This manuscript discusses the use of big data technologies in the fight against cybercrime. The underlying issues with crime analysis have been addressed, and the types of criminals that are included have been considered in light of different situations. With the use of previously published literature, the two main categories of data mining strategies managed and unsupervised learning techniques used in criminal investigations have been thoroughly examined. This should aid in determining which data mining technologies are most beneficial for investigating crimes in specific areas. A country's economy cannot function without banks, which benefit both citizens and governments. Due to people with personal stakes, banks have accounted for a significant number of crime exercises in the past. It provides a definition, discuss contributing elements to certain crime groups, and highlight challenges in identifying crimes. It is crucial to recognize these types of criminal activities before it is too late and to educate the public or a group of people about them. Conveniently, data mining systems can identify abnormal patterns within a given data source.