As 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.