Suki Dhuphar, Head of International Business, Tamr
Until now, organisations have attempted a number of different methods of identifying cybercrime. Many have tried to improve their fraud detection by simply employing more staff to manually look for fraud. But the increasing popularity of AI now begs the question – is there a more efficient method to solve the cybercrime issue that won’t create further financial problems or dissolve existing trust?
The answer to that question is AI-driven data products, which provide an innovative solution to not only recognise cybercrime but also address it. AI-powered data products create the cleanest and most curated form of data, and when partnered with human intelligence to validate the results revealed by the AI’s algorithms, thereby achieve the highest rate of accuracy.
The best version of your data
Data products are a consumption-ready set of high-quality, clean, curated and accessible data that can be used across an organisation to solve business challenges. Organised by business entities like investment portfolios, customers or suppliers, and governed by domain, data products are the best version of data, ready to be utilised across an organisation to address various business challenges.
Many organisations grapple with incomplete or inaccurate data sets necessitating reliance on additional third-party data to gain a comprehensive view of their business entities. Data products, equipped with built-in data quality capabilities, simplify this process by automatically enriching third-party data. This not only reduces the manual complexity involved in cleaning incoming data from third-party sources but also ensures that the data is reliable and accurate.
The advanced AI techniques incorporated into data products with built-in third-party data enrichment make them fundamental tools for fraud detection. These data products provide a broader view of data sets – enriched and quality-assured data acts as an additional layer of security, bolstering existing data frameworks by enhancing their ability to detect and prevent fraud effectively.
The power of AI and human intelligence in fraud detection
For data products to be harnessed effectively for fraud detection, the synergy of AI and human intelligence is indispensable. While machine learning (ML) models used to feed the AI are adept at identifying patterns within the data, human insight is crucial for validating these findings, refining the underlying models, and translating the results into actionable and valuable outcomes.
Over time, as these data products continue to be utilised, they progressively yield results with enhanced precision, simultaneously reducing inaccuracies within the company’s data. This increasing accuracy allows human experts to allocate less time to mundane, manual tasks. Instead, they can shift their focus towards proactive thinking and process optimisation, as the majority of the data has already been cleaned and streamlined through AI and ML processes. The collaboration of AI’s computational prowess and the discerning human intellect not only accelerates fraud detection but also cultivates an environment where innovation thrives.
Fostering trust in financial services
In the rapidly evolving landscape of financial services, adopting comprehensive fraud detection methodologies is imperative. Data products stand out as a pivotal element in this ongoing battle against fraud. By meticulously consolidating and refining vast data sets, providers of financial services not only augment the decision-making capabilities of various stakeholders but also foster a deeper level of trust in the market’s integrity.
Data products are not a mere option but a crucial asset in safeguarding against the continuously changing and advancing techniques of fraudulent activities. For the UK, in particular, embracing and excelling in data products is of paramount importance. Doing so not only reflects a commitment to upholding the principles of honesty and trust but also ensures the cultivation of a resilient and thriving financial ecosystem well into the future.