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• Fraudulent transactions across Europe are an estimated €1.8 billion per annum.
• The number of bank frauds in India was up 166% in FY24.
• In the United States 26% of adults surveyed said they had personally experienced bank/credit fraud.

The explosion of online banking, neobanks, fintechs and financial applications has also made it easier for scammers to strike, making it vital to spot anomalies in transactions and strange behaviour to catch fraud early. In this scenario, Artificial intelligence (AI), Generative AI & Machine Learning (ML) are new sentinels for safe and secure business operations and technology, helping banks, financial services, and insurance (BFSI) companies stay one step ahead of fraudsters.

According to one survey, 62% of UK and US based large/mid-sized businesses intend to deploy AI-based solutions to combat the issue.

Power of AI in fraud detection: Traditional security options vs AI-driven solutions

• AI can “learn” from past fraud cases, helping ML algorithms more accurate with time. An AI model flags suspicious data/anomalies in transactional and behavioural data.
• As self-learning models, AI gets smarter over time, reducing the likelihood of repetitive errors and minimizing false positives.
• AI can not only alert the humans overseeing the systems to potential fraud, but also take action by blocking transactions or removing suspicious attached files.

AI and ML can give banks and financial companies a huge advantage with a “two-steps ahead” approach to security and risk management. For instance, for a large multinational bank, fraud detection traditionally involved wading through mountains of data, reading endless reports, and manually checking every suspicious transaction. It was a slow and painful process, often leading to delays in spotting fraud. Sometimes, customers would even have to report the problem themselves, which could mean losing a lot of money before the bank could fix the issue.

The power of AI-backed fraud prevention means that the same bank can now process copious volumes of data in real time, monitor all activity including transactions as they happen. When a possible high risk event begins to occur, it escalates this to the top of the list for review on priority. The bank can now intervene as the fraud is occurring and prevent it from happening or reduce further potential loss. Overall, this can mean better customer satisfaction with fewer losses incurred.

Using AI in fraud detection means fast detection – since AI algorithms act instantly to freeze/block a transaction/account, and offers increased accuracy over traditional methods – since AI applies dynamic rule setting, learning from itself, rather than just predefined rules. Over time, this results in cost optimization as the long-term cost of prevention vs reaction is lower.

Business impact of AI for fraud prevention

AI can be applied in multiple ways to help mitigate the risk of fraud:

• AI-driven analytics platforms can integrate diverse data sources (financial data, market data, customer data) to provide a comprehensive view of risk exposure.
• GenAI for real-time fraud detection identifies suspicious patterns of behaviour through comprehensive data analysis; this helps block and prevent potentially fraudulent activity. 
• AI-powered alert prioritization is used to classify alerts by risk level, ensuring that higher risk cases get assigned for review and intervention first, which means speedy intervention and protection for the business.
• Predictive analytics help determine future risk based on constantly updated data. AI & ML can minimize false positives, making for a seamless customer experience while ensuring security.
• Data-driven operations backed by AI/ML and robust analytics help ensure regulatory compliance and support KYC verification.
• Automation along with a strong GenAI/AI/ML powered business analytics and data engine supports scalability and boosts operational efficiency.

Use Cases for BFSI | How AI helps in fraud prevention

AI-based use cases for fraud prevention in the banking and financial services sectors can take on various forms:

1. Real-Time Anomaly Detection: Systems using GenAI can detect fraud early by learning normal behaviour and spotting unusual activity or deviations that might indicate account takeovers from identity theft or phishing. This improves speed – something that’s crucial when dealing with fraud, where every minute counts.

GenAI-powered behavioural analysis can monitor app usage, banking transactions, payments, or any other financial transaction across channels/touchpoints in real time and flag off potential threats like unusual spending pattern/unauthorized account access, blocking them and preventing fraud.

AI-backed fraud detection enables faster action, better communication and quick resolution. Traditionally, we have relied on programming languages to identify any aberrations. With ML algorithms, statistical analyses and AI, we can implement a framework that easily identifies the current unusual behaviour as well as new behaviour in the future without too many changes in the program and environment. This translates to cost savings, cuts developer time and reduces time to market/time to go live.
Dipti Pasupalak, Data & Analytics Architect, Cloud Kinetics

2. Automated Fraud Reporting and Reduced Manual Reviews: AI and ML allows for automated fraud reporting and reduces the need for manual reviews. GenAI generates suspicious activity reports (SARs) incorporating millions of data points. With a lower burden on analysts, finance and IT teams, their time can be freed up to be used to propel business growth, enhance solutions and drive innovation.

