 How to introduce RPA into your law firm? Law firms have bought into the idea, an RPA is presently being implemented to simplify work processes in the legal business. Any large law firm that requires extensive documentation, as well as data authentication, will find RPA useful. Law firms need to stay in the loop of corporate board meetings, company incorporation, secretarial issues, investors work and without a doubt, these processes require a lot of documentation. Here are six use cases of RPA in the legal industry. Assess financial risk of a law firm. According to McKinsey's Global Institute, it is possible to partially or fully automate 56% of financial planning and evaluation processes, as well as 20% of risk management workflow. Risk reconciliation performed by robots is a notable example. It requires no human intervention. RPA is flexible as it is capable of retrieving and sorting historical case cost details into the firm's database. Not only that, but it can also manage the credit ratings of clients sourced from the transaction database, as well as accounts payable from the accounting department of the same firm. Build clients risk profile. RPA can quickly generate the risk profile of the client. It works with existing e-discovery, document management, law practice management software, or imported public databases. For instance, it can fill the risk assessment forms. Recoverable information may incorporate the client's product and services, business operation location, and the length of time of the relationship between the two parties, the client and the firm. After collecting the data, RPA can establish a micro database having legally held all documents and collect all pieces of information in a single organized file. It then runs the reports, verifies for completeness, and subsequently sort it. The output is a cohesive client profile. Guarantee legal compliance. A verified client can go rogue. Updating compliance checklists before or after a case secures the law firm against fines and sanctions. RPA can carry out due diligence verifications at intervals and flag suspicious transactions with 100% accuracy and 24-7th vigilance. The software robots are capable of filling the suspicious activity report, then ping it after completion. By crawling the records of the law firm, RPA can input data needed in the transaction, as well as the subject details. Organize data between the client and the fee earner. Data management is a big challenge for large law firms. We are talking about terabytes of data here. Law professionals and practitioners need to go through these databases to build a strong case. You need to store, retrieve, and manipulate the information as efficiently as possible. RPA primarily organizes the client's requirement and business to guarantee consistency across diverse formats and frameworks. RPA is capable of moving the right documents from the document management database of a law firm to an extra net that can be accessed anytime by a client. Reduce fee overruns. Handling fee overrun is a big concern for law firms. It goes without saying that fee earners need to be extra careful while calculating their fees. The practitioner, or the firm, runs the risk of seriously hurting their image each time they take a new project. A fee earner rarely factors in the time required to finalize on a case or the resources utilized in the court. Fee overruns cause disagreement, and also open up length expense disputes and related matters. Track and audit running expenses accurately. It is important to note that a claimant would receive fewer funds and fixed recoverable costs. This is usually common in case a judge perceives that the claimed charges are disproportionate to the basis of the case. Complaints will start coming once the margin between the recoverable and the eventual charges of the client begins to widen. It is now the norm for corporate clients to employ task-based bill estimation having experienced frustration with the block billing. It is recommended that law firms buy into the ongoing technological revolution by leveraging RPA. Don't be discouraged by the input needed to implement, instead approach the implementation from an individual-centered perspective.