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Gabe Gotthard, CEOAs a software company, DataWalk is focused on unlocking the enormous potential that is hidden within the myriad of data sets that financial services companies depend on. The uniqueness of DataWalk’s breakthrough link-based analysis lies in gathering data from many disparate sources—transaction systems, customer records, internet sources, police records, watchlists, and many others —effectively combining and linking this data, and then utilize their patented technology to identify the “bad actors” to determine whether an entity has suspicious connections that may indicate fraud or money laundering. ”It is much like searching for a needle in the haystack that is trying to hide,” remarks Gabe Gotthard, CEO of DataWalk.
He explains while the traditional fraud-fighting technology such as credit scoring and behavioral analytics could easily identify individual cases of fraud, what these methods were unable to expose is fraud rings and networks hidden behind the superficial cases of fraud. By bringing together contrasting data from various sources and channels, DataWalk enables financial institutions to easily recognize these relationships between various people, places, and objects to intelligently piece together and present a unified view of the entities involved in a fraud or money laundering scheme.
Illustrating a case for insurance fraud, Gotthard mentions, “One of the key things in insurance frauds is drawing hypotheses.” to “For instance, if an investigator checks the data and finds that an expensive car is hit by a fairly inexpensive car numerous times, it is more likely than not that the accidents are faked to claim insurance money.
Extensive domain knowledge expertise and ground-breaking technology have been the “secret sauce” behind DataWalk’s customer success
DataWalk calls this process hypothesis testing; one of the many ways the company detects frauds for insurance companies.
What further makes DataWalk unique is its ability to provide outcomes that are repeatable. Gotthard explains that a major part of providing trusted results involves driving an analysis process that can be used frequently to determine accurate results for different sets of data. DataWalk makes it possible by successfully documenting the processes of an on-target analysis and run the same approach numerous times to drive similar results.
DataWalk’s robust “fraud-busting” technology also aims to address several of the prevailing challenges in the present fintech industry. Firstly, most of the solutions that are available in the market have a long and tedious implementation timeline, often measured in months or years. “Besides implementation time, traditional solutions are also slow at providing results,” adds Gotthard. DataWalk speeds up the entire implementation process by almost ten times. Secondly, DataWalk also aids to reform the exorbitant fee structure levied on companies intending to implement a traditional solution. The company believes that huge costs of traditional solutions not only make the analytic toolsets inaccessible for SMBs, but also discourage large companies from investing in new technologies.
Extensive domain knowledge expertise and ground-breaking technology have been the “secret sauce” behind DataWalk’s customer successes. Moving ahead, DataWalk is confident that it’s specialization in scalable visual analytics and link analysis coupled with numerous other patent-pending technologies will help them in making a prominent dent in the fintech market in the years to come.
Datawalk: A Cost-Effective Alternative To Palantir Gotham
Wednesday, September 04, 2024
Palantir Technologies is a well-known company that offers Gotham, a popular software product used by many large government agencies in the U.S. and around the world. A key application area for Gotham is intelligence analysis, where the challenge is to find hidden patterns and connections across vast amounts of data from multiple disparate data sources and to correlate all this data to provide a comprehensive view of any person, event, company, or anything else.
For example, a national law enforcement agency may want to combine data from their own databases, motor vehicle databases, other government databases, information from the web, and other sources in order to learn all they can about a particular criminal. Intelligence analysis software can effectively integrate this data and enable analysts to find and analyze the direct and indirect “connections” across all this data, such as the relatives, vehicles, and known associates of a particular criminal. This information can then be used to help locate a criminal and identify possible accomplices.
When it comes to intelligence analysis applications, DataWalk provides a comprehensive and affordable alternative to Palantir Gotham. Like Gotham, DataWalk is used by larger local, state, and national government agencies, though at a much lower price. It can be used by smaller organizations with greater budget constraints. Beyond its technological prowess, DataWalk's distinct business model and philosophy offer significant advantages, particularly in terms of cost-effectiveness and operational efficiency.
DataWalk serves as a powerful central "database" equipped with advanced intelligence analysis capabilities. It is an excellent alternative to Palantir Gotham, and in specific scenarios, such as machine learning operations infrastructure, DataWalk can also rival Palantir Foundry.
DataWalk's robust functionality allows for the import of data from a multitude of internal and external systems, consolidating and connecting this information within a unified knowledge graph. This integration capability extends to various applications and data silos, creating an aggregated view of entities such as individuals, phone calls, transactions, and anything else. DataWalk includes an advanced facility for entity resolution to ensure an accurate view of connected, consolidated data.
The platform is designed to scale and is capable of handling vast data quantities through visual querying, link analysis, geospatial analysis, entity extraction, and more. It supports collaborative investigations, catering not only to analysts but also to users across the entire organization.
DataWalk includes a Machine Learning facility that supports an end-to-end Machine Learning process in a single platform, thus accelerating both time to production results and delivery of better results. DataWalk also helps to optimize the capabilities of your large language models (LLMs). DataWalk integrates with various LLMs, and the DataWalk knowledge graph helps ensure that LLMs deliver the most accurate results.
As an open platform, DataWalk seamlessly interoperates with other systems, whether upstream or downstream. While it can operate as a standalone system, it is also designed to support automated enterprise workflows efficiently. The DataWalk App Center facilitates the integration of machine learning models, custom scripts, and open-source software modules, enhancing the platform's flexibility.
DataWalk’s business model contrasts sharply with Palantir's. DataWalk focuses on delivering Commercial Off The Shelf Software (COTS), maintaining a single code base and releasing new software updates quarterly. All enhancements are made available to all customers, reducing the need for extensive professional services. This model empowers customers to undertake tasks such as modifying data models and integrating new data sources independently.
This approach not only reduces the need for ongoing professional services but also significantly lowers costs. For example, DataWalk's price per server core starts at $43K, compared to Palantir Gotham’s GSA price of approximately $141K. This substantial cost difference highlights DataWalk's affordability.
DataWalk ensures that you retain ownership of your data and analyses. The platform’s algorithms are transparent, providing clear visibility into how scores and calculations are derived. Importantly, with DataWalk, you own your data and analyses. DataWalk also supports granular security, maintaining excellent performance and ensuring that data access is tightly controlled.
For organizations seeking the capabilities of Palantir without the associated high costs, DataWalk offers a compelling and cost-effective alternative. With predictable costs, frequent updates, and a robust suite of tools, DataWalk is an ideal choice for modern intelligence analysis, providing substantial savings and operational efficiency.
Company
DataWalk
Management
Gabe Gotthard, CEO
Description
Utilizes a data-driven intelligence approach to more effectively identify financial crimes affecting banks and insurance companies