Automation also makes the process of identifying investment fraud, payment fraud, or card fraud faster, more efficient and often more accurate, with lower instances of false positives.

3. Enhanced Authentication with AI: Secure authentication powered by AI can be improved with GenAI and reduce risk in case of forgery or identity theft.

GenAI can help refine algorithms used for recognition and verification, thereby making traditional biometric verification methods more effective and limiting access to only legitimate users. This cuts the risk of unauthorized access/ account takeover fraud.

Use Case | Seamless User onboarding & authentication with AI/ML-powered solutions from AWS: In the online registration process for an account, using ML-powered facial biometrics – with pre-trained facial recognition and embedded analysis capabilities, ID verification, user onboarding and authentication – can be done securely with no need for prior ML expertise in-house.

4. Detecting Variations in Usage Patterns: AI is able to analyse metadata to detect variations from the norm that might be missed in manual reviews by the human eye. As fraudsters begin to use sophisticated methods including AI to commit fraud, the use of AI as a defense against things like deepfakes will be critical.

Take for example a scenario where a customer has been duped into sharing their net banking details with a fraudster. Normally transactions after this would not be flagged since the data compromise has not occurred on the bank’s system. But AI-based risk monitoring software will spot any unusual pattern in the transactions or amounts not in line with their normal transactions, or even things like screen resolution, currency or language used and flag it for manual tele-verification in real time, more swiftly than older methods.

Use Case | Fraud prevention with Snowflake’s scalable multi-cluster shared data architecture and advanced data governance: This can help protect merchants from fraud and risk. Snowflake-powered fraud prevention models are able to identify bad actors, detect attack vectors and block account takeover attempts.

5. Offline Fraud Prevention: AI-powered video analytics can flag off suspicious behaviour at ATMs and branches that may be linked to ATM skimming, usage of stolen cards or cheque forgery.

Use Case | Geospatial analytics and AI for fraud detection from Databricks: Geospatial data, machine learning and a lakehouse architecture from Databricks help FSI clients better understand customer spending behaviours and spot abnormal credit card transaction patterns in real time. This enhances the fraud prevention and detection capabilities of the organization, which in turn reduces losses and helps cement customer trust.

Building an AI-backed fraud detection strategy

Banks and financial institutions aren’t the only ones with an eye on AI. According to Deloitte’s Center for Financial Services, fraud losses in the United States could hit US$40 billion by 2027, on the back of GenAI.

With fraudsters already using AI, industry needs to quickly adopt an AI-backed defense as well. Here’s your roadmap:

• Create a cross-functional fraud management team: Drawn from IT, operations, compliance, legal, data sciences
• Build a multi-layered fraud detection strategy: Use AI in tandem with traditional anomaly detection systems, encryption, multi-factor authentication etc.
• Implement the right environment and tools: These must be compatible with existing infrastructure and scalable and effective. Banks must modernize their infrastructure to effectively leverage AI for fraud prevention.

By migrating to the cloud or adopting a hybrid approach and establishing a robust data platform, banks can ensure timely access to high-quality data. This real-time data empowers AI, ML, and generative AI systems to analyze patterns, identify potential fraud, and enable rapid intervention.

• Follow transparent & ethical data usage: Adhere to customer privacy norms and practise ethical data usage
• Monitor & update regularly: Retrain with new data to stay effective against new types of fraud
• Run simulations: Run controlled realistic fraud attack simulations to check robustness of the systems in place and keep ahead of advanced fraud attacks

Building an effective AI-backed fraud detection strategy into your organization requires an overall commitment to a security-conscious culture. In addition to the AI, ensure every “human firewall” is well armed to respond to fraudulent activity with regular training and a culture that encourages a security-first approach. Dipti Pasupalak, Data & Analytics Architect, Cloud Kinetics

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With the exponential growth of data, legacy databases are falling short on scalability and flexibility. Research shows that data silos pose one of the major roadblocks to informed decision-making across enterprises.

Join us on 22 June for an insightful Workshop with Snowflake, AWS and Cloud Kinetics as we show you how to break free from legacy databases and data silos by building a strong modern data foundation.

Why attend?

Through power-packed sessions, you’ll gain expert insights on how to overcome data silos with a single source of truth, democratize data access and strike the best balance between data sharing and security.

