ability to handle large analytic workloads, coupled with its comprehensive suite of analytics tools); deep domain knowledge (embedded within our risk solutions, giving us an edge in understanding and addressing industry challenges); and completeness and flexibility (SAS Risk solutions offer a complete and flexible technology stack, enabling seamless open-source integration).

SAS is consistently recognized as a leader in Model Risk Management, IFRS9, and Risk & Finance Integration, which distinguishes us from competitors and is a source of pride.

How do you work with Analytics/AI in your different solution areas?
In our risk projects, we focus on operationalizing analytics by leveraging AI-driven decision-making. We use AI in areas such as data quality, model interpretability, fairness and bias assessment, natural language processing for insights, and bias mitigation. These capabilities are integrated into model lifecycle management, enhancing the decision-making process across our solutions.

Where do you see the key challenges for SAS Risk Solutions?
Key challenges in the risk space include: In-house development (budget and cost constraints on the customer side); competition(increasing competition from niche players and SaaS products); technology (continued reliance on legacy technology systems); and regulatory interpretation (variations in how regulations are interpreted and applied).

What makes risk exciting to work with?
Our approach to risk management implementation enables banks to meet both functional and non-functional requirements through strategic technology solutions. Some of the highlights include: fully automated, end-to-end process execution that is auditable and aligned with data management principles; enhanced agility and control, allowing for seamless model changes and impact analysis using standard reporting, sensitivity analysis, and what-if analysis; improved efficiency, processing power, and transparency in model execution; and new reporting analytics capabilities that meet increasing regulatory, auditor, and management expectations.

Additionally, working across various geographies allows us to leverage our industry and risk domain expertise to benefit different clients. Ultimately, seeing satisfied customers, successful project implementations, and the establishment of long-term, trustworthy relationships is highly rewarding. It allows us to help clients stay ahead of regulatory changes, manage emerging risks, and remain technologically relevant.

Nitzi Roehl
Senior Manager, US Consulting Services

What led you to pursue a career in the technical space?

In short, my curiosity and my dad. Since childhood, I’ve wanted to understand how things work. I enjoyed helping my father fix electronics and small appliances around the house, eager to learn about their inner workings. Through those interactions, I gained valuable insights into the importance of using the right tools, applying the right techniques, and following a methodology to solve problems.

A few years later, I decided to become an engineer like my dad, but I chose electrical engineering. As I delved deeper into the math and physics behind electrical systems, I became increasingly interested in controlling and optimizing those processes. I completed my Master’s in Control Theory and Statistics, which eventually led to a Ph.D. in the field of Artificial Intelligence and a career in research.

What brought you to SAS?
I soon realized that I wanted to apply all that theory to help organizations solve complex business problems and make better decisions using data and math. This desire led me to a career in consulting. SAS’s reputation as a leader in advanced analytics was the perfect fit for me—it provided the opportunity I was looking for to reconcile the researcher and the engineer within me.

Describe the team you lead—how they typically engage with SAS customers?
I am very fortunate to work with a group of talented and high-performing individuals. We are part of the Analytical Consulting and Enterprise Solutions services team in the U.S. Our team brings together a broad range of skills and expertise, including statistics, machine learning and AI, operations research, econometrics, data engineering, and the production deployment of complex analytical systems.

We work with customers across various industries, with highlights in consumer goods, energy, retail, and media. The variety of customer challenges we encounter keeps us busy and engaged.

We help customers improve supply chain planning by providing best-in-class forecasts of demand. We analyze customer-level data to model behaviors and assist organizations in optimizing their marketing and sales strategies. Additionally, we develop machine learning models to forecast short-term residential energy usage.

We are typically involved in the sales process from the beginning, starting with early-stage planning and devising analytical roadmaps. We work on use-case-specific proofs of value, deliver quick-start enablement services, and implement comprehensive analytical models and processes. We also provide post-implementation support to help our customers protect their investments and realize the promised benefits of their SAS enabled data science assets and processes through services such as expert consulting and model care.

How has your team’s collective experience helped with customer engagements?
The breadth and depth of our data science and advanced analytics knowledge, combined with industry-specific experiences, is one of my team’s strengths. We learn from each other, our amazing consulting customers, and our sales partners, constantly seeking opportunities to innovate and bring efficiencies to our services.

What is an example of how working together as a team matters?
A great example is the unique approach we developed a few years ago to forecast new products and services. This challenging problem is highly relevant for our retail and consumer packaged goods (CPG) customers, but it has also been applied in the telecommunications, manufacturing, and state departments of transportation. We continue to enhance and streamline our analytical approach and implementation assets as we work with different types of data and learn from our customers' experiences.

By supporting each other and valuing input from every team member, we’ve been able to standardize and automate much of the code we’ve developed over time to support our energy customers. This not only improves the customer experience but also makes it easier for the team to deliver fast, high-quality results.

The data analytics space is constantly evolving. How does your team stay on the leading edge?
My team members are deeply invested in expanding their skills. They frequently take classes on new analytics techniques, including open-source technology. We share course links, scientific papers, blogs, and more with each other. We are part of communities of practice, and some of us are members of scientific organizations. We also collaborate regularly with SAS R&D teams, sharing our experiences from the field and learning about the new functionalities and innovative technologies they are developing.

We are avid learners, inspired by the analytical challenges our consulting customers face. This provides us with opportunities to research new methods and experiment with new techniques while tackling real-world problems. Our field is dynamic, and so are we!