Highlights

• Why data is a double-edged sword
• Value of data modernization & obstacles organizations face while migrating legacy data
• Key considerations for a successful legacy data migration
• The power of Snowflake Data Cloud
• End-to-end data warehousing in Snowflake
• Centralization of data warehouses and lakes into a single system

The post Unshackle Your Data: Draw Rich Insights & Make Smart Business Decisions With Your Data appeared first on Cloud Kinetics.

With the exponential growth of data, legacy databases are falling short on scalability and flexibility. Research shows that data silos pose one of the major roadblocks to informed decision-making across enterprises.

This insightful Lunch & Learn with Snowflake, AWS and Cloud Kinetics showed how to break free from legacy databases and data silos by building a strong modern data foundation.

Through power-packed sessions, participants gained expert insights on how to overcome data silos with a single source of truth, democratize data access and strike the best balance between data sharing and security.

Agenda included:

9.30 – 10.00 am Welcome & Introduction by Cloud Kinetics

10.00 – 10.20 am Presentation by Cloud Kinetics

10.20 – 10.40 am Presentation by AWS

10.45 – 11.05 am Presentation by Snowflake

11.05 – 11.25 am Customer’s sharing

11.25 – 11.45 am Q&A

11.45 – 12.30 pm Lunch & Networking

The post Unshackle Your Data With Snowflake, AWS & Cloud Kinetics appeared first on Cloud Kinetics.

Indonesia, 28 Apr 2023 – Cloud Kinetics, salah satu penyedia jasa Layanan transformasi cloud terkemuka dan AWS Managed Service Provider di Asia Tenggara, mengumumkan telah mempererat kemitraannya dengan Snowflake (Penyedia Jasa Layanan Data di Cloud) untuk mendorong transformasi bisnis Data – Led di Asia Tenggara. Dengan memanfaatkan keahlian Cloud Kinetics di bidang data hybrid dan multi cloud serta keahlian Snowflake, pelanggan dapat membangun fondasi data yang modern.

Snowflake telah mengumumkan peluncuran mereka di Jakarta, Indonesia. Sebagai salah satu ekonomi digital dengan pertumbuhan tercepat di Asia Tenggara, Indonesia merupakan pasar prioritas bagi Cloud Kinetics dan Snowflake dalam fase pertumbuhan berikutnya.

Cloud Kinetics yang berkantor pusat di Singapura adalah salah satu pionir dalam meluncurkan penawaran Migrasi Data dan Modernisasi dengan Snowflake di Amazon Web Services (AWS) Marketplace.

Cloud Kinetics juga siap untuk menjajaki pasar baru yang akan mempercepat adopsi fondasi data modern di Asia Tenggara dan sekitarnya. Dengan penawaran yang tersedia di AWS Marketplace, perusahaan bisa mendapatkan solusi untuk me-migrasi data lama dan meminimalisir adanya data silo.

Memungkinkan Perusahaan Membangun Fondasi Data Modern

Data Silo dapat menghambat pertumbuhan bisnis dan merupakan tantangan bagi banyak perusahaan saat ini. Dengan pertumbuhan data yang begitu cepat, perusahaan menghadapi data silo yang terfragmentasi, tidak mudah diakses, dibagikan, atau digunakan oleh tim lain yang membutuhkan respon yang cepat.

Penawaran ini akan membantu perusahaan mengatasi data silo, serta memindahkan, menyaring, dan menyatukan data bisnis yang vital menjadi fondasi data modern untuk memberikan analisa & sumber informasi, serta memungkinkan pengguna mengambil keputusan bisnis yang tepat. Dengan kemitraan ini, pelanggan dapat memigrasikan database on-premise atau cloud mereka ke infrastruktur Snowflake yang berjalan di AWS untuk mendapatkan manfaat secara langsung.

Dengan menggabungkan Snowflake Data Cloud dengan infrastruktur AWS yang aman dengan skalabilitas tinggi, maka solusi cloud berbasis data dari Cloud Kinetics akan memungkinkan perusahaan memproses, dan melindungi semua data pengguna dengan andal. Dengan model penawaran yang fleksibel, memberikan pengguna lebih banyak pilihan untuk menyesuaikan data migrasi dan proses modernisasi untuk memenuhi spesifikasi kebutuhan pengguna.

“Dengan momentum pertumbuhan bisnis kami di Asia, kami sangat senang dapat memperdalam kemitraan dengan Snowflake untuk melayani pasar Asia Tenggara dengan lebih baik lagi. Hal ini merupakan langkah signifikan untuk memperkuat/mempercepat perjalanan transformasi digital perusahaan dan mengimbangi pertumbuhan data yang cepat, dengan memanfaatkan kemampuan data Snowflake yang berjalan di AWS,” kata Saleh M “Haji” Munshi, Group CEO of Cloud Kinetics. “Kami berharap dapat memperluas dan mengembangkan layanan data kami yang kuat untuk menghadirkan nilai tambah bagi para pengguna, sehingga dapat benar-benar berkembang dan berinovasi di dunia digital.”

“Bisnis dari para pengguna kami di ASEAN berkembang secara cepat dan data silo merupakan salah satu tantangan terbesar saat ini,” kata Ash Willis, Vice President, Partners and Alliances APJ at Snowflake “Kemitraan Snowflake dengan Cloud Kinetics ini akan membantu perusahaan di ASEAN dalam implementasi Migrasi dan Modernisasi data lebih lancar dan lebih cepat .”

Referensi

Cloud Kinetics Data Migration & Modernization di AWS Marketplace (Klik Disini)

The post Cloud Kinetics Mempererat Kemitraan Bersama Snowflake Untuk Mendorong Transformasi Data-Led Bagi Bisnis Di Asia Tenggara appeared first on Cloud Kinetics.

• Cloud Kinetics is amongst the earliest in the region to announce a Data Migration and Modernization service suite with Snowflake to be listed in AWS Marketplace
• The offering will enable organizations to build a strong modern data foundation and unlock the value of their data

Indonesia, 24 March 2023 – Cloud Kinetics, a leading cloud transformation and AWS Managed Service Provider, announced today that it has strengthened its partnership with Snowflake, the Data Cloud company, to drive data-led transformation for businesses across USA, ANZ and Asia. Leveraging Cloud Kinetics’ extensive hybrid and multi-cloud data expertise and Snowflake’s differentiated capabilities, enterprises will be able to build a strong modern data foundation, by way of a comprehensive Data Migration and Modernization service suite.

Cloud Kinetics is amongst the earliest in the APAC region to launch a joint Data Migration and Modernization offering with Snowflake on Amazon Web Services (AWS) Marketplace, a curated digital catalog that makes it easy for customers to find, test, buy, and deploy the third-party software they want, with the simplified procurement and controls they need.

Cloud Kinetics is also well-poised to enter new markets ripe for digital disruption, consolidating its presence in United States and Australia while making inroads in Thailand and Malaysia in Asia. With the joint offering readily available in AWS Marketplace, enterprises looking for solutions to migrate legacy data sources or eliminate disparate data silos will have easy access to it.

Enabling enterprises to build a modern data foundation

Data silos stifle business growth and are a challenge for many enterprises today. With data growing at an exponential rate, enterprises facing siloed and fragmented data are not able to seamlessly access, share, or tap across organizational and geographical teams to generate actionable insights.

The joint offering will help enterprises break down data silos, move, distill and unify vital business data into a modern data foundation that unlocks analytics & insights, and allows for informed business decisions. Under this partnership, joint customers can migrate their existing on-premise or cloud-hosted databases to a Snowflake environment running on AWS and gain numerous performance benefits right away.

Combining Snowflake’s Data Cloud that requires near-zero maintenance with AWS’s highly scalable and secure infrastructure, the data-driven cloud solutions from Cloud Kinetics will enable enterprises to ingest, process and protect all their data reliably. With elastic engagement models, the joint offering also gives customers greater choice and flexibility to tailor the data migration and modernization process to meet their unique needs.

“Riding on our growth momentum in the APAC region, we are thrilled to deepen our ongoing partnership with Snowflake to better serve our customers. This marks a significant step for us to empower more businesses in the region to accelerate their digital transformation journey and keep pace with rapid data growth, capitalizing on Snowflake’s intelligent data capabilities running on AWS,” said Saleh M “Haji” Munshi, Group CEO of Cloud Kinetics. “We look forward to extending and evolving our robust data service offerings to bring high value to our customers, so they can truly thrive and innovate in the digital-first world.”

“Our customers’ businesses are growing at an exponential rate and data silos present one of the biggest challenges that may jeopardize this growth,” said Ash Willis, Vice President, Partners and Alliances APJ at Snowflake. “Snowflake’s expanded partnership with Cloud Kinetics will help enterprises in the region with their Data Migration and Modernization journey, making the adoption smoother and faster for the end customer.”

Cloud Kinetics’ Data Migration & Modernization service suite with Snowflake is now available on AWS Marketplace

The post Cloud Kinetics Strengthens Partnership With Snowflake To Drive Data-Led Transformation appeared first on Cloud Kinetics